Bober_smart

@Bober_smart • 21,041 subscribers

AI Builder | Technologies | Testing

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I got 48 million views and 53k followers on Instagram, and all of this in 2 days I came up with a character Generated a video Published The year 2026 gives huge opportunities for development We are moving towards AI influencers I named him Artur and he is just as he is, a self-made guy who doesn't try to please others, he looks unusual and attracts people's attention I don't know how far this will go, but I definitely don't plan on stopping

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I built an absolute monster. My crazy idea to merge all the most powerful AI tools together made me $832 while I was asleep opus 5.5 + REA + Jev + Dots + Grok Bot + Obsidian Half a dozen utilities. A single unified ecosystem. Zero human intervention Opus 5.5 -> acts as the core intellect, designing every assignment Grok bot -> monitors X around the clock to spot emerging patterns REA -> conducts deep analysis on any subject within a four-minute window Jev -> executes concepts autonomously, turning them into reality Dots -> weaves all six components into a seamless workflow Obsidian -> functions as the archive containing 1,260 records with zero data loss Before heading to bed, I assigned it a single objective: discover a profitable market gap and launch a working product by sunrise, keeping the expenses under $15 I went to sleep at 11:40 PM, and here is what unfolded over the course of seven hours: 12:12 AM: Grok bot uncovers 1,900 distinct posts from delivery workers venting about a shared frustration: tracking their income across three separate platforms 1:05 AM: REA evaluates the competitive landscape, finding 14 existing paid solutions starting at $19 monthly, with users universally criticizing the exact same two software glitches 2:30 AM: Opus 5.5 drafts an application architecture designed to resolve both flaws, consisting of nine screens and a single database, without asking me a single question 4:10 AM: Jev programs the software, deploys it live, and writes the promotional landing page. 5:45 AM: Dots generates a 30-second promotional animation and publishes it alongside three forum threads 7:20 AM: Obsidian logs every single action, financial expense, and misstep along the way Upon waking up, I discovered a fully functioning application, 243 registrations, and 31 paying customers subscribed at $9 each, bringing in $832 before my morning meal The entire nightly overhead amounted to $5.10 for API tokens plus a $4 web domain, totaling $9.10 -> yielding a 91x return while I slept The system even exercised self-control: when Jev attempted to purchase a $55 web address, it hit the preset $15 threshold and automatically opted for a $4 alternative instead The primary misconception is that individuals turn to AI merely for answers: instead, I provided mine with a clear objective, a strict timeline, and a financial ceiling I did not author a single line of programming code, nor did I open a single browser tab: I simply went to sleep While everyone else is holding out for artificial general intelligence, I already have six autonomous utilities pulling the night shift

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A 21-year-old guy from Brazil created an AI construction worker girl, and 764 men bought a paid subscription to see her Subscription price: $9.99 Total revenue: $7,632 Investment: $200 spent on Claude for generation He chose a niche that wasn't crowded and made the right call: the "construction girl" persona really caught men's attention At first, he posted videos of her on TikTok, and once he built an audience, he started promoting his Fanvue page, where the paid subscription (and some slightly different content, if you know what I mean) was hosted It took him 37 days to set it all up. He easily recouped his investment and reached a solid profit AI is a useful tool, but first and foremost, you need to have a good imagination

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I still don't understand why everyone is not using this yet. Thanks to it, a year ago I increased my income to 17,000 dollars a month Andrey Karpathy, co-founder of OpenAI, published a simple idea that got 16 million views: stop using AI to write code, use it to build a second brain You point Claude Code to a folder, drop any source in there (an article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. It compounds like interest: the more you feed it, the smarter it gets Here is the gist: Install Obsidian, create a vault, open it in Claude Code Paste the file with Karpathy's wiki idea and tell Claude to build it Claude creates three folders: raw for sources, wiki for its pages, CLAUDE which runs everything Drop any source into raw and say "ingest this" Ask questions across everything, forever Five minutes to set up, and you never start with an empty chat again The full step-by-step guide is in the article. Save to bookmarks

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A 23-year-old Indian developer created a game called GTA India and it has already been purchased by 16,548 people Game Price: $10 Revenue: $165,480 Costs: $200 spent on Claude for modifications Instead of classic bank robberies, the missions involve taking control of illegal spice markets or intercepting shipments of elite tea Instead of highway chases in Los Santos, players engage in chaotic, wild tuk-tuk races through the narrow alleys of Mumbai, dodging sacred cows and endless crowds of people He developed the game using Claude on the Unity engine, taking GTA 5 as a base. He modified the AI, rewrote the code, and launched the game on a server Sometimes, for success, all it takes is to take a popular product and give it a fresh twist

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A 19-year-old Japanese man created an AI girl and earned $5,614 in 2 weeks He used Claude to create the photo and video material He started a TikTok for her where she danced; after 5 days, there were already 52,544 new followers on this account He understood that everyone liked the girl very much and created an account for her on Fanvue > TikTok for advertising > Fanvue for earnings After 2 weeks, 562 people signed up for a paid subscription -> subscription price is $9.99 -> $5,614 profit AI gives opportunities literally at every step

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A 22-year-old Indian who turned himself into an anime character made $6,405 in 6 hours At first, he didn't take it seriously, he started the stream just to have a laugh, but the result surprised everyone He spent $20 on Claude Claude changed his appearance and voice in real-time Women liked the look so much that they started donating The biggest donation was $750 In 6 hours, $6,405 Artificial intelligence is frighteningly realistic, and literally anyone can repeat this

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A 19-year-old student from China, Zhang Wei, developed an AI radar and sold it to Hong Kong for $550,000 He created it using Claude, spending just $20 and a month on development He walked into the Hong Kong administration office with a flash drive and asked for just 5 minutes of their time. 30 minutes later, he walked out with a check for $550,000 The code, connected to a camera, detects speed in real time. If the speed exceeds the limit, Claude takes a video clip and identifies the owner by the car's license plate. The video and the fine are then automatically sent to the owner's email address Unlike a conventional radar that only takes a photo and doesn't always work, this AI radar eliminates disputes because it captures video and makes the process fully autonomous by sending out the fines on its own The article includes the ready-to-use configurations.

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47-year-old man from Japan made $13,450 in a month. He created an AI girl and made a profile for her on OnlyFans and Fanvue Costs: $20 for Claude/month He created a TikTok account for her -> 7 days -> +1.2M views + 4,678 followers He created a Reddit account where he posted her photos and short videos Thus, he set up 2 traffic sources absolutely for free, men got interested, followed the link and subscribed to OnlyFans/Fanvue First week: > OnlyFans: +143 subscriptions > Fanvue: +64 subscriptions Each subscription is $9.9 -> $2,700 Claude created the AI girl, comes up with the visuals, works with the platform algorithms, posts content at the scheduled time, works autonomously The article contains 10 folders with tools for creation and workflow automation

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It is becoming f*cking dangerous: every iOS owner needs to know this Your "deleted" pictures are actually still around Claude Code uncovered years worth of them resting inside a concealed cache on my iPhone I plugged my iPhone into my MacBook to create a backup, having Claude Code run a routine security sweep simultaneously. It flagged an unexpected directory named PhotoData/Thumbnails Countless files. Images, clips, and screen grabs. A significant portion consisted of items I had previously erased Pictures from several years ago. Screen captures I snapped and discarded mere seconds later. Stuff I deliberately cleared out from the Recently Deleted album. Fragments of it were still lingering there Here is what turned up within that cache: old snapshots of financial applications photos I got rid of immediately after capturing them random images I no longer wanted on my device a handful of files I specifically recall deleting on multiple occasions When an image is removed on an iPhone, iOS strips it from your main gallery and the Recently Deleted folder. However, it preserves a compressed duplicate inside the Spotlight search cache so the system can still index items for queries. That specific storage area never gets fully purged I reviewed which software programs held permissions to access files and folders. There were far more than anticipated, encompassing utilities I downloaded ages ago and completely overlooked. Any of them could potentially read data out of that cache I went down the roster and revoked permission for the vast majority of them The exact prompt I deployed is provided below. It takes very little time if a backup is already on hand How many apps on your device currently possess File access privileges?

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THIS IS AN ABSOLUTE GOLDMINE The team at Anthropic just revealed one of the most effective techniques for Claude Code The core concept: run Sonnet, Haiku 5.5, and Opus 5.5 simultaneously, letting each model focus strictly on what it does best You get higher quality output while dramatically reducing token consumption, since every specific job gets routed to the optimal model To spin up Claude Code with this setup, simply execute: ⁠claude --model sonnet --advisor opus⁠ Here is how the workload is split: > Sonnet 5.5 handles the primary session, writes code, and applies bug fixes > Haiku 5.5 scans the codebase in parallel: performing searches, running grep queries, exploring docs, and auditing diffs > Opus 5.5 acts as an on-demand advisor for critical decisions and approves final code diffs > You stop burning expensive Opus context on routine tasks that don't require high-level reasoning Opus intervenes exclusively during three specific scenarios: > Right before locking in an execution plan > Whenever the exact same error triggers twice in a row > Prior to marking a task as complete Sonnet builds. Haiku scans and explores. Opus reviews JEV engineering applies the exact same principle one layer deeper: routine execution forks that don't need high-level reasoning (determining which file to inspect, which tool to trigger, or whether to retry or stop) are processed by JEV in sub-milliseconds, leaving big models to handle only complex decision splits The full architectural tree: Sonnet 5.5 manages the primary session and modifies code Search maps out the repository structure via Haiku 5.5 Grep locates call references using Haiku 5.5 Docs fetches API specifications through Haiku 5.5 Opus 5.5 serves as an advisor, reading the complete conversation history whenever consulted JEV routes lightning-fast micro-forks in milliseconds Feed this tree structure alongside the prompt below into Claude Code Reconfigure my Claude Code workspace based on this architecture: 1. Run the primary session utilizing Sonnet 5.5, with Opus 5.5 designated as the advisor 2. Set up three read-only Haiku 5.5 subagents: search (maps out the repo), grep (locates call sites), and docs (retrieves API documentation) 3. Insert a single rule into CLAUDE.md: consult the advisor prior to committing to a plan, after encountering an identical error twice, and before marking a task as done 4. Direct rapid, deterministic decisions (tool selections, file paths, retries) through JEV. Show all modifications as a diff first. Do not execute any edits until I grant permission Bookmark this setup: it will become a daily driver in your workflow

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I still don't understand why everyone isn't doing this yet. Elon Musk reposted this guide, and using this exact agent setup, I made $9,300 just last week Eight Grok agents on the desk, costing $200 a month, service a trading floor that typically costs a crypto fund $500,000 a year in analyst salaries A 5 AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time. RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human While I was sleeping, the system scanned 164 tokens, selected 21 qualifying setups, and executed 8 trades. The result: net profit of $9,300 (already after fees) Each agent has its own virtual browser, terminal, and local cloud memory. The trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this before your next trade. Save the guide

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It is becoming f*cking dangerous: I don't understand why everyone still isn't doing this, thanks to this I reached an income of $12,000 as early as 3 months ago Andrej Karpathy, co-founder of OpenAI, shared a straightforward concept that blew up with over 23 million views: stop relying on AI strictly for coding and start using it to construct your own personal knowledge engine Point Claude Code to a folder, toss in raw materials (whether it's an article, a video transcript, or a PDF) and Claude processes everything, links relevant topics together, and organizes it into a self-updating wiki of your personal knowledge. It acts like compound interest: the more information you add, the more capable it becomes Here is the exact breakdown: Set up Obsidian, create a fresh vault, and open it using Claude Code Supply Karpathy's wiki layout prompt and instruct Claude to build the architecture Claude automatically sets up three components: a ⁠raw⁠ directory for source files, a ⁠wiki⁠ directory for processed pages, and a ⁠CLAUDE.md⁠ control file to run the system Dump any document into the ⁠raw⁠ folder and run "ingest this" Query your entire knowledge repository at any time, indefinitely It takes just five minutes to configure, eliminating the need to ever start a conversation with a completely blank context window again Check the link below for the complete step-by-step walkthrough on setting up Claude with Obsidian Bookmark this post for later

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A 27-year-old guy from China bought 100 Mac minis and turned his apartment into a server hub Instead of furniture, the space is filled with neat racks where a hundred Mac minis hum like a living organism, processing gigabytes of data in a continuous stream Many small AI startups in Asia cannot afford to train models on NVIDIA H100 servers: it is insanely expensive He provides his Mac minis for running and fine-tuning small, highly specialized models. He takes on the dirty work of data labeling and quality assurance by using his network of agents that check each other's work > His initial investment was $59,900 > He was able to recoup his costs in 3 months Right now, his average income is $25,000–$30,000 per month He is not a genius: he simply found a niche with high demand and created an offer

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A 33-year-old guy from Beijing decided to pull a prank but ended up making $3,856 in just 3 hours He created an AI girl using Claude and launched a livestream on TikTok, YouTube, and Kick Claude modified the appearance, background, voice, and even the language in real-time Just 10 minutes in, the first $55 donation came through Men liked the girl so much that they started donating en masse > Over the course of 4 hours, he received $3,856 in donations > The largest single donation was $500 The article contains 10 folders with tools for creation and workflow automation

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It blows my mind how few people have implemented this setup. A year ago, this exact system allowed me to automate 90% of my tasks and expand my business Andrey Karpathy, co-founder of OpenAI, dropped a simple idea that generated 22 million views and 108,000 saves "stop relying on AI strictly for generating code, and start leveraging it to build a personal second brain" The logic is straightforward: You link Claude Code to a specific directory and throw in any reference materials (articles, meeting transcripts, or PDFs) The system analyzes the text, maps out connections, and constructs a living repository of everything you know. It compounds continuously: as you feed it more data, the entire ecosystem becomes significantly smarter How it breaks down in practice: Launch Obsidian, set up a new repository, and connect it to Claude Code Feed in the template based on Karpathy's wiki approach and instruct Claude to deploy the architecture The model automatically constructs three core areas: raw for your incoming documents, wiki for organized pages, and a master CLAUDE file that coordinates all processes Move any new resource into the raw folder and issue a quick command to process it Query your entire personal knowledge base whenever you need answers A quick five-minute deployment means you will never have to initiate a prompt from a blank canvas again I published the complete guide in the article. Make sure to bookmark it for later

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By tomorrow, everyone will be using this: Anthropic just revealed the ultimate power move for Claude Code The concept: have Opus 5.5 design the master plan as a script, then deploy parallel swarms of the new Haiku 5.5 Massive scale operations with zero wasted Opus compute: the script manages the execution loop so Opus only reviews the final diff Simply boot up Claude Code with these parameters: claude --model opus --effort ultracode Here is the task distribution: -> Opus 5.5 translates your target into a fully runnable workflow script -> Haiku 5.5 scans all files concurrently at 340 tokens/sec to spot candidates -> Sonnet 5.5 applies each patch and validates findings within an isolated workspace -> You eliminate wasting Opus context on dozens of agent log transcripts Opus is involved at only three specific steps: -> writing the initial workflow script before execution -> analyzing verified results once the swarm wraps up -> giving final approval prior to committing any code to git Opus architects | Haiku audits | Sonnet delivers JEV engineering applies the exact same principle a level deeper: logic paths that require no deep reasoning (choosing files, picking tools, handling retries/stops) pass through JEV in milliseconds, leaving heavy models to focus only on complex branches The complete architecture: Opus 5.5 orchestrates the core session and generates workflow.js pipeline() fans out instances of Haiku 5.5 to inspect every file parallel() schema validators eliminate false alarms directly in V8 Sonnet 5.5 applies fixes within dedicated, isolated worktrees verify double-checks all code diffs prior to summary generation Opus 5.5 processes exclusively the results that survived validation JEV routes lightweight micro-decisions in milliseconds Feed this architecture and prompt directly into Claude Code Reconfigure my Claude Code setup following this tree: 1. Execute the primary session using Opus 5.5 with ultracode enabled 2. Assign read-only scanning phases to Haiku 5.5 across all workflows, while routing code modification steps to Sonnet 5.5, running each edit inside its own isolated copy 3. Update CLAUDE.md with a new rule: assign a separate verifier agent to every issue before reporting, and terminate fix loops after two iterations without progress 4. Route fast, deterministic branching (tool selection, path routing, retry logic) via JEV Present every modification as a diff upfront do not execute changes until approved Bookmark this to stay one step ahead

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A 22-year-old Chinese man created 2 AI girls and built a business on it: he managed to earn $24,542 in a month His investment was $20 for Claude For one AI girl, he created an account on Fanvue with a paid subscription of $9.99 Claude conducted an analysis of male preferences and created the ideal girl it creates photos and videos in autonomous mode and posts them according to a timer Month: +1,265 new subscribers -> $12,637 With the help of another AI girl, he launches a stream on three platforms: TikTok, YouTube, and Kick Claude changes the appearance and voice in real time right during the stream Men really liked the girl, and they regularly send donations $500 is the largest donation Month: +$11,905 Total amount $24,542 AI + 🧠 = unlimited possibilities

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A 22-year-old girl from Zimbabwe gained 235,474 TikTok followers in 28 days and earned $5,800 from advertising Using Claude, she developed personas, created characters, and generated video content She posted 4 videos every day, and at the beginning, they received almost no views However, everything changed on the 15th day: one of her videos went viral, garnering a staggering 21 million views. In just 24 hours, her account gained 235,474 followers In her blog, she revealed that 5 brands booked advertising with her, and in total, she earned $5,800 over the 28 days Claude came up with everything: she simply pressed the button to publish

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This video, created by a 23-year-old guy from Norway using Claude, has taken the internet by storm The guy asked Claude to generate a cartoon video of Erling Haaland set to a trending song. With a brand-new TikTok account and just that single video, he reached 135 million views and 15 million likes, gaining 58,900 followers in just 24 hours It’s interesting to wonder if this was planned to ride the wave of World Cup hype, or if it was just a lucky coincidence Regardless, one thing is clear: AI has the power to create something truly monumental

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0:22

It is becoming f*cking dangerous: AI agents from Claude Code transformed an ordinary academic reading list into an interactive research lab right inside the browser Boris Cherny, who created Claude Code, gave a dozen agents a stack of 64 research papers with a strict assignment: design a web platform where any user can independently reproduce physical experiments There you can select a fluid flow model, adjust external conditions, and analyze in real time how the physics of the process changes The interface allows switching between algorithms right during the scene, inspecting the formulas involved, source scripts, and numerical metrics alongside the graphics Each link in the team received a clear scope of work: > rightarrow analysts pull the math, baseline assumptions, and test settings from the texts > rightarrow coders translate formulas into working algorithms > rightarrow auditors check the resulting dynamics against the original papers > rightarrow interface specialists build control panels for every experiment The danger lies in the fact that a pretty visualization can easily turn out to be mathematically wrong Therefore, controllers strictly check adherence to mass conservation laws, calculation stability, and accurate matching with the source metrics before launching into production For every experiment, the interface displays: the statement being tested the constants involved the deviation from the baseline calculation blind spots requiring additional verification The resulting sandbox combined 11 approaches and 28 reference scenes. Seven of them matched the original within allowable tolerances, while four remained stuck in "pending revision" status If you want to run something similar, upload your stack of PDFs into Claude Code and give this command: Turn these papers into an interactive web complex: 1. Extract working algorithms, mathematical models, and test parameters. Be sure to specify page numbers and highlight gaps 2. Assign different methodologies to isolated agents, unifying them with a shared input field and single measurement tools for correct analytics 3. Set up an independent review stage: let reviewers record bugs, and leave all unverified results clearly marked with warning tags 4. Design convenient controls to tweak parameters, compare methodologies, and run through the source code It is wiser to start with a single document and a single baseline experiment, gradually scaling up the number of agents Be sure to pack dependencies and clean input data so that an outside researcher can bring up the entire testbed from scratch with a single button Full instructions on how to create this can be found in the article below

Bober_smart

796,763 Aufrufe • vor 14 Tagen

0:22

It is becoming f*cking dangerous: The Claude Code tool found absolutely every shot that I considered permanently deleted from my iPhone. Data spanning 4 years of photos and videos was continuously stored in a disguised system cache. Every application with permissions to the file system had direct access to them I synced my smartphone with a MacBook to create a backup. Then I ran the Claude Code vulnerability scan mentioned in my previous post. The scanner unexpectedly flagged a folder that I had not even asked it to check, a system directory named PhotoData/Thumbnails containing over 183,000 items. Pictures, video clips, screenshots, absolutely everything I had gotten rid of Archives for 2021, 2022, 2023, and 2024. Shots I deleted instantly after taking them. Photos for which I manually cleared the Recently Deleted section. Originals that I double checked and erased a second time just to be safe. All of it was still stored there What exactly was found in that cache: A random photo of a recipe from a cookbook from 2023 Screenshots of shopping lists and notes with daily chores Failed takes and blurry landscape shots deleted right during a walk A screenshot of a bus schedule from 2022 captured for just a few seconds Photos of price tags and store labels deleted right at the checkout A saved meme image from social media that I deleted back in 2024 A total of 173,521 files. Some of them in original resolution. Everything neatly sorted chronologically starting from 2021 When you delete media on an iPhone, iOS simply removes it from your gallery and trash. In reality, iOS keeps compressed copies in the Spotlight search index directory. That is precisely how fast keyphrase search works on your phone. Apple never clears this area, not after a month, not after a year. Claims of permanent deletion are simply untrue I decided to check the list of software that has permission to access Files and Folders. It turned out there were 19 of them: weather utilities, QR code scanners, PDF readers, and even an old flashlight app installed in 2021. Any of these applications could freely read the data I considered destroyed all this time I cut down the list of these applications from 19 to 5 in just a couple of clicks The beauty of modern technology is that it allows us to recall what we have long forgotten

Bober_smart

103,654 Aufrufe • vor 2 Tagen

0:24

It is becoming f*cking dangerous: when Anthropic disclosed this, they didn't even realize they were opening a Pandora's box 1. Create a folder named ⁠SECOND BRAIN⁠ on your PC 2. Launch Claude Code inside this folder and install GWS CLI (to gain access to your Gmail, Calendar, and Drive) 3. Create a subfolder named ⁠MEMORY⁠ inside the main folder 4. Place a ⁠CLAUDE.md⁠ file in the main folder and add a rule to save all key details to the ⁠MEMORY⁠ folder 5. Install Graphify from GitHub to link your notes and build a knowledge graph 6. Install Playwright so Claude can control a web browser 7. Set up skills to merge everything into an automation executable with a single command The whole setup process takes around 20 minutes Turn Claude into your ultimate second brain, equipped with long-term memory, email and cloud access, plus full web browsing features Find the step-by-step instructions in the article below

Bober_smart

363,839 Aufrufe • vor 13 Tagen

0:22

It is becoming f*cking dangerous: when Anthropic released this, they didn't even realize what a massive chain reaction they were triggering 1. Set up a folder called SECOND BRAIN on your computer 2. Open Claude Code inside that directory and configure GWS CLI to give it access to your Google Drive, Gmail, and Calendar 3. Make a new subfolder named MEMORY inside the root folder 4. Add a ⁠CLAUDE.md⁠ file to the root directory with instructions to log all critical context inside the MEMORY folder 5. Download and install Graphify from GitHub to connect your notes into a knowledge graph 6. Set up Playwright so Claude gets full browser automation capabilities 7. Configure skills to bundle everything into a single automation executable triggered by one command The entire setup takes roughly 20 minutes Transform Claude into your ultimate second brain, packed with persistent memory, direct cloud and email integration, plus seamless web browsing Check out the full step-by-step guide in the article below

Bober_smart

194,847 Aufrufe • vor 8 Tagen

1:00

A 24-year-old guy from Texas turned himself into Elon Musk and made $4,356 in 4 hours It all started as a joke, he launched a TikTok stream, but the result was unpredictable The costs amounted to $20 for Claude Claude changed his appearance in real time The audience loved the look so much that they started donating and sending gifts At the end of the stream, his balance was $4,356 Peak viewership reached 11,430 The stream gathered 186,580 likes He gained 65,000 new followers And the funniest thing is, everyone knew it was AI

Bober_smart

2,461,491 Aufrufe • vor 4 Monaten

$I don't understand why everyone isn't doing this yet. Anthropic released a guide for Claude that makes work much more efficient while burning a fraction of the tokens Main Idea: Agent Teams in Claude Code Instead of burning the expensive Opus 5.5 context on every line of code, tasks are delegated across an autonomous swarm: Architect (Opus 5.5, high effort): Plans the structure and handles final PR merges Developers (Sonnet 5.5, medium effort): Write code inside isolated ⁠git worktree⁠ environments (UI/UX, backend) Adversary / Critic (Fable 5.1): Steps in at contract boundaries, recurring test failures, and pre-PR audits to catch vulnerabilities Script Layer (Jev): Handles mechanical tasks (opening files, CLI invocations) in 16ms without involving LLMs Launch the team via terminal: claude --teammates ux,backend,adversary Configure my Claude Code workspace for autonomous agent teams: In ⁠~/.claude/teams⁠, generate missing roles: set workers to ⁠Sonnet⁠ (⁠medium effort⁠) in separate ⁠git worktree⁠ branches, and the adversary to ⁠Fable⁠ In ⁠~/.claude/settings.json⁠, set ⁠CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1⁠ and lock the main session to ⁠effortLevel: high⁠ Initialize ⁠tasks.json⁠ with file-level locking for direct peer coordination In ⁠CLAUDE.md⁠, add a rule requiring an adversary review before opening a PR. Show configuration diffs before applying edits >$