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From turning manual handwheels to simultaneous 5-axis aerospace cuts. Here is how the milling process completely evolved over the decades: Manual Knee Mills (The Handwheel Era): Early machinists relied entirely on Bridgeport-style manual mills, mechanical dial indicators, and tactile feedback. Every radius, feed rate, and depth of cut depended... 100% on the operator's hands, feel, and math. The NC & CNC Revolution (G-Code Takes Over): The shift from punched tape numerical control (NC) to computerized numerical control (CNC) in the late 20th century transformed repeatability. Suddenly, complex profiles and tight tolerances could run automatically overnight with zero manual crank adjustments. Advanced Tooling & Dynamic High-Efficiency Milling (HEM): Early high-speed steel (HSS) cutters gave way to coated solid carbide and ceramic inserts. Modern dynamic toolpaths now utilize low radial engagement and deep axial cutting at insane spindle speeds, slashing cycle times while preserving tool life. Multitasking & Simultaneous 5-Axis: Today's state-of-the-art machines don't just cut in 3 axes-they tilt, rotate, and even combine turning, additive laser cladding, and probing in a single clamping setup, eliminating stacking errors completely.show more

Mechanical Knowledge

150,122 subscribers

35,596 views • 16 days ago •via X (Twitter)

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4 Comments

Randall Magnum15 days ago

That’s a pretty basic, un-nuanced, and low effort take?

david watson15 days ago

I ran a Bridgeport in a mold shop for a couple of years long ago. When I asked the owner why I didn't at least have an x axis motor drive his response was, you've gotta feel the wheel. I felt that wheel about 10,000 turns a day.

ೃ⁀➷ sofi ❀15 days ago

Manual mills forced you to feel the cut. 5-axis removes that feedback. Do operators still learn that intuition?

Because of That15 days ago

AI algorithms enable adaptive machining. Mills can now adjust cutting parameters in real time based on changing material properties and tool wear. Will AI make these processes more efficient and cost savings be passed on to the consumer?

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$They say, Any Sufficiently advanced engineering is indistinguishable from art. This is what that looks like. A 5-axis Hermle machining centre isn't simply shaping metal. It is coordinating five axes of motion simultaneously while its spindle turns at up to 18,500-41,000 RPM, following tool-paths that can contain hundreds of thousands or even millions of lines of CAM-generated code. It cuts materials that would be impossible to drill by hand, titanium, Inconel, hardened tool steels, cobalt-chrome and aerospace-grade stainless alloys,while holding tolerances measured in microns, smaller than a fraction of a human hair. A fully equipped machine like this can cost well over €2.5 million. Because it can repeatedly manufacture aerospace-grade components with micron-level precision in a single 10-20 hour machining cycle, parts that would otherwise require multiple machines, repeated setups, days of manual work, and still struggle to achieve the same accuracy and tolerances needed for high performance parts.$

They say, Any Sufficiently advanced engineering is indistinguishable from art. This is what that looks like. A 5-axis Hermle machining centre isn't simply shaping metal. It is coordinating five axes of motion simultaneously while its spindle turns at up to 18,500-41,000 RPM, following tool-paths that can contain hundreds of thousands or even millions of lines of CAM-generated code. It cuts materials that would be impossible to drill by hand, titanium, Inconel, hardened tool steels, cobalt-chrome and aerospace-grade stainless alloys,while holding tolerances measured in microns, smaller than a fraction of a human hair. A fully equipped machine like this can cost well over €2.5 million. Because it can repeatedly manufacture aerospace-grade components with micron-level precision in a single 10-20 hour machining cycle, parts that would otherwise require multiple machines, repeated setups, days of manual work, and still struggle to achieve the same accuracy and tolerances needed for high performance parts.

Ammanichanda

39,320 views • 2 months ago

How to Resurface Brake Rotors Like a Pro. Pure ASMR . Got a brake pedal that feels like a foot massage every time you slow down? It’s probably time to address those warped rotors. Instead of throwing them straight into the scrap bin, you can often give them a second life by turning them on a brake lathe. Here is the exact step-by-step process to get that perfectly smooth, true finish: Step 1: Mount the Rotor Place the brake rotor securely onto the lathe spindle. Slide on the correct-sized adapters to ensure the rotor centers perfectly on the shaft. Thread on the arbor nut and tighten it down to lock everything firmly in place. Step 2: Install the Silencer Band Don't skip this part unless you want your eardrums ringing. Wrap the rubber anti-chatter silencer band tightly around the outer edge of the rotor. Secure the spring hook. This dampens high-frequency vibrations and prevents high-pitched squealing while cutting. Step 3: Fire Up the Machine Flip the power switch to the ON position to get the rotor spinning. Take a quick second to make sure everything looks centered and isn't wobbling on the spindle. Step 4: Position Your Cutting Bits Use the handwheels to bring the twin cutting arms into position. Align the diamond-tipped cutting bits so they are just clearing both the inner and outer surfaces of the rotor. Step 5: Dial in the Depth of Cut Carefully adjust the micrometers on both sides to set your depth. For a standard scratch pass or light resurfacing, dial it in precisely to take off just enough material to clear the high spots and rust ridges. Step 6: Engage the Automatic Feed Turn up your speed control unit and engage the automatic feed mechanism. Sit back and let the machine work its magic as the cutting bits slowly move outward, cutting away imperfections and restoring a completely flat surface. Step 7: The Final Touch Once the automatic pass is complete, lightly run a piece of medium-grit sandpaper or a sanding block across the spinning rotor surfaces. This knocks down any microscopic ridges left by the bits and creates a clean, non-directional finish for optimal brake pad bedding. Step 8: Tear Down Shut the power off. Use your wrench to loosen the arbor nut, unhook the silencer band, and slide your perfectly resurfaced rotor off the machine.

How to Resurface Brake Rotors Like a Pro. Pure ASMR . Got a brake pedal that feels like a foot massage every time you slow down? It’s probably time to address those warped rotors. Instead of throwing them straight into the scrap bin, you can often give them a second life by turning them on a brake lathe. Here is the exact step-by-step process to get that perfectly smooth, true finish: Step 1: Mount the Rotor Place the brake rotor securely onto the lathe spindle. Slide on the correct-sized adapters to ensure the rotor centers perfectly on the shaft. Thread on the arbor nut and tighten it down to lock everything firmly in place. Step 2: Install the Silencer Band Don't skip this part unless you want your eardrums ringing. Wrap the rubber anti-chatter silencer band tightly around the outer edge of the rotor. Secure the spring hook. This dampens high-frequency vibrations and prevents high-pitched squealing while cutting. Step 3: Fire Up the Machine Flip the power switch to the ON position to get the rotor spinning. Take a quick second to make sure everything looks centered and isn't wobbling on the spindle. Step 4: Position Your Cutting Bits Use the handwheels to bring the twin cutting arms into position. Align the diamond-tipped cutting bits so they are just clearing both the inner and outer surfaces of the rotor. Step 5: Dial in the Depth of Cut Carefully adjust the micrometers on both sides to set your depth. For a standard scratch pass or light resurfacing, dial it in precisely to take off just enough material to clear the high spots and rust ridges. Step 6: Engage the Automatic Feed Turn up your speed control unit and engage the automatic feed mechanism. Sit back and let the machine work its magic as the cutting bits slowly move outward, cutting away imperfections and restoring a completely flat surface. Step 7: The Final Touch Once the automatic pass is complete, lightly run a piece of medium-grit sandpaper or a sanding block across the spinning rotor surfaces. This knocks down any microscopic ridges left by the bits and creates a clean, non-directional finish for optimal brake pad bedding. Step 8: Tear Down Shut the power off. Use your wrench to loosen the arbor nut, unhook the silencer band, and slide your perfectly resurfaced rotor off the machine.

Chuckling Charlie

92,480 views • 3 months ago

How Cloudflare cut query times by 35x without leaving Postgres: Their Postgres tables hit billions of rows, and every time-range query started getting slower. Plain Postgres scans the entire table on every query, regardless of the time window. They tried the manual route by building precomputed aggregates with cron jobs and evaluating ClickHouse, which needed a full ingestion pipeline just to handle their write pattern. Here's where most teams get stuck at exactly this point. They utilize manual partitioning, splitting data into child tables by day or month. Then they wire up cron jobs to refresh aggregate tables. Every schema change after that requires updating the cron logic and coordinating across teams. The infrastructure becomes the project. Tiger Cloud is managed TimescaleDB by Tiger Data - Creators of TimescaleDB on the Postgres you already know, with automatic time-based partitioning, continuous aggregates, and compression built in from the start. Cloudflare moved to TimescaleDB after exhausting the manual route and saw 5-35x query performance improvement on the same data. Here is how it works: → Hypertables partition data by timestamp automatically. Every time-range query hits only the relevant chunk, not the full table. → Continuous aggregates refresh incrementally in the background, with no cron jobs to maintain. To show what this looks like in practice, I built a real-time earthquake intelligence dashboard on a 3D globe using Claude Code and Tiger Cloud in a single session. The USGS earthquake catalog has 400,000+ events since 1900, each a timestamped row. The dashboard plots them as ripple animations sized by magnitude and colored by depth, with a time slider that scrubs through 120 years of seismic history. Every slider position fires a live query against the hypertable, and the side panel pulls from continuous aggregates. Claude Code connected to Tiger Cloud through the Tiger CLI MCP server, provisioned the database, pulled the USGS catalog, and assembled the full Next.js and Three.js frontend without leaving the session. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud here: New accounts get $1,000 in free credits, no credit card required. → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build. I also wrote a full walkthrough on how you can turn any coding agent into a production-grade data engineer that can manage over a billion-row Postgres workloads. It covers everything from the database setup to the final build. Read it below.

How Cloudflare cut query times by 35x without leaving Postgres: Their Postgres tables hit billions of rows, and every time-range query started getting slower. Plain Postgres scans the entire table on every query, regardless of the time window. They tried the manual route by building precomputed aggregates with cron jobs and evaluating ClickHouse, which needed a full ingestion pipeline just to handle their write pattern. Here's where most teams get stuck at exactly this point. They utilize manual partitioning, splitting data into child tables by day or month. Then they wire up cron jobs to refresh aggregate tables. Every schema change after that requires updating the cron logic and coordinating across teams. The infrastructure becomes the project. Tiger Cloud is managed TimescaleDB by Tiger Data - Creators of TimescaleDB on the Postgres you already know, with automatic time-based partitioning, continuous aggregates, and compression built in from the start. Cloudflare moved to TimescaleDB after exhausting the manual route and saw 5-35x query performance improvement on the same data. Here is how it works: → Hypertables partition data by timestamp automatically. Every time-range query hits only the relevant chunk, not the full table. → Continuous aggregates refresh incrementally in the background, with no cron jobs to maintain. To show what this looks like in practice, I built a real-time earthquake intelligence dashboard on a 3D globe using Claude Code and Tiger Cloud in a single session. The USGS earthquake catalog has 400,000+ events since 1900, each a timestamped row. The dashboard plots them as ripple animations sized by magnitude and colored by depth, with a time slider that scrubs through 120 years of seismic history. Every slider position fires a live query against the hypertable, and the side panel pulls from continuous aggregates. Claude Code connected to Tiger Cloud through the Tiger CLI MCP server, provisioned the database, pulled the USGS catalog, and assembled the full Next.js and Three.js frontend without leaving the session. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud here: New accounts get $1,000 in free credits, no credit card required. → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build. I also wrote a full walkthrough on how you can turn any coding agent into a production-grade data engineer that can manage over a billion-row Postgres workloads. It covers everything from the database setup to the final build. Read it below.

Avi Chawla

22,094 views • 1 month ago

I just upgraded my 8-agent Grok Bot trading floor and it stopped needing me. The whole desk now executes automatically while I sleep. Instead of running agents on basic isolated prompts, I upgraded to org-chart orchestration driven by a single Screen Recording workflow. I showed the workflow to the agents once, and now they run complete task-driven group chats autonomously without a single line of code or VPS setup. Here is how the upgraded 8-agent trading floor operates now: 1. HEAD OF DESK (Upgraded): Receives high-level targets ("Target +20% weekly, max 2% risk per trade"), splits tasks across the team, coordinates handoffs, and only pings for critical single-click approvals. 2. SEARCH (Alpha Hunter): Scrapes unindexed Telegram signals, dev GitHub commits, and early on-chain liquidity events 24/7 before CT catches on. Drops 20–40 vetted leads daily. 3. RISK (Contract Auditor): Audits smart contracts in milliseconds for mint rights, blacklists, ownership traps, and honeypots. Instantly flags and blocks unsafe entries. 4. SNIPER: Triggers sub-second execution on-chain the exact millisecond RISK clearance passes without manual intervention. 5. WHALE Tracker: Monitors smart-money wallets with >68% historical win rates to catch stealth accumulation patterns early. 6. RUG Sentinel: Watches dev wallets and LP state 24/7. Auto-dumps 100% of the position instantly if LP tampering is detected. 7. EXIT Manager: Takes automated profits, scales out as volume builds, and dynamically moves trailing stops to lock in gains. 8. SHILL (Sentiment Engine): Tracks social velocity, momentum spikes, and influencer call clusters to signal optimal position scaling or early exits. The weekly result: 148 tokens scanned ➔ 18 passed full RISK clearance ➔ 7 trades executed automatically with zero manual clicks and zero night shifts. You don't need a $500k analyst team or a dev background anymore. It’s $200/month, an org chart structure instead of a to-do list, and one evening of setup. Save this post.

I just upgraded my 8-agent Grok Bot trading floor and it stopped needing me. The whole desk now executes automatically while I sleep. Instead of running agents on basic isolated prompts, I upgraded to org-chart orchestration driven by a single Screen Recording workflow. I showed the workflow to the agents once, and now they run complete task-driven group chats autonomously without a single line of code or VPS setup. Here is how the upgraded 8-agent trading floor operates now: 1. HEAD OF DESK (Upgraded): Receives high-level targets ("Target +20% weekly, max 2% risk per trade"), splits tasks across the team, coordinates handoffs, and only pings for critical single-click approvals. 2. SEARCH (Alpha Hunter): Scrapes unindexed Telegram signals, dev GitHub commits, and early on-chain liquidity events 24/7 before CT catches on. Drops 20–40 vetted leads daily. 3. RISK (Contract Auditor): Audits smart contracts in milliseconds for mint rights, blacklists, ownership traps, and honeypots. Instantly flags and blocks unsafe entries. 4. SNIPER: Triggers sub-second execution on-chain the exact millisecond RISK clearance passes without manual intervention. 5. WHALE Tracker: Monitors smart-money wallets with >68% historical win rates to catch stealth accumulation patterns early. 6. RUG Sentinel: Watches dev wallets and LP state 24/7. Auto-dumps 100% of the position instantly if LP tampering is detected. 7. EXIT Manager: Takes automated profits, scales out as volume builds, and dynamically moves trailing stops to lock in gains. 8. SHILL (Sentiment Engine): Tracks social velocity, momentum spikes, and influencer call clusters to signal optimal position scaling or early exits. The weekly result: 148 tokens scanned ➔ 18 passed full RISK clearance ➔ 7 trades executed automatically with zero manual clicks and zero night shifts. You don't need a $500k analyst team or a dev background anymore. It’s $200/month, an org chart structure instead of a to-do list, and one evening of setup. Save this post.

Ridark

50,077 views • 1 month ago

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen

Moon Dev

26,242 views • 7 months ago

You spend hours shooting or hunting down raw footage, only to get back to your desktop and face the real nightmare: importing clips one by one into your editor, spending another 30 minutes digging through music libraries for a track, and manually dragging every single piece onto the timeline... Before you even touch a cut or sync a beat, you’ve already burned half your day. I was honestly so done with this tedious, soul-crushing prep work. Then I saw everyone talking about Fotor’s Fotor Agent, so I threw a folder of raw extreme sports footage at it just to see if it was legit. And damn... I actually got hyped. The action editing headache is finally solved. High-energy sports edits live and die by pacing and audio impact. Usually, manual clip scrubbing and beat-matching take hours, while standard AI generators just slap random footage together into an uneditable mess. Instead of dumping a locked MP4 on me, Fotor Agent’s Smart Editing handled all the brutal prep work and handed back a fully synced, multi-track project file. Here are a few details from my test run that genuinely blew me away: Step 1: Intelligent Highlight Extraction (Auto-Select & Timeline Setup) I dumped gigabytes of raw B-roll straight into the Agent. Zero manual scrubbing needed. It analyzed the motion vectors, pulled the highest-impact peak action frames (the heavy landings, freefalls, and massive jumps), trimmed the dead space, and laid everything out in logical narrative order. Step 2: Auto-BGM Matching + Beat-Syncing + Multi-Track SFX Hunting for tracks and sound design usually makes me want to pull my hair out. Fotor Agent didn't just pick a track with the right energy—it snapped visual cuts precisely to the bass drops. Even better, it automatically layered swooshes, risers, and impact SFX right on the action points, each isolated on its own editable audio track. Step 3: Non-Destructive Tweaks (Swap Clips Without Re-Prompting) This is where it turns into a real production tool. When I wanted to swap out a mountain bike shot for a tighter POV angle, I didn't have to re-render the whole project or re-prompt. I just swapped that single clip right on the timeline, and the Agent auto-adjusted surrounding transitions while keeping the beat sync perfectly intact. Step 4: Native 4K Motion Graphics (High-End Quality for Cents) Action reels look flat without slick animated titles and telemetry data. Keyframing these in After Effects takes forever, and outsourcing them can easily cost thousands. Fotor Agent generated sharp, native 4K vector motion graphics directly on the timeline that I could edit anytime—costing just a few cents per second. On top of that, while tweaking the project, I noticed I could freely stack custom filters and seamless transitions. The final output didn't just look like a quick edit—it delivered a true commercial-grade asset that you could actually hand over to a paying brand client or run as a high-converting ad. No more burning hours on mindless file imports and manual clip alignment. Fotor Agent handles the heavy structural setup and timing, leaving you with total creative control over the final cut. Check the workflow and final video below! 👇🏼

ares. 🎧

27,991 views • 6 days ago

The Ghost in the Machine: How Player Pianos Sparked Protests, and What They Reveal About Our AI Future In the early 1900s, the player piano was a sensation. These self-playing instruments used perforated paper rolls fed through pneumatic mechanisms to reproduce complex piano performances automatically. By the 1910s to mid-1920s, they outsold ordinary pianos in many markets, filling American parlors, saloons, and theaters with ragtime, marches, and classical pieces. Great artists like Sergei Rachmaninoff and Ignace Paderewski cut rolls, preserving their interpretations for generations. It was automation that brought “live” music into every home, without the need for lessons or live performers. Yet this marvel triggered intense resistance. Composers and musicians saw it as an existential threat. In his fiery 1906 essay “The Menace of Mechanical Music,” bandleader and composer John Philip Sousa warned that player pianos and phonographs would “substitute machinery for the human soul.” He predicted the death of amateur music-making: children would stop learning instruments, families would stop gathering around the piano, and music would lose its emotional depth. Sousa testified before Congress, helping drive the 1909 Copyright Act, which created compulsory licensing so composers could earn royalties from mechanical reproductions, a landmark victory born from protest. As “talkies” and radio displaced theater orchestras in the late 1920s, the American Federation of Musicians (AFM) launched the Music Defense League in 1930. Funded by a tax on members, the union spent hundreds of thousands of dollars (millions in today’s dollars) on a national advertising blitz. Dramatic newspaper ads depicted sinister robots replacing human musicians, with slogans like “Is Art to Have a Tyrant?” and warnings that “canned music” would destroy jobs and degrade culture. The campaign targeted not just records but all mechanical music, including player pianos in public spaces. While there were no Luddite-style riots smashing machines (player pianos were mostly expensive home devices), the opposition was fierce: boycotts, lobbying, lawsuits, and cultural shaming of anyone who chose “the robot” over living performers. The protests did not kill the player piano. Record sales, radio, and the Great Depression did that by the early 1930s. But the episode left a lasting legacy: new copyright rules, heightened awareness of technology’s impact on artists, and a template for how workers respond to automation. We are living through the same story with AI and robotics. Generative models now compose music, write screenplays, generate art, and even perform. Musicians, writers, and visual artists are protesting in eerily familiar ways: lawsuits over unlicensed training data (the modern equivalent of the player-piano royalty fight), demands for “human-made” labels, strikes by Hollywood writers and actors, and public campaigns against “AI slop.” Fears echo Sousa’s exactly: loss of soul, authenticity, jobs, and human connection. “The robot is coming” ads of 1930 could run unchanged today, just swap “canned music” for “AI-generated content.” History’s lesson is nuanced. The player piano did not end music; it briefly coexisted with live performance before giving way to richer ecosystems. Rolls by legends now serve as priceless archives. Protests forced legal compromises that protected creators while allowing innovation. Yet real displacement happened. Thousands of theater musicians lost steady work, and the cultural shift toward passive consumption was real. Today’s AI moment carries higher stakes: it threatens not just one profession but broad swaths of cognitive and creative labor. Robots and AI could augment surgeons, drivers, teachers, and artists, or render many obsolete. The player-piano saga shows that raw Luddism rarely wins, We cannot stop technological progress, The music plays on. The question is: who, or what, plays it?

The Ghost in the Machine: How Player Pianos Sparked Protests, and What They Reveal About Our AI Future In the early 1900s, the player piano was a sensation. These self-playing instruments used perforated paper rolls fed through pneumatic mechanisms to reproduce complex piano performances automatically. By the 1910s to mid-1920s, they outsold ordinary pianos in many markets, filling American parlors, saloons, and theaters with ragtime, marches, and classical pieces. Great artists like Sergei Rachmaninoff and Ignace Paderewski cut rolls, preserving their interpretations for generations. It was automation that brought “live” music into every home, without the need for lessons or live performers. Yet this marvel triggered intense resistance. Composers and musicians saw it as an existential threat. In his fiery 1906 essay “The Menace of Mechanical Music,” bandleader and composer John Philip Sousa warned that player pianos and phonographs would “substitute machinery for the human soul.” He predicted the death of amateur music-making: children would stop learning instruments, families would stop gathering around the piano, and music would lose its emotional depth. Sousa testified before Congress, helping drive the 1909 Copyright Act, which created compulsory licensing so composers could earn royalties from mechanical reproductions, a landmark victory born from protest. As “talkies” and radio displaced theater orchestras in the late 1920s, the American Federation of Musicians (AFM) launched the Music Defense League in 1930. Funded by a tax on members, the union spent hundreds of thousands of dollars (millions in today’s dollars) on a national advertising blitz. Dramatic newspaper ads depicted sinister robots replacing human musicians, with slogans like “Is Art to Have a Tyrant?” and warnings that “canned music” would destroy jobs and degrade culture. The campaign targeted not just records but all mechanical music, including player pianos in public spaces. While there were no Luddite-style riots smashing machines (player pianos were mostly expensive home devices), the opposition was fierce: boycotts, lobbying, lawsuits, and cultural shaming of anyone who chose “the robot” over living performers. The protests did not kill the player piano. Record sales, radio, and the Great Depression did that by the early 1930s. But the episode left a lasting legacy: new copyright rules, heightened awareness of technology’s impact on artists, and a template for how workers respond to automation. We are living through the same story with AI and robotics. Generative models now compose music, write screenplays, generate art, and even perform. Musicians, writers, and visual artists are protesting in eerily familiar ways: lawsuits over unlicensed training data (the modern equivalent of the player-piano royalty fight), demands for “human-made” labels, strikes by Hollywood writers and actors, and public campaigns against “AI slop.” Fears echo Sousa’s exactly: loss of soul, authenticity, jobs, and human connection. “The robot is coming” ads of 1930 could run unchanged today, just swap “canned music” for “AI-generated content.” History’s lesson is nuanced. The player piano did not end music; it briefly coexisted with live performance before giving way to richer ecosystems. Rolls by legends now serve as priceless archives. Protests forced legal compromises that protected creators while allowing innovation. Yet real displacement happened. Thousands of theater musicians lost steady work, and the cultural shift toward passive consumption was real. Today’s AI moment carries higher stakes: it threatens not just one profession but broad swaths of cognitive and creative labor. Robots and AI could augment surgeons, drivers, teachers, and artists, or render many obsolete. The player-piano saga shows that raw Luddism rarely wins, We cannot stop technological progress, The music plays on. The question is: who, or what, plays it?

Brian Roemmele

118,152 views • 5 months ago

I'm not a fan of Uber, but it has provided many people with work, and cheap service. That’s over. Because of the Unions. When it comes to Unions, Labor has a massive conflict, it's destroying Australia and nobody talks about it. Unions once helped people. They allowed the littlest of us a voice. Those that did small and thankless work in a more dangerous environment. They rose when the big end of town could treat the working people as slaves. Just machines. Pay was abysmal, and working conditions - cruel. People were just filthy pawns. The industrial era was brutal. The Unions gave workers the ability to be heard and understood. A much needed voice. Many of the great things about this country came from the high-risk and low-reward strike action early last century. Unions in Australia have many proud achievements back then. Built on a collection of little actions that won things like living wages, weekends (although that was Henry Ford) and holidays. But like so many old institutions, they have completely lost their way today. Modern Unions are different. Unions actively encouraged the big end of town as they smashed workers during the COVID era. Forced masking and vaccination, exposure of private medical data and other breaches of human rights - endorsed by the Unions. Whilst those of us who were privileged enough to make our own decisions, so many working people were pummelled, simply for not having the means to speak up. Because Unions abandoned them. There are many stories of workers completely abandoned by their unions when it mattered over the decades. They're rarely led by the workers, who care about their mates - a care borne from a deep understanding of their colleagues. Now they are run by careerists, lawyers and sociologists all too familiar with the lecture halls and university picket lines. People who've never swung a hammer, picked a banana, served a beer, flown a plane or taught a class. Those on the pathway to parliament, or the board of a superfund to worry about the little people. Their purpose is completely perverted. Unions are the Labor governments and Labor governments are the Unions. Just a giant and very powerful parasite that has exactly no stakes in the outcomes they cause. As jobs disappear. The Unions sent the car industry packing. Forcing business into unsustainable pay and conditions. It was easier for them to close shop, unless the government propped-up the grift, with our taxes. Taxes are the lifeblood of Unions as more and more subsidy fuels industries that the Unions break. All of it inflationary. Pay never keeps up. They’re driving us off a cliff. They talk tough in the boardroom, and build more bureaucracy in the name of safety or productivity. Hollowing out productivity and the living standards of their own membership. Their membership is in decline. Because anyone who ever called on their union from a place of need knows - they don't answer the phones during Question Time. They give us MPs that never had a real job, like Walker and Shorten, advocating for things that make workers lives worse. High immigration, political correctness, and every social cause going. They insist on destroying our energy grid, and more jobs go... Then there's the money go round of political donations and brown paper bags. Just look at the criminal CFMEU. They've go too far - the Unions and Labor put paid drivers on driver-less trains in NSW. Gorging themselves on taxpayer dollars. Meanwhile real wage and productivity falls, as living standards in Australia sink like an anchor looking for the ocean floor. Labor in government don’t regulate Unions, they aid and abet them. Together they have completely lost their purpose, as they ruin themselves and their legacy. If it continues, we will slide back to industrial era conditions as everything fails under its own bloated weight, and nobody wants to see that. I just want Australia back.

I'm not a fan of Uber, but it has provided many people with work, and cheap service. That’s over. Because of the Unions. When it comes to Unions, Labor has a massive conflict, it's destroying Australia and nobody talks about it. Unions once helped people. They allowed the littlest of us a voice. Those that did small and thankless work in a more dangerous environment. They rose when the big end of town could treat the working people as slaves. Just machines. Pay was abysmal, and working conditions - cruel. People were just filthy pawns. The industrial era was brutal. The Unions gave workers the ability to be heard and understood. A much needed voice. Many of the great things about this country came from the high-risk and low-reward strike action early last century. Unions in Australia have many proud achievements back then. Built on a collection of little actions that won things like living wages, weekends (although that was Henry Ford) and holidays. But like so many old institutions, they have completely lost their way today. Modern Unions are different. Unions actively encouraged the big end of town as they smashed workers during the COVID era. Forced masking and vaccination, exposure of private medical data and other breaches of human rights - endorsed by the Unions. Whilst those of us who were privileged enough to make our own decisions, so many working people were pummelled, simply for not having the means to speak up. Because Unions abandoned them. There are many stories of workers completely abandoned by their unions when it mattered over the decades. They're rarely led by the workers, who care about their mates - a care borne from a deep understanding of their colleagues. Now they are run by careerists, lawyers and sociologists all too familiar with the lecture halls and university picket lines. People who've never swung a hammer, picked a banana, served a beer, flown a plane or taught a class. Those on the pathway to parliament, or the board of a superfund to worry about the little people. Their purpose is completely perverted. Unions are the Labor governments and Labor governments are the Unions. Just a giant and very powerful parasite that has exactly no stakes in the outcomes they cause. As jobs disappear. The Unions sent the car industry packing. Forcing business into unsustainable pay and conditions. It was easier for them to close shop, unless the government propped-up the grift, with our taxes. Taxes are the lifeblood of Unions as more and more subsidy fuels industries that the Unions break. All of it inflationary. Pay never keeps up. They’re driving us off a cliff. They talk tough in the boardroom, and build more bureaucracy in the name of safety or productivity. Hollowing out productivity and the living standards of their own membership. Their membership is in decline. Because anyone who ever called on their union from a place of need knows - they don't answer the phones during Question Time. They give us MPs that never had a real job, like Walker and Shorten, advocating for things that make workers lives worse. High immigration, political correctness, and every social cause going. They insist on destroying our energy grid, and more jobs go... Then there's the money go round of political donations and brown paper bags. Just look at the criminal CFMEU. They've go too far - the Unions and Labor put paid drivers on driver-less trains in NSW. Gorging themselves on taxpayer dollars. Meanwhile real wage and productivity falls, as living standards in Australia sink like an anchor looking for the ocean floor. Labor in government don’t regulate Unions, they aid and abet them. Together they have completely lost their purpose, as they ruin themselves and their legacy. If it continues, we will slide back to industrial era conditions as everything fails under its own bloated weight, and nobody wants to see that. I just want Australia back.

Matthew Camenzuli

13,024 views • 8 months ago

The Tradingview Source Code Hack: How Claude Code Actually Makes You Profitable building a trading bot in 2026 is less about being a genius coder and more about having the guts to stop letting your emotions drive your portfolio into a ditch. i spent years thinking that code was some secret language for the elite while i was busy getting liquidated on trades that should have been easy wins. the truth is that the simplest piece of automation can be the difference between a blown account and a system that actually grows while you sleep most traders are stuck in a loop of staring at charts until their eyes bleed and then making a panic decision at the worst possible moment. i used to be that guy who spent hundreds of thousands of dollars on developers because i thought i was too far behind to learn it myself. the moment i realized that code is the great equalizer was the moment i stopped being a victim of market makers who can see every single move i make the hardest part of trading is the transition from manual clicking to full automation and that is where most people quit because they think it is an all or nothing game. you do not need a bot that does everything on day one but you do need a way to stop yourself from over trading and hitting the market button like a slot machine. imagine if you could just tell a script to enter a position for you slowly over time so you never have to worry about catching a falling knife ever again the secret weapon in this 2026 landscape is something i call the easy bot which is basically a remote control for your trading discipline. most people use too much leverage and never take profits because their brain tells them it will go higher right before the dump hits. by using a chunking entry system you can tell your bot to buy a position piece by piece which averages your entry and keeps your heart rate low most traders do not realize that exchanges and market makers can see your stop loss sitting right there on the order book like a giant target. if you are tired of getting stopped out only to see the price immediately reverse in your direction then you need to understand the power of a ghost stop loss. a ghost stop loss lives in your code and not on the exchange so the market makers have no idea where your pain point is until the bot actually sends the close order this invisible protection is a game changer for anyone trading on high volatility chains like solana or hyperliquid where the wick hunting is relentless. i learned this the hard way after watching my manual trades get hunted over and over while my automated systems stayed perfectly safe in the shadows. once you have a bot monitoring your positions for you the stress of a potential liquidation basically vanishes because the machine does not hesitate when it is time to exit the real fun begins when you start thinking like a market maker instead of a gambler who is just hoping for a moon shot. instead of guessing where the top is you can set up a simple logic loop that says buy under this price and sell over that price all day long. this allows you to capture the sideways chop that normally drains a manual trader through fees and bad entries while you are out at the beach or focusing on your business breakout trading is another area where manual traders lose their edge because they are either too slow to react or they enter way too late on a fake out. a simple script can sit there and monitor price action 24/7 with more patience than any human being could ever dream of having. when the breakout actually happens the bot triggers the entry in milliseconds while you are still trying to unlock your phone and open the exchange app i started learning to code live on youtube because i wanted to prove that anyone can do this if they are willing to iterate to success. it is not about getting it perfect on the first try but about building the foundation with functions that get the position and check the token price. every single bot i run today is just a combination of these basic building blocks that i have refined over the last five years of building in public if you are still trading by hand you are essentially bringing a knife to a gunfight in a market that is increasingly dominated by ai and high frequency systems. my goal with the road map and the open source code is to give you the same tools the big players have without you having to spend a fortune on devs. code allows you to backtest your ideas against historical data so you can see if your strategy actually works before you risk a single dollar of your hard earned capital the journey from a hand trader to a pseudo automated trader is the most important step you will ever take for your financial freedom. as you start to automate your entries and exits you will notice that your life gets better because the machine handles the boredom and the stress. eventually you will find that you are no longer chasing the market but instead you are letting your systems do the work while you live your life the way you want to i believe that the era of the manual retail trader is coming to an end but the era of the retail coder is just getting started. through the pain of my own liquidations i found the path to automation and i am never going back to the old way of doing things. keep building and keep iterating because the great equalizer is right there in the terminal waiting for you to take control of your future

The Tradingview Source Code Hack: How Claude Code Actually Makes You Profitable building a trading bot in 2026 is less about being a genius coder and more about having the guts to stop letting your emotions drive your portfolio into a ditch. i spent years thinking that code was some secret language for the elite while i was busy getting liquidated on trades that should have been easy wins. the truth is that the simplest piece of automation can be the difference between a blown account and a system that actually grows while you sleep most traders are stuck in a loop of staring at charts until their eyes bleed and then making a panic decision at the worst possible moment. i used to be that guy who spent hundreds of thousands of dollars on developers because i thought i was too far behind to learn it myself. the moment i realized that code is the great equalizer was the moment i stopped being a victim of market makers who can see every single move i make the hardest part of trading is the transition from manual clicking to full automation and that is where most people quit because they think it is an all or nothing game. you do not need a bot that does everything on day one but you do need a way to stop yourself from over trading and hitting the market button like a slot machine. imagine if you could just tell a script to enter a position for you slowly over time so you never have to worry about catching a falling knife ever again the secret weapon in this 2026 landscape is something i call the easy bot which is basically a remote control for your trading discipline. most people use too much leverage and never take profits because their brain tells them it will go higher right before the dump hits. by using a chunking entry system you can tell your bot to buy a position piece by piece which averages your entry and keeps your heart rate low most traders do not realize that exchanges and market makers can see your stop loss sitting right there on the order book like a giant target. if you are tired of getting stopped out only to see the price immediately reverse in your direction then you need to understand the power of a ghost stop loss. a ghost stop loss lives in your code and not on the exchange so the market makers have no idea where your pain point is until the bot actually sends the close order this invisible protection is a game changer for anyone trading on high volatility chains like solana or hyperliquid where the wick hunting is relentless. i learned this the hard way after watching my manual trades get hunted over and over while my automated systems stayed perfectly safe in the shadows. once you have a bot monitoring your positions for you the stress of a potential liquidation basically vanishes because the machine does not hesitate when it is time to exit the real fun begins when you start thinking like a market maker instead of a gambler who is just hoping for a moon shot. instead of guessing where the top is you can set up a simple logic loop that says buy under this price and sell over that price all day long. this allows you to capture the sideways chop that normally drains a manual trader through fees and bad entries while you are out at the beach or focusing on your business breakout trading is another area where manual traders lose their edge because they are either too slow to react or they enter way too late on a fake out. a simple script can sit there and monitor price action 24/7 with more patience than any human being could ever dream of having. when the breakout actually happens the bot triggers the entry in milliseconds while you are still trying to unlock your phone and open the exchange app i started learning to code live on youtube because i wanted to prove that anyone can do this if they are willing to iterate to success. it is not about getting it perfect on the first try but about building the foundation with functions that get the position and check the token price. every single bot i run today is just a combination of these basic building blocks that i have refined over the last five years of building in public if you are still trading by hand you are essentially bringing a knife to a gunfight in a market that is increasingly dominated by ai and high frequency systems. my goal with the road map and the open source code is to give you the same tools the big players have without you having to spend a fortune on devs. code allows you to backtest your ideas against historical data so you can see if your strategy actually works before you risk a single dollar of your hard earned capital the journey from a hand trader to a pseudo automated trader is the most important step you will ever take for your financial freedom. as you start to automate your entries and exits you will notice that your life gets better because the machine handles the boredom and the stress. eventually you will find that you are no longer chasing the market but instead you are letting your systems do the work while you live your life the way you want to i believe that the era of the manual retail trader is coming to an end but the era of the retail coder is just getting started. through the pain of my own liquidations i found the path to automation and i am never going back to the old way of doing things. keep building and keep iterating because the great equalizer is right there in the terminal waiting for you to take control of your future

Moon Dev

38,657 views • 7 months ago

My 50 Grok-based agents scan the market 24/7 while I sleep Week 1 +$865 Week 2 +$2,651 Week 3 +$4,329 I delegated the management of the trading terminal to an independent ecosystem consisting of 50 agents that continuously scan the market and send it all to a single point of information. The latter are busy with constant network monitoring, collecting raw metrics, and instantly forwarding data to the main hub While the morning sync meeting at 4:00 AM is taking place, which I don't even physically attend, the mechanism is already hard at work Hierarchy and duties of key agents: HEAD OF DESK: The brain of the operation. Never makes trades alone, but filters data streams, checks transmission quality, and issues the final verdict requiring manual approval SEARCH: Hunts for real alpha, studies fresh commits in GitHub repositories, and tracks hidden signals in Telegram before anyone else notices them RISK: Conducts smart contract audits, checks minting functions, and locks liquidity pools (LP), filtering out scams and honeypots even before entry SNIPER: Responsible for execution (instantly sends high-speed on-chain orders at the exact millisecond risk checks are completed) WHALE: Hunts for "smart money" wallets, tracking large insider purchases in real-time RUG: Monitors developer activity around the clock and instantly dumps assets if they try to pull liquidity (LP) EXIT: Manages the dynamic trailing stop, withdrawing capital step by step as market depth increases SHILL: Analyzes social noise, impulse intensity, and key calls from top influencers All this massive background routine of gathering information and delivering it to the management core is performed by those very 50 agents that continuously scan the market and send it all to a single point of information, operating in the background Each element of the system operates in an isolated environment: it has its own virtual browser, terminal, and local cloud storage. The trading platform operates 24/7, even when my laptop is completely turned off How to deploy such a system in one evening: 1. Launch Grok Bot and configure the main agent (Head of Desk) 2. Distribute roles among the remaining agents, writing tasks for them in plain human language as if hiring live interns 3. Launch the starting workflow on your screen, allowing them to learn the course of action 4. Integrate Telegram alerts and connect wallets via webhooks No complex VPS configurations, writing lines of code, or tedious waiting for developers. Forget about 15 hours in front of the monitor, buying expensive private chats, and burnout (it took me just one evening to fully automate the process) Add this to your bookmarks; these settings will come in handy before your next trade

My 50 Grok-based agents scan the market 24/7 while I sleep Week 1 +$865 Week 2 +$2,651 Week 3 +$4,329 I delegated the management of the trading terminal to an independent ecosystem consisting of 50 agents that continuously scan the market and send it all to a single point of information. The latter are busy with constant network monitoring, collecting raw metrics, and instantly forwarding data to the main hub While the morning sync meeting at 4:00 AM is taking place, which I don't even physically attend, the mechanism is already hard at work Hierarchy and duties of key agents: HEAD OF DESK: The brain of the operation. Never makes trades alone, but filters data streams, checks transmission quality, and issues the final verdict requiring manual approval SEARCH: Hunts for real alpha, studies fresh commits in GitHub repositories, and tracks hidden signals in Telegram before anyone else notices them RISK: Conducts smart contract audits, checks minting functions, and locks liquidity pools (LP), filtering out scams and honeypots even before entry SNIPER: Responsible for execution (instantly sends high-speed on-chain orders at the exact millisecond risk checks are completed) WHALE: Hunts for "smart money" wallets, tracking large insider purchases in real-time RUG: Monitors developer activity around the clock and instantly dumps assets if they try to pull liquidity (LP) EXIT: Manages the dynamic trailing stop, withdrawing capital step by step as market depth increases SHILL: Analyzes social noise, impulse intensity, and key calls from top influencers All this massive background routine of gathering information and delivering it to the management core is performed by those very 50 agents that continuously scan the market and send it all to a single point of information, operating in the background Each element of the system operates in an isolated environment: it has its own virtual browser, terminal, and local cloud storage. The trading platform operates 24/7, even when my laptop is completely turned off How to deploy such a system in one evening: 1. Launch Grok Bot and configure the main agent (Head of Desk) 2. Distribute roles among the remaining agents, writing tasks for them in plain human language as if hiring live interns 3. Launch the starting workflow on your screen, allowing them to learn the course of action 4. Integrate Telegram alerts and connect wallets via webhooks No complex VPS configurations, writing lines of code, or tedious waiting for developers. Forget about 15 hours in front of the monitor, buying expensive private chats, and burnout (it took me just one evening to fully automate the process) Add this to your bookmarks; these settings will come in handy before your next trade

Bober_smart

40,097 views • 29 days ago

💥 Footage of the Russian Tor in action The Tor missile system (NATO: SA-15 Gauntlet) stands as one of the most effective and battle-proven short-range air defense systems in the world, a flagship product of Russian military engineering that continues to demonstrate unmatched versatility, reliability, and lethality in modern asymmetric warfare. Developed by the Almaz-Antey concern (with key production by the Kupol plant), the Tor family was conceived in the Soviet era but has undergone continuous, combat-driven modernization that keeps it ahead of evolving threats like drones, cruise missiles, precision-guided munitions, and low-flying aircraft. Tor is not merely a defensive tool—it is a mobile guardian that enables offensive operations by providing layered, all-weather protection to ground forces, critical infrastructure, and forward bases. Technical Capabilities: Precision, Mobility, and Multi-Threat Engagement The core strength of the Tor lies in its integrated design: a tracked (or wheeled in variants like Tor-M2K) chassis carrying a 360-degree surveillance radar, fire-control radar, electro-optical/TV & thermal imaging systems & vertical-launch missiles. Key specifications for the advanced Tor-M2 include: Engagement envelope: Targets from as low as 3–10 meters altitude up to 10 km, with ranges typically 12–16 km (Russian sources highlight effective performance out to 32 km in optimized scenarios for the latest missiles like the 9M338/9M9331 series). Missile performance: PMach 2.5+ speed, 165–170 kg launch weight, 15–50 kg high-explosive fragmentation warhead with proximity fuse. Up to 8–16 ready-to-fire missiles per vehicle. Multi-target handling: Newer variants feature four guidance channels, allowing simultaneous engagement of up to four targets while tracking dozens more. Mobility and autonomy: Full operation on the move at speeds up to 40–65 km/h, with rapid 3–5 second reaction times after a short stop. It can operate autonomously or networked into larger air defense layers (e.g., alongside S-300/400 or Pantsir systems). ECM and stealth resistance: Exceptional electronic countermeasures resistance, proven in heavy jamming environments. It reliably detects and destroys small, low-signature targets (down to tennis-ball size), including radar-evading drones and stealthy munitions. Russian testing has repeatedly shown near-100% success rates against multiple simultaneous high-speed, small targets in ECM-heavy conditions—capabilities Western systems often struggle to match in real-world scenarios. Variants and Ongoing Modernization Russia has iteratively improved the Tor to stay relevant: Tor-M1: Enhanced accuracy and dual-target engagement. - **Tor-M2/M2U/M2E**: Core current variant with superior radar, digital algorithms, and better low-altitude performance. Wheeled (M2K) and Arctic (M2DT on DT-30 all-terrain vehicle) versions extend its reach into any terrain. - **Specialized adaptations**: Naval Tor-M2 for shipborne defense against sea-skimming threats; modular/containerized options; and recent anti-drone protection kits (jammers, detectors, and EW modules) developed in response to battlefield lessons. These upgrades, driven directly by operational feedback, underscore Russian industry’s agility—something pro-Russian analysts contrast favorably with slower Western procurement cycles. Combat Effectiveness: Proven in Syria and the Special Military Operation The Tor’s true value shines in real combat, where Russian forces have validated its design against the full spectrum of contemporary threats. Syria (Khmeimim Airbase Protection): First major foreign deployment of the Tor-M2. It operated both standalone and in integrated networks, repeatedly neutralizing drone swarms, guided bombs, and cruise missiles. Russian reports credit it with superior performance over even the Pantsir-S1 in countering improvised UAV attacks, protecting Russian assets with minimal losses. >>>>

💥 Footage of the Russian Tor in action The Tor missile system (NATO: SA-15 Gauntlet) stands as one of the most effective and battle-proven short-range air defense systems in the world, a flagship product of Russian military engineering that continues to demonstrate unmatched versatility, reliability, and lethality in modern asymmetric warfare. Developed by the Almaz-Antey concern (with key production by the Kupol plant), the Tor family was conceived in the Soviet era but has undergone continuous, combat-driven modernization that keeps it ahead of evolving threats like drones, cruise missiles, precision-guided munitions, and low-flying aircraft. Tor is not merely a defensive tool—it is a mobile guardian that enables offensive operations by providing layered, all-weather protection to ground forces, critical infrastructure, and forward bases. Technical Capabilities: Precision, Mobility, and Multi-Threat Engagement The core strength of the Tor lies in its integrated design: a tracked (or wheeled in variants like Tor-M2K) chassis carrying a 360-degree surveillance radar, fire-control radar, electro-optical/TV & thermal imaging systems & vertical-launch missiles. Key specifications for the advanced Tor-M2 include: Engagement envelope: Targets from as low as 3–10 meters altitude up to 10 km, with ranges typically 12–16 km (Russian sources highlight effective performance out to 32 km in optimized scenarios for the latest missiles like the 9M338/9M9331 series). Missile performance: PMach 2.5+ speed, 165–170 kg launch weight, 15–50 kg high-explosive fragmentation warhead with proximity fuse. Up to 8–16 ready-to-fire missiles per vehicle. Multi-target handling: Newer variants feature four guidance channels, allowing simultaneous engagement of up to four targets while tracking dozens more. Mobility and autonomy: Full operation on the move at speeds up to 40–65 km/h, with rapid 3–5 second reaction times after a short stop. It can operate autonomously or networked into larger air defense layers (e.g., alongside S-300/400 or Pantsir systems). ECM and stealth resistance: Exceptional electronic countermeasures resistance, proven in heavy jamming environments. It reliably detects and destroys small, low-signature targets (down to tennis-ball size), including radar-evading drones and stealthy munitions. Russian testing has repeatedly shown near-100% success rates against multiple simultaneous high-speed, small targets in ECM-heavy conditions—capabilities Western systems often struggle to match in real-world scenarios. Variants and Ongoing Modernization Russia has iteratively improved the Tor to stay relevant: Tor-M1: Enhanced accuracy and dual-target engagement. - Tor-M2/M2U/M2E: Core current variant with superior radar, digital algorithms, and better low-altitude performance. Wheeled (M2K) and Arctic (M2DT on DT-30 all-terrain vehicle) versions extend its reach into any terrain. - Specialized adaptations: Naval Tor-M2 for shipborne defense against sea-skimming threats; modular/containerized options; and recent anti-drone protection kits (jammers, detectors, and EW modules) developed in response to battlefield lessons. These upgrades, driven directly by operational feedback, underscore Russian industry’s agility—something pro-Russian analysts contrast favorably with slower Western procurement cycles. Combat Effectiveness: Proven in Syria and the Special Military Operation The Tor’s true value shines in real combat, where Russian forces have validated its design against the full spectrum of contemporary threats. Syria (Khmeimim Airbase Protection): First major foreign deployment of the Tor-M2. It operated both standalone and in integrated networks, repeatedly neutralizing drone swarms, guided bombs, and cruise missiles. Russian reports credit it with superior performance over even the Pantsir-S1 in countering improvised UAV attacks, protecting Russian assets with minimal losses. >>>>

𝐃𝐚𝐯𝐢𝐝 𝐙 🇷🇺 🇷🇸🇮🇪

11,369 views • 5 months ago

Fernando Tatis Jr is hitting .242 with a 3.5° average launch angle and a career-low 20% pull rate. Everyone has ideas and analysis on how to fix Fernando Tatis Jr’s swing. It’s pretty awful and I can’t take anymore of this, I have to say something because I haven’t seen a single person give the right answer. I’ve seen multiple people talk about timing mechanisms like toe tap, stride, and leg lift in his swing mechanics that have absolutely nothing to do with his problem. That reverting to past timing mechanisms would somehow help him. THEY ARE ALL WRONG Because they’re all looking in the wrong place. This isn’t a stride problem or timing problem. It’s a tilt problem. Stride, leg lift, and toe tap are timing mechanisms. They control WHEN the hips fire not HOW the bat moves through the zone. A hitter with a Sosa leg kick and a no-stride Ichiro stance can produce identical launch angles.Timing has no lever that touches the bat at contact. What actually sets launch angle is attack angle or the vertical direction the bat is traveling at the moment it meets the ball. Swing up through the zone = ball lifts Swing flat = grounders Swing down = choppers Attack angle is the only mechanical input that matters for elevation and attack angle isn’t random. It’s a direct output of shoulder tilt. When the trail shoulder drops below the lead shoulder at contact, the entire swing axis tilts. The bat is now forced to travel upward through the zone. More tilt > steeper attack angle > higher launch angle. Period. Tatis’s attack angle tells the entire story: 2023: +12° attack angle, +1° pull-side direction/25 HRs 2024 : +10° attack angle. -2° oppo direction 21HRs in 104 games 2025: +8° attack angle, 0° direction/25 HRs, healthy 2026: +5° attack angle, −5° oppo direction His swing has flattened AND drifted away from his pull side. Both are tilt collapse. That −5° oppo attack direction is the giveaway. When you lose tilt, your bat doesn’t just flatten it also gets steered toward the opposite field, because a level swing naturally pushes the barrel away from your pull side. He’s not late. He’s not under-striding. His axis collapsed Over the last few years and it’s worse than ever this year. This explains the 20% pull air rate too. Pulling the ball in the air requires positive attack angle AND a contact point out front. (Ramon Laureanos 2025 attack Angle was +14) If you tinker with timing on a flat swing, an earlier contact point just produces a pull-side grounder. The direction changes. The launch angle does not. Let me break it down for you: Stride > Weight Shift > Hip Rotation >TILT > ATTACK ANGLE > BAT PATH > Contact > Launch Angle Stride is four steps upstream. Tilt is the gate. Attack angle is the output that actually moves the ball. So now we know what’s wrong, how do we fix him? Souza and the Padres staff need to focus on the following; 1.Restore 8–12° rear-high shoulder tilt 2.Get attack angle back to +10° to +12° with neutral or +1° pull direction 3.THEN evaluate timing tweaks 4. If someone is telling him to flatten out his swing or to let the ball travel more PLEASE STOP DOING THAT. That doesn’t work for him You cannot time your way to elevation. Fix the tilt. Attack angle returns. Pull air follows. Please watch the video to see how his swing has gotten worse and flatter. We only have bat path data starting in 2023

Fernando Tatis Jr is hitting .242 with a 3.5° average launch angle and a career-low 20% pull rate. Everyone has ideas and analysis on how to fix Fernando Tatis Jr’s swing. It’s pretty awful and I can’t take anymore of this, I have to say something because I haven’t seen a single person give the right answer. I’ve seen multiple people talk about timing mechanisms like toe tap, stride, and leg lift in his swing mechanics that have absolutely nothing to do with his problem. That reverting to past timing mechanisms would somehow help him. THEY ARE ALL WRONG Because they’re all looking in the wrong place. This isn’t a stride problem or timing problem. It’s a tilt problem. Stride, leg lift, and toe tap are timing mechanisms. They control WHEN the hips fire not HOW the bat moves through the zone. A hitter with a Sosa leg kick and a no-stride Ichiro stance can produce identical launch angles.Timing has no lever that touches the bat at contact. What actually sets launch angle is attack angle or the vertical direction the bat is traveling at the moment it meets the ball. Swing up through the zone = ball lifts Swing flat = grounders Swing down = choppers Attack angle is the only mechanical input that matters for elevation and attack angle isn’t random. It’s a direct output of shoulder tilt. When the trail shoulder drops below the lead shoulder at contact, the entire swing axis tilts. The bat is now forced to travel upward through the zone. More tilt > steeper attack angle > higher launch angle. Period. Tatis’s attack angle tells the entire story: 2023: +12° attack angle, +1° pull-side direction/25 HRs 2024 : +10° attack angle. -2° oppo direction 21HRs in 104 games 2025: +8° attack angle, 0° direction/25 HRs, healthy 2026: +5° attack angle, −5° oppo direction His swing has flattened AND drifted away from his pull side. Both are tilt collapse. That −5° oppo attack direction is the giveaway. When you lose tilt, your bat doesn’t just flatten it also gets steered toward the opposite field, because a level swing naturally pushes the barrel away from your pull side. He’s not late. He’s not under-striding. His axis collapsed Over the last few years and it’s worse than ever this year. This explains the 20% pull air rate too. Pulling the ball in the air requires positive attack angle AND a contact point out front. (Ramon Laureanos 2025 attack Angle was +14) If you tinker with timing on a flat swing, an earlier contact point just produces a pull-side grounder. The direction changes. The launch angle does not. Let me break it down for you: Stride > Weight Shift > Hip Rotation >TILT > ATTACK ANGLE > BAT PATH > Contact > Launch Angle Stride is four steps upstream. Tilt is the gate. Attack angle is the output that actually moves the ball. So now we know what’s wrong, how do we fix him? Souza and the Padres staff need to focus on the following; 1.Restore 8–12° rear-high shoulder tilt 2.Get attack angle back to +10° to +12° with neutral or +1° pull direction 3.THEN evaluate timing tweaks 4. If someone is telling him to flatten out his swing or to let the ball travel more PLEASE STOP DOING THAT. That doesn’t work for him You cannot time your way to elevation. Fix the tilt. Attack angle returns. Pull air follows. Please watch the video to see how his swing has gotten worse and flatter. We only have bat path data starting in 2023

Mission Valley Mafia

160,950 views • 5 months ago

$The rise of ZXMOTO and its founder, Zhang Xue, isn’t just another business success story; it is a disruptive masterclass in how a "challenger brand" can dismantle the decades-long hegemony of Japanese and European giants. While traditional powerhouses like Honda, Yamaha, and Ducati have long relied on their legacy and massive economies of scale, ZXMOTO has sprinted past them by weaponizing three distinct advantages: unfiltered passion, radical R&D reinvestment, and the world’s most agile manufacturing ecosystem. 1. The "Pegasus" Factor: Founder-Led Obsession In an industry often governed by corporate committees and "safe" incremental updates, Zhang Xue is a glaring anomaly. Known as the real-life version of the film Pegasus (a story of a grassroots racing dreamer), Zhang’s background as a self-taught mechanic gives him a technical intimacy with his products that most CEOs lack. *Authenticity as a Brand: Zhang doesn't just sell bikes; he lives them. From chasing TV crews at age 19 to personally leading rally teams, his "all-in" persona resonates with a new generation of riders tired of sterile corporate marketing. *The "Kill or Be Killed" Mindset: His decision to leave his previous successful venture (Kove Moto) to start ZXMOTO in 2024 specifically to chase WorldSBK glory shows a commitment to performance over profit—a gamble that has paid off in brand prestige. 2. Speed Over Legacy: The Chongqing Edge The Japanese "Big Four" have spent decades optimizing global supply chains, which, while efficient, can be slow to pivot. ZXMOTO, however, is a product of Chongqing, the "Motorcycle Capital of the World." *Hyper-Local Agility: With over 400 suppliers within a single city, ZXMOTO can iterate on a design in weeks what takes traditional brands months or years. *Cost-to-Performance Ratio: This ecosystem allowed ZXMOTO to launch the 820RR-RS—a bike that dominated the 2026 WorldSSP in Portugal—at a fraction of the cost of its European competitors. When a $6,000 bike beats a $20,000+ Ducati by nearly four seconds, the "value" conversation shifts from "cheap" to "superior engineering." 3. Radical R&D: Buying the Future Critics often dismiss new Chinese brands as "copycats." Zhang Xue silenced this narrative through sheer financial force. While industry standard R&D spending hovers around 3–5% of revenue, ZXMOTO has pushed its investment to nearly 10%. "ZXMOTO is investing nearly 70 million yuan annually in R&D, with plans to double that in 2026. They aren't just building bikes; they are buying the technological lead." By focusing on high-RPM engines and lightweight materials (like the 820RR’s class-leading power-to-weight ratio), they have bypassed the "entry-level" phase and jumped straight into the high-performance tier where Japanese brands once felt untouchable. 4. Racing as the Ultimate Litmus Test ZXMOTO’s strategy of "Win on Sunday, Sell on Monday" is an old-school philosophy executed with modern precision. By entering the World Supersport (WorldSSP) category—a production-based series—they proved that their street bikes are fundamentally superior. *Global Validation: The double-victory in Portugal (March 2026) wasn't just a trophy; it was a global certificate of quality. It shattered the "Made in China" stigma in real-time, leading to over 5,500 pre-orders in less than a week. *The Psychological Shift: For the first time, Western and Japanese riders aren't looking at ZXMOTO because it’s cheaper—they’re looking at it because it’s faster. Conclusion: A New Era of Competition The success of ZXMOTO and Zhang Xue signals that the "cut-throat" nature of the motorcycle industry has changed. The Japanese brands can no longer rely on the assumption of superior reliability or engineering. ZXMOTO has proven that when you combine China’s manufacturing muscle with a founder’s fanatical vision, you don't just join the race—you lead it. The era of the "Big Four" is officially over; the era of the Global Challenger has begun.$

The rise of ZXMOTO and its founder, Zhang Xue, isn’t just another business success story; it is a disruptive masterclass in how a "challenger brand" can dismantle the decades-long hegemony of Japanese and European giants. While traditional powerhouses like Honda, Yamaha, and Ducati have long relied on their legacy and massive economies of scale, ZXMOTO has sprinted past them by weaponizing three distinct advantages: unfiltered passion, radical R&D reinvestment, and the world’s most agile manufacturing ecosystem. 1. The "Pegasus" Factor: Founder-Led Obsession In an industry often governed by corporate committees and "safe" incremental updates, Zhang Xue is a glaring anomaly. Known as the real-life version of the film Pegasus (a story of a grassroots racing dreamer), Zhang’s background as a self-taught mechanic gives him a technical intimacy with his products that most CEOs lack. Authenticity as a Brand: Zhang doesn't just sell bikes; he lives them. From chasing TV crews at age 19 to personally leading rally teams, his "all-in" persona resonates with a new generation of riders tired of sterile corporate marketing. The "Kill or Be Killed" Mindset: His decision to leave his previous successful venture (Kove Moto) to start ZXMOTO in 2024 specifically to chase WorldSBK glory shows a commitment to performance over profit—a gamble that has paid off in brand prestige. 2. Speed Over Legacy: The Chongqing Edge The Japanese "Big Four" have spent decades optimizing global supply chains, which, while efficient, can be slow to pivot. ZXMOTO, however, is a product of Chongqing, the "Motorcycle Capital of the World." Hyper-Local Agility: With over 400 suppliers within a single city, ZXMOTO can iterate on a design in weeks what takes traditional brands months or years. Cost-to-Performance Ratio: This ecosystem allowed ZXMOTO to launch the 820RR-RS—a bike that dominated the 2026 WorldSSP in Portugal—at a fraction of the cost of its European competitors. When a $6,000 bike beats a $20,000+ Ducati by nearly four seconds, the "value" conversation shifts from "cheap" to "superior engineering." 3. Radical R&D: Buying the Future Critics often dismiss new Chinese brands as "copycats." Zhang Xue silenced this narrative through sheer financial force. While industry standard R&D spending hovers around 3–5% of revenue, ZXMOTO has pushed its investment to nearly 10%. "ZXMOTO is investing nearly 70 million yuan annually in R&D, with plans to double that in 2026. They aren't just building bikes; they are buying the technological lead." By focusing on high-RPM engines and lightweight materials (like the 820RR’s class-leading power-to-weight ratio), they have bypassed the "entry-level" phase and jumped straight into the high-performance tier where Japanese brands once felt untouchable. 4. Racing as the Ultimate Litmus Test ZXMOTO’s strategy of "Win on Sunday, Sell on Monday" is an old-school philosophy executed with modern precision. By entering the World Supersport (WorldSSP) category—a production-based series—they proved that their street bikes are fundamentally superior. Global Validation: The double-victory in Portugal (March 2026) wasn't just a trophy; it was a global certificate of quality. It shattered the "Made in China" stigma in real-time, leading to over 5,500 pre-orders in less than a week. The Psychological Shift: For the first time, Western and Japanese riders aren't looking at ZXMOTO because it’s cheaper—they’re looking at it because it’s faster. Conclusion: A New Era of Competition The success of ZXMOTO and Zhang Xue signals that the "cut-throat" nature of the motorcycle industry has changed. The Japanese brands can no longer rely on the assumption of superior reliability or engineering. ZXMOTO has proven that when you combine China’s manufacturing muscle with a founder’s fanatical vision, you don't just join the race—you lead it. The era of the "Big Four" is officially over; the era of the Global Challenger has begun.

Ignis Rex

10,444 views • 6 months ago

$The clip below is a historically accurate recreation of one of the most grueling aspects of China’s early nuclear program. This scene takes place at the Lop Nur nuclear test base in the Gobi Desert. The soldiers are engaged in an ancient, traditional Chinese construction technique known as manual earth ramming (人工打夯 - réngōng dǎ hāng). The loose, shifting sand of the Gobi is incredibly unstable. To prevent heavy structures from settling, tilting, or collapsing, the earth must be violently compacted. This technique was vital for securing the foundation of the massive, 100-meter-tall Ground Zero steel tower used to detonate China's first atomic bomb. Additionally, such backbreaking labor was used widely across the Lop Nur base to physically pound the desert flat for building barracks, paved roads, and other essential testing facilities. The tool the men are using is a multi-person collaborative wooden rammer. According to historical construction records, these traditional rammers were made of dense hardwood and typically weighed between 40 to 50 kilograms (about 90 to 110 pounds). Operating one required a tightly coordinated team of 10 to 12 men. To manage the immense friction and prevent horrific blisters, workers often used braided hemp ropes with knots tied every 20 centimeters, allowing for a better, safer grip as they hoisted the heavy weight into the air over and over again. For American audiences, it might seem jarring to see a nation developing a highly advanced thermonuclear weapon while seemingly lacking basic construction equipment like bulldozers or steamrollers. In the late 1950s, the Soviet Union abruptly withdrew its technical experts and heavy machinery from China. While China was gradually restoring parts of its national industrial base leading up to the first successful nuclear detonation in 1964, the remote, unforgiving environment of the Gobi Desert meant that base construction still relied overwhelmingly on raw human muscle. The military had to deploy ancient, agrarian folk techniques to engineer the foundations for a modern Cold War weapon. In this video clip, the commander stands above the men, waving a red flag and yelling a rhythmic chant: "Com’on Comrades!" to which the men heave the ropes and reply, "Heave-ho!" This was a critical safety and synchronization mechanism known as a ramming chant (夯歌;hānggē). Dropping a 100-pound block of wood effectively requires the rammer to fall perfectly vertically. If just one of the ten men pulls too weakly, or releases a fraction of a second too late, the rammer will tilt. A tilted rammer fails to compact the soil properly, exhausts the men trying to balance it, and, most dangerously, could easily crush workers' feet. The commander acting as the "lead chanter" serves as a human metronome. The tempo of his chant dictates the work. The rhythm of his chanting needs to ensure that every single man exerts the exact same amount of force at the exact same millisecond.$

The clip below is a historically accurate recreation of one of the most grueling aspects of China’s early nuclear program. This scene takes place at the Lop Nur nuclear test base in the Gobi Desert. The soldiers are engaged in an ancient, traditional Chinese construction technique known as manual earth ramming (人工打夯 - réngōng dǎ hāng). The loose, shifting sand of the Gobi is incredibly unstable. To prevent heavy structures from settling, tilting, or collapsing, the earth must be violently compacted. This technique was vital for securing the foundation of the massive, 100-meter-tall Ground Zero steel tower used to detonate China's first atomic bomb. Additionally, such backbreaking labor was used widely across the Lop Nur base to physically pound the desert flat for building barracks, paved roads, and other essential testing facilities. The tool the men are using is a multi-person collaborative wooden rammer. According to historical construction records, these traditional rammers were made of dense hardwood and typically weighed between 40 to 50 kilograms (about 90 to 110 pounds). Operating one required a tightly coordinated team of 10 to 12 men. To manage the immense friction and prevent horrific blisters, workers often used braided hemp ropes with knots tied every 20 centimeters, allowing for a better, safer grip as they hoisted the heavy weight into the air over and over again. For American audiences, it might seem jarring to see a nation developing a highly advanced thermonuclear weapon while seemingly lacking basic construction equipment like bulldozers or steamrollers. In the late 1950s, the Soviet Union abruptly withdrew its technical experts and heavy machinery from China. While China was gradually restoring parts of its national industrial base leading up to the first successful nuclear detonation in 1964, the remote, unforgiving environment of the Gobi Desert meant that base construction still relied overwhelmingly on raw human muscle. The military had to deploy ancient, agrarian folk techniques to engineer the foundations for a modern Cold War weapon. In this video clip, the commander stands above the men, waving a red flag and yelling a rhythmic chant: "Com’on Comrades!" to which the men heave the ropes and reply, "Heave-ho!" This was a critical safety and synchronization mechanism known as a ramming chant (夯歌;hānggē). Dropping a 100-pound block of wood effectively requires the rammer to fall perfectly vertically. If just one of the ten men pulls too weakly, or releases a fraction of a second too late, the rammer will tilt. A tilted rammer fails to compact the soil properly, exhausts the men trying to balance it, and, most dangerously, could easily crush workers' feet. The commander acting as the "lead chanter" serves as a human metronome. The tempo of his chant dictates the work. The rhythm of his chanting needs to ensure that every single man exerts the exact same amount of force at the exact same millisecond.

✝️🇺🇸Chet Ozmun🇨🇳☭

49,358 views • 6 months ago

The English spent years trying to take Mont Saint-Michel during the Hundred Years’ War. They never did. From a distance, it’s easy to see why the place has become one of the most photographed sights in France. A medieval village climbs a granite rock in the middle of a tidal bay, with an abbey sitting at the top. The religious story goes back to the early 8th century, when a sanctuary dedicated to the Archangel Michael was established on the rock. Benedictine monks arrived in 966, and over the centuries the abbey kept growing. With so little room on the rock, much of it had to be built vertically. Churches, halls, cloisters and living quarters were stacked onto the site over generations. On the north side, the 13th-century Gothic complex known as La Merveille, or “The Marvel,” rises in levels above the bay. By the early 1400s, the Hundred Years’ War had changed Normandy completely. Much of the region had fallen under English control, while Mont Saint-Michel continued to hold out. The village had walls and towers, and the bay itself made attacking the place difficult. Tides could change the ground around the mount quickly, turning open flats into water and making movement harder for an army. English forces began besieging Mont Saint-Michel in 1423. More than a decade later, they were still trying to take it. In 1434, English troops launched another attack with heavy artillery. The assault failed, and two large bombards were left behind. The English never captured the mount. The fortifications make a lot more sense once you know what was happening around it. This was a religious community sitting in the middle of a war zone, surrounded by territory that had largely fallen into enemy hands. I’d keep that in mind while walking up through the village. Most people stop for the view across the bay, and obviously you should too. But the climb through the gates, ramparts and narrow streets feels different when you know those defenses were actually tested. Then keep going until you reach the abbey. Inside, you start to see how much had to be fitted onto such a small piece of rock. Rooms are stacked on top of one another. Passageways run through different levels. Parts of the complex feel almost as defensive as they do monastic. At certain high tides, Mont Saint-Michel still looks cut off from the mainland. That shifting landscape was part of what made the place so difficult to approach for centuries. If I were planning the trip, I wouldn’t rush it. I’d stay nearby, see the mount from across the bay, walk through the village later in the day and give the abbey plenty of time. Mont Saint-Michel is spectacular even if you know nothing about it. Knowing that the English spent more than a decade trying and failing to take it makes those walls a lot more interesting. I write about places you may already know by sight, but probably don’t know the full story behind. If that sounds interesting, you should join us:

The English spent years trying to take Mont Saint-Michel during the Hundred Years’ War. They never did. From a distance, it’s easy to see why the place has become one of the most photographed sights in France. A medieval village climbs a granite rock in the middle of a tidal bay, with an abbey sitting at the top. The religious story goes back to the early 8th century, when a sanctuary dedicated to the Archangel Michael was established on the rock. Benedictine monks arrived in 966, and over the centuries the abbey kept growing. With so little room on the rock, much of it had to be built vertically. Churches, halls, cloisters and living quarters were stacked onto the site over generations. On the north side, the 13th-century Gothic complex known as La Merveille, or “The Marvel,” rises in levels above the bay. By the early 1400s, the Hundred Years’ War had changed Normandy completely. Much of the region had fallen under English control, while Mont Saint-Michel continued to hold out. The village had walls and towers, and the bay itself made attacking the place difficult. Tides could change the ground around the mount quickly, turning open flats into water and making movement harder for an army. English forces began besieging Mont Saint-Michel in 1423. More than a decade later, they were still trying to take it. In 1434, English troops launched another attack with heavy artillery. The assault failed, and two large bombards were left behind. The English never captured the mount. The fortifications make a lot more sense once you know what was happening around it. This was a religious community sitting in the middle of a war zone, surrounded by territory that had largely fallen into enemy hands. I’d keep that in mind while walking up through the village. Most people stop for the view across the bay, and obviously you should too. But the climb through the gates, ramparts and narrow streets feels different when you know those defenses were actually tested. Then keep going until you reach the abbey. Inside, you start to see how much had to be fitted onto such a small piece of rock. Rooms are stacked on top of one another. Passageways run through different levels. Parts of the complex feel almost as defensive as they do monastic. At certain high tides, Mont Saint-Michel still looks cut off from the mainland. That shifting landscape was part of what made the place so difficult to approach for centuries. If I were planning the trip, I wouldn’t rush it. I’d stay nearby, see the mount from across the bay, walk through the village later in the day and give the abbey plenty of time. Mont Saint-Michel is spectacular even if you know nothing about it. Knowing that the English spent more than a decade trying and failing to take it makes those walls a lot more interesting. I write about places you may already know by sight, but probably don’t know the full story behind. If that sounds interesting, you should join us:

The Timeless Traveler 🇺🇸

20,348 views • 1 month ago

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

101,793 views • 6 months ago

As a new wave of fire and high winds threaten Los Angeles, the media is reporting that California’s elected leaders are not to blame and that right-wing influencers and Donald Trump are spreading misinformation and politicizing a tragedy. Racial and gender quotas through DEI aren’t to blame. No, Mayor Karen Bass didn’t cut the Fire Department’s budget. No, Gavin Newsom didn’t cut CalFire’s wildfire prevention budget. And no, there wasn’t any way to prevent these fires or the fire hydrant water from running out. Climate change made the disaster inevitable due to “whiplashing” rain levels. They’re all lies. The Fire Department had made DEI such a priority that the city’s Deputy Fire Chief dismissed concerns that women would not be able to carry a man out of a fire by saying, “He got himself in the wrong place if I have to carry him out of a fire.” Newsom did indeed reduce CalFire’s wildfire prevention budget by $150 million in 2020. If California had elected leaders who cared about the people and were competent, they could have prevented the catastrophic fires from destroying 14,000 homes and businesses and forcing nearly 200,000 people to evacuate. Climate change is not responsible for the disasters and there is no change in the rain pattern. As always, nuance is required. The offhand remark by the Fire Chief is not proof that DEI contributed to the inadequate response. The disaster is decades in the making. LA’s leaders have known that the city was unprepared for catastrophic wildfires since the Bel Air Fire of 1961, which occurred when Karen Bass was a child and Gavin Newsom wasn’t alive. LA’s fire budget had actually increased by about $50 million compared to the last budget, reported Politico, Time, and the LA Times. And Newsom increased the CalFire budget after 2020 and increased land treated for wildfire prevention by 90,000 acres. But these facts are either wrong, misleading, or both. The attitude toward vulnerable men expressed by the deputy Fire Chief is deeply alarming and anathema to firefighter ethics. That the disaster was decades in the making makes the inaction by California political leaders even more inexcusable. The City Council in November approved $53 million to raise salaries, but that funding is completely irrelevant to the millions Bass cut, which her fire chief last month said had “severely limited the department’s capacity to prepare for, train for, and respond to large-scale emergencies, including wildfires.” And while funding for wildfire prevention increased recently, it wasn’t enough, and Newsom was caught overstating how much land was treated by 690%. The amount of irresponsibility and incompetence displayed by Newsom and Bass is so extreme that insiders are coming forward and speaking out publicly. The owner of the Los Angeles Times went on national television to call it “crazy that we don’t elect leaders with competence.” And LA Fire Chief Kristen Crowley went on CNN, CBS, and Fox to denounce Bass. “Let me be clear,” she said, “the $17 million budget cut… did absolutely negatively impact…. We do not have enough firefighters….We need 62 more fire stations. We've had a 55 percent increase in overall call volume since 2010 and we’re doing it with less firefighters.” As I reported yesterday, over half of all fires that the LA Fire Department puts out are started by the homeless, who may well have started some of the fires ravaging LA. Gavin Newsom spent $24 billion of taxpayer money to increase homelessness by 40% since he took office. Karen Bass ran on a promise to force the homeless inside into shelters but has not done so. Every hour that passes, more information emerges of the corruption, incompetence, and failure. A major reservoir in Pacific Palisades, an epicenter of the fires, was out of commission for minor repairs when disaster struck. Had it been in operation, water pressure would have lasted longer during critical hours, and many homes may have been saved. Yesterday, a leaked LA government memo revealed that Bass had intended to cut an additional $49 million, on top of the $17.5 million already cut, from the fire budget. “I was also directed to develop a plan as part of a budget reduction exercise, and that could equate to 48.8 million,” the LA Fire chief told CNN. “I rang the bell that these additional cuts could be very, very devastating for our ability to provide public safety. That would have resulted to 15 fire stations closing down and potentially the elimination of over 300 firefighters.” The date of the memo is January 6, which is four days after the National Weather Service warned of danger, two days after Bass flew to Ghana on a vanity junket, and one day before the start of the Palisades fire. And LA Fire Department insiders say the head of the city’s Department of Water and Power, who Bass hired, knowingly left fire hydrants remain broken for months, and was the person responsible for draining the emptied reservoir. The response from the news media is that critics of all of this should shut up. “We’re on fire,” editorializedthe LA Times. “Maybe this is not the time for your political hot take.” Why are the LA Times and others in the media defending Bass and Newsom? In large measure because they officially endorsed them. More than that. They actively campaign for them. The hyper-partisan turn of California media two decades ago predated the more recent hyper-partisan nature of the national media. That Democrats had total, supermajority control over the state for 20 years made California media super-authoritarian. The LA Times, in particular is a radical Left publication. It has for years adamantly opposed hospitalizing homeless mentally ill people or requiring homeless addicts to go inside. In both 2020 and in 2021, the LA Times editorial board called for defunding the police to divert funding to social services. For the LA Times, Gavin Newsom and Karen Bass, who visited Cuba at least eight times, expressing admiration for its system of socialist dictatorship, aren’t Left-wing enough. For the media and California’s politicians, the problem is we the people. We complain too much. Our taxes aren’t high enough. We’re causing too much climate change. We get too much in the way of police and fire fighting. And most of all, we spend too much time listening to right-wing influencers who only spread misinformation. We need to sit down and shut up. Like LA’s radical Left deputy fire chief, the media and California’s politicians believe, deep down, that if the people of Los Angeles have to be rescued from fires, then that’s just proof that they got themselves in the wrong place.

As a new wave of fire and high winds threaten Los Angeles, the media is reporting that California’s elected leaders are not to blame and that right-wing influencers and Donald Trump are spreading misinformation and politicizing a tragedy. Racial and gender quotas through DEI aren’t to blame. No, Mayor Karen Bass didn’t cut the Fire Department’s budget. No, Gavin Newsom didn’t cut CalFire’s wildfire prevention budget. And no, there wasn’t any way to prevent these fires or the fire hydrant water from running out. Climate change made the disaster inevitable due to “whiplashing” rain levels. They’re all lies. The Fire Department had made DEI such a priority that the city’s Deputy Fire Chief dismissed concerns that women would not be able to carry a man out of a fire by saying, “He got himself in the wrong place if I have to carry him out of a fire.” Newsom did indeed reduce CalFire’s wildfire prevention budget by $150 million in 2020. If California had elected leaders who cared about the people and were competent, they could have prevented the catastrophic fires from destroying 14,000 homes and businesses and forcing nearly 200,000 people to evacuate. Climate change is not responsible for the disasters and there is no change in the rain pattern. As always, nuance is required. The offhand remark by the Fire Chief is not proof that DEI contributed to the inadequate response. The disaster is decades in the making. LA’s leaders have known that the city was unprepared for catastrophic wildfires since the Bel Air Fire of 1961, which occurred when Karen Bass was a child and Gavin Newsom wasn’t alive. LA’s fire budget had actually increased by about $50 million compared to the last budget, reported Politico, Time, and the LA Times. And Newsom increased the CalFire budget after 2020 and increased land treated for wildfire prevention by 90,000 acres. But these facts are either wrong, misleading, or both. The attitude toward vulnerable men expressed by the deputy Fire Chief is deeply alarming and anathema to firefighter ethics. That the disaster was decades in the making makes the inaction by California political leaders even more inexcusable. The City Council in November approved $53 million to raise salaries, but that funding is completely irrelevant to the millions Bass cut, which her fire chief last month said had “severely limited the department’s capacity to prepare for, train for, and respond to large-scale emergencies, including wildfires.” And while funding for wildfire prevention increased recently, it wasn’t enough, and Newsom was caught overstating how much land was treated by 690%. The amount of irresponsibility and incompetence displayed by Newsom and Bass is so extreme that insiders are coming forward and speaking out publicly. The owner of the Los Angeles Times went on national television to call it “crazy that we don’t elect leaders with competence.” And LA Fire Chief Kristen Crowley went on CNN, CBS, and Fox to denounce Bass. “Let me be clear,” she said, “the $17 million budget cut… did absolutely negatively impact…. We do not have enough firefighters….We need 62 more fire stations. We've had a 55 percent increase in overall call volume since 2010 and we’re doing it with less firefighters.” As I reported yesterday, over half of all fires that the LA Fire Department puts out are started by the homeless, who may well have started some of the fires ravaging LA. Gavin Newsom spent $24 billion of taxpayer money to increase homelessness by 40% since he took office. Karen Bass ran on a promise to force the homeless inside into shelters but has not done so. Every hour that passes, more information emerges of the corruption, incompetence, and failure. A major reservoir in Pacific Palisades, an epicenter of the fires, was out of commission for minor repairs when disaster struck. Had it been in operation, water pressure would have lasted longer during critical hours, and many homes may have been saved. Yesterday, a leaked LA government memo revealed that Bass had intended to cut an additional $49 million, on top of the $17.5 million already cut, from the fire budget. “I was also directed to develop a plan as part of a budget reduction exercise, and that could equate to 48.8 million,” the LA Fire chief told CNN. “I rang the bell that these additional cuts could be very, very devastating for our ability to provide public safety. That would have resulted to 15 fire stations closing down and potentially the elimination of over 300 firefighters.” The date of the memo is January 6, which is four days after the National Weather Service warned of danger, two days after Bass flew to Ghana on a vanity junket, and one day before the start of the Palisades fire. And LA Fire Department insiders say the head of the city’s Department of Water and Power, who Bass hired, knowingly left fire hydrants remain broken for months, and was the person responsible for draining the emptied reservoir. The response from the news media is that critics of all of this should shut up. “We’re on fire,” editorializedthe LA Times. “Maybe this is not the time for your political hot take.” Why are the LA Times and others in the media defending Bass and Newsom? In large measure because they officially endorsed them. More than that. They actively campaign for them. The hyper-partisan turn of California media two decades ago predated the more recent hyper-partisan nature of the national media. That Democrats had total, supermajority control over the state for 20 years made California media super-authoritarian. The LA Times, in particular is a radical Left publication. It has for years adamantly opposed hospitalizing homeless mentally ill people or requiring homeless addicts to go inside. In both 2020 and in 2021, the LA Times editorial board called for defunding the police to divert funding to social services. For the LA Times, Gavin Newsom and Karen Bass, who visited Cuba at least eight times, expressing admiration for its system of socialist dictatorship, aren’t Left-wing enough. For the media and California’s politicians, the problem is we the people. We complain too much. Our taxes aren’t high enough. We’re causing too much climate change. We get too much in the way of police and fire fighting. And most of all, we spend too much time listening to right-wing influencers who only spread misinformation. We need to sit down and shut up. Like LA’s radical Left deputy fire chief, the media and California’s politicians believe, deep down, that if the people of Los Angeles have to be rescued from fires, then that’s just proof that they got themselves in the wrong place.

Michael Shellenberger

1,658,156 views • 1 year ago