#FreeCAD #feature PartDesign gets a parametric Defeaturing command! Removes... selected faces + rebuilds a clean solid based - no more manual workarounds for imported geometry cleanup. Quickly edit STEP files or remove features like tangentially propagated fillets or geometry lumpsshow more

Mesh simplification is one of the many new features... in the latest LiquiGen 1.1 release, which includes a complete surface post-processing pipeline with dozens of tunable parameters: - Mesh Simplification: reduces the triangle count of the generated mesh while preserving its overall shape - Smooth SDF: averages the surface to remove bumps and noise, with reshaping, depth limiting, and velocity/vorticity/density masks - Curvature Flow (MCF): geometry-aware smoothing that targets noise while preserving flat areas, thin sheets, and fine strands, with much better volume preservation than plain smoothing - Reshape: dilate/erode and open/close operations to grow/shrink the surface and fill or remove small features - Smooth Mesh: vertex smoothing with two algorithms — Bilateral (preserves sharp edges like wave crests and splashes) and Weighted Laplacian (aggressively flattens bulk surfaces while particle density protects droplets) - Snap to Colliders: pulls mesh vertices onto nearby collider surfaces so liquid sits flush against solids (e.g. water against the inside of a glass), with configurable distance, iterations, and margin - Clipping: remove solid faces at liquid/collider boundaries, and clip the mesh against connected primitives or imported meshes via a new 'Clipping geometry' input - Adaptive particle radius and a minimum-neighbors filter to mesh generation, helping fill holes, stabilize isolated particles temporally, and cull stray floating dropletsshow more

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0... is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:show more

Look closely at a roughly $109 million F-35B and... the remarkable feature is what you barely see, fastener heads, wide panel gaps or steps between sections. That apparent single shell contains more than 40,000 threaded fasteners and over 1,000 measured seams in between panels. Despite weighing up to 27 tons and measuring 15.6 m long with a 10.7 m wingspan, the F-35B has an estimated frontal radar cross section of just 0.001 m², roughly a metal golf ball once in the air. Even advanced airborne AESA fighter radars and ground based long range SAM engagement radars like the S400 system, typically cannot detect or lock it until within 25-40 km, making long range air-to-air or surface to air missiles extremely hard to employ against it. Radar does not see a “smooth”surface as we do. The aircraft’s shape redirects energy away, while low observable materials absorb part of it. But a single raised fastener head, open or uneven panel gap or small step becomes a new edge or cavity that creates a radar signature. It disrupts electrical currents across the surface and can scatter energy back which advanced radar can pick up. Composite skins are formed on precision tools that set the exterior contour, then drilled to fit the structure beneath. The fasteners are not hidden inside, countersunk heads pass through the skin, are set flush or recessed, measured, filled until the curve is restored, and measured again. Exact F-35 tolerance limits are not public, but the inspection tool repeats to better than 0.001 inch, about 25 micrometres. Seams are separately checked for gap and vertical mismatch, conductive gap fillers and low-observable coatings help stop those transitions becoming strong reflectors points. Fourth-generation fighters already used flush fasteners for reducing aero drag. The real fifth-generation leap is treating every minute seam, material change and removable panel as radar geometry, then reproducing that finish across a fleet. At sea, salt, moisture, fluids and panel removal make preserving it a permanent maintenance discipline. A stealth outline can be copied from a photograph. The real manufacturing capability is making tens of thousands of parts and panels behave like one electromagnetic surface and restoring it for decades. Source, Pacific Airshowshow more

HTML Artifacts are a big part of how I... work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:show more

Stanford researchers did it again. They just built the... agent-native version of Git. When an agent works on a longer task, the run builds up a lot of state. This includes files edited/created, a dev server, a database, installed packages, KV cache, etc. Say the agent is at step 10 and makes a mistake, maybe it misreads a traceback and rewrites a file that was actually fine. The tests start failing, and the run goes off track, although everything through step eight was correct. By default, the agent just tries to fix it, which creates more edits and tool calls. This burns more tokens and grows the context. The other options are a person stepping in to redirect it or restarting the whole run from step one. That's wasteful, because it pays for every model/tool call again and re-prefills the context. Moreover, since an agent's run is non-deterministic, it doesn't reproduce the same early steps anyway. The reason it's hard to just jump back exactly to a previous correct step and resume from there is that the trajectory is only a message log. It records what the agent said and which tools it called, but not the live state underneath. That state includes things like memory, open file handles, child processes, installed packages, /tmp, and KV cache. None of that is in the log. Git can version the files, but it doesn't snapshot the running process or the KV cache. Checking out step eight moves the files back, but the process is still sitting in step-ten memory with a cold cache. Shepherd is a runtime layer by Stanford that records the run as a trace of typed events rather than a flat log. Each agent-environment interaction becomes a commit, similar to Git, but it tracks the live run. Its commit includes the agent process and the filesystem together, copy-on-write, so a branch carries the actual state and not just the files. Going back to a previous step is then a single call that forks from that commit and continues from the exact state. The copy-on-write fork is roughly five times faster than docker commit, and because the prompt prefix through step eight is unchanged, the KV cache is reused over 95% on replay, so early steps aren't reprocessed again. Once the run can be forked, a meta-agent can sit on top and operate it. It watches the trace and reverts as soon as it looks wrong, before the bad write is committed. In practice, it's just Python calling fork, replay, and revert on the trace, rather than a separate control plane wired into the harness. Not everything is reversible though. Files and sandbox changes undo themselves, but a database write has no automatic undo, so it needs a matching undo step set up in advance. Something external, like a sent email or a real charge, can't be undone, so the supervisor's job there is to catch it before it fires. They tested this on a few public benchmarks. On CooperBench, where two agents work on the same codebase, adding a live supervisor took the pair-coding pass rate from 28.8% to 54.7%. It's still early and labeled alpha. The benefit mostly shows up when a run gets branched a lot over a heavy sandbox state, which is exactly where restarting wastes the most tokens and time. If Git was made to make file changes reversible, Shepherd is trying to do the same thing for a live agent run. Shepherd Repo: (don't forget to star it ⭐ ) That said, Shepherd reverts a bad step inside a run. The harness around it, the prompts, tools, and checks the supervisor relies on, still drifts across runs as models and dependencies change. Akshay wrote about making that harness repair itself, where a failing trace gets diagnosed, the fix is verified against the exact input that failed, and the failure is locked as a regression test so it can't recur. Read it below.show more

Aman has no training manual. Most properties are under... 55 rooms runs on staff hired for judgment, not procedure and is vetted one person at a time by a company that never built a system to replace that. More hotels doesn't mean a better hotel company. It means the company traded something for reach. Four Seasons runs 130 properties, Ritz-Carlton close behind, and both train every GM on the same playbook. The same system that turns one founder's vision into something 200 people can execute without ever meeting him. That's what a training manual is: a delegation tool. A way to remove the founder from every decision so the company can outgrow the size of his attention. Aman never built one. Its standard is applied one hire at a time, by people selected for judgment rather than procedure. This is where the math runs backwards on scale. Most Aman properties are under 55 rooms with staff-to-guest ratios between 4:1 and 6:1. A density of attention no 200-property group can afford, because it would mean thousands of individually vetted hires instead of thousands of manual-trained ones. Harvard Business School's case on Aman describes staff pushed toward "considerable initiative" rather than procedure, hired for attitude over hospitality-school credentials. A big group calls that a liability or a lawsuit waiting to happen at scale. At Aman it's the whole product. I've stayed on both sides of this line. The branded properties are excellent, reliable. You can predict the shower pressure before you turn the tap. The Aman properties are the ones where something feels decided by a person, not configured by a department. But if the whole product lives inside one person's taste, it may not survive that person's absence and Aman has grown far past the scale where that was a small bet. Taste that lives in one person's judgment is either the deepest moat in hospitality or a risk no one is paying attention to. I don't think anyone, including the people inside Aman, knows for certain which one it is yet. What this proves about operating at a genuinely high standard: 1/ A training manual is proof a standard has been simplified enough to teach. That's an achievement. It's also a ceiling. 2/ Taste doesn't scale through documentation. It scales through proximity to the person who has it. Meaning a hard structural limit is built into the model. 3/ The real luxury is direct access to the person who decided what the room should feel like, with no system standing between you. Scale protects a company from its founder's limits. Aman is a bet they were never the problem.show more

After a few more hours, I think I've figured... out Opus 5. Opus 5 is trained to be more agentic than anything I've used. All Claude 5 models are like that. So what changes? The way to interact with Opus 5 or contextualize it won't work the same way as with other models. It loves exploring, so it doesn't need much guidance for it. Unique preferences, artifacts, and references compliment it well and enable cleaner and more effective exploration and execution. Now that it can explore more effectively on its own and understand intent better, the best thing to do is to get out of its way (e.g., it doesn't need examples of your preferences; a clear high-level description of it works best). It's truly agentic in that sense. A good first step to provide better context for Opus 5 is to distinguish between what's situational and what needs persistence. Regardless, persistent system prompts and CLAUDE.MD needs to stay lightweight. Remove memories and tool descriptions from these. CLAUDE.MD is also a great place to tap into progressive disclosure by linking command/skills to it. On the situational side, agent skills and auto-memory can leverage progressive disclosure and the improved ability of the model to use its external context/knowledge. Conflicting and unnecessary instructions, which are common at this layer (mainly to ensure reliability), are going to throw off this model easily. That's the biggest change I had to make. Simple, clean, and clear prompts and skills work best. I had to clean a lot of my skills and system prompts. The way I prompt remains the same (usually clear and well-scoped). MCP tool descriptions are also more descriptive and have been deduped from the system prompt. Anthropic released a guide on the new rules for context engineering, which was helpful here. I started to test the recommendations and created a little artifact with the things that worked along the way. This might feel like a lot of work. Believe me, it has been frustrating. But I think we can expect future frontier models to become more agentic and smarter at figuring out the right context/gaps. The best thing to do is to prepare for that now. Boris Cherny mentioned that Opus 5 is their least prompt-injectable model yet. I am not sure if that was something they intentionally trained for or if it emerged based on how it was trained, which is to be extremely agentic in nature and more direct in execution.show more

Dune analytics MCP.. Claude becomes your on chain SQL... analyst.. No dashboard has every query you'll ever need. dune does but writing SQL is a skill, and most of you would skip it.. i know this MCP fixes that. Claude writes the query, runs it on dune, and explains what the data actually means. with this MCP wired in, you don't need to know SQL. you describe what you want in plain english and Claude does the rest. like "Claude, which wallets bought $RAVE in last few weeks and still hold?" "Claude, show me the top 50 ETH wallets by stablecoin inflows last 7 days." "Claude, what's the median gas paid by ARB users in the last 24h?" Questions no dashboard can answer. one prompt away.. Setup (3 minutes) ▫️Step 1: grab a free dune API key → ▫️Step 2: add this to ~/.claude/settings.json or .mcp.json: { "mcpServers": { "dune": { "command": "npx", "args": ["-y", "dune-analytics-mcp"], "env": { "DUNE_API_KEY": "your-key-here" } } } } ▫️Step 3: restart claude. you'll see the dune tool load in your tool menu. that's it. you now have onchain SQL on tap. How to actually use it: 3 prompts i use: 1) Smart money watchlist: "claude, pull the top 20 wallets by realized pnl on $TOKEN in the last 30 days. show me which ones are still holding." gives you a clean leaderboard of who's actually winning on that token. add them to your etherscan watchlist. 2) accumulation vs distribution "claude, compare net inflows vs outflows for $TOKEN across all CEX wallets in the last 14 days." if whales are moving off exchanges → accumulation. onto exchanges → distribution. you see the rotation before the candle. 3) narrative heat check "claude, which 10 tokens saw the biggest % increase in unique new holders this week?" finds where fresh money is flowing. before this MCP i'd either, pay for a pro dune account + write queries manually, or look at someone else's dashboard and hope it answers my question… now claude writes it for me, in seconds, custom to my thesis. no dashboard in existence beats that. free tier covers most of what you need. upgrade if you're querying heavy. ( built a quick $RAVE post mortem dashboard using a prompt as shown in the video ) MORE SUCH USEFUL MCP for traders below.. 👇show more

✨ I open sourced my first Chrome extension 🚀... SuperLevels I vibe coded it to replace all my Chrome extensions that are increasingly being bought up by spyware and malware companies who sell your data or worse hack your accounts and steal your stuff/money/data, which I'd call one of the top security risks right now For example: Chrome extensions can read your cookies or localStorage data, including session tokens, then login to your web or email accounts and hack you, they can inject code into any site to pull data form any site you browse, then break into your crypto accounts, drain your wallets, and selling your browsing history to ad companies, but that'd actually be the most favorable thing to happen of all these! Chrome extensions are just very very very unsafe So I coded my own, that I can trust because I made it, and I can read the source code: my extension is called 🚀SuperLevels and has all the features that the Chrome extensions I used to use have but all built into one safe one The cool thing is it's 100% open source and free, and you can audit the code first with AI yourself before installing it, and then if you do install it, customize it to your liking again with AI It has these features that improve my daily workflow while browsing the web: 🚮 Tab Cleaner Automatically closes inactive tabs after a configurable timeout (default: 5 minutes). Set excluded hosts to keep important tabs alive. View and re-open recently closed tabs. 🍪 Cookie Editor Full cookie manager for the current site. View, edit, add, and delete cookies. Export cookies as JSON. Expand any cookie to see and modify all fields including domain, path, SameSite, secure, and httpOnly flags. 🔀 Redirect Tracer See every redirect hop your browser took to reach the current page. Shows status codes (301, 302, 307, etc.) with a visual chain. Copy the full redirect chain to clipboard. 🌙 Dark Mode Instant dark mode for any website using CSS filter inversion. Adjustable brightness. Toggle per-site or globally. Images and videos are automatically re-inverted so they look normal. 𝕏 X Dim Mode Custom dim theme for X/Twitter with 7 color palettes: Dim, Slate, Jade, Plum, Dusk, Ember, or a custom hue. Live preview in the popup. ⚡ JS Toggle Disable JavaScript per-site with one click. Useful for debugging, reading articles without popups, or testing progressive enhancement. Page reloads automatically. 🚫 GDPR Cookie Consent Dismisser Auto-hides and auto-clicks cookie consent banners. Supports OneTrust, CookieBot, Didomi, Quantcast, GDPR plugins, and dozens more frameworks. Toggle off if a site breaks. 🎨 Live CSS Editor Write custom CSS for any website, applied in real-time as you type. Saved per-domain. Supports tab key for indentation. 📺 YouTube Unhook Removes YouTube distractions: no homepage feed, no sidebar suggestions, no end screen overlays, no Shorts. Search still works — just no algorithmic recommendations. 🎵 Music Recognizer Shazam-like music identification for any tab. Captures 10 seconds of audio and identifies the song via ACRCloud (free signup, bring your own API key). Results link to YouTube. History of recognized songs. 🖼 Picture-in-Picture Pop the largest video on the current tab into a floating PiP window with one click. 🗺 Google Maps Links Re-adds clickable Maps links and map preview cards to Google Search results. 🖼 View Image Adds a "View Image" button back to Google Images, linking directly to the full-size original image. {} JSON Formatter Auto-detects pure JSON response pages and formats them with syntax highlighting, collapsible sections, and a dark theme. Copy or view raw with one click. Never triggers on regular HTML pages.show more

I've bought over 30 RV & MH parks in... the last 5 years. Lately? 2 per month. Want our playbook? Here ya go: How to buy a small, off-market mobile home or RV park that can 2x your money in 1-2 years, in 5 steps: 1. Pick a city in a red state. The two biggest factors: Crime & unemployment rates Crime: CrimeGrade . org Unemployment: SimpleMaps . com Cities with 3k - 30k people are best. This is the sweet spot for enough population & not to much competition. You want parks with almost no web presence & little to no reviews. A DG nearby is great. Walmart is better. But remember, “if no DG, it ain’t for me.” If there's a Whole Foods you ain't getting a good deal, I promise. Growth rate is good too, but #3 to the two above. Don't worry about the path of progress as much as other asset classes might. 2. Find the leads Get on Google Maps and search "mobile home park" in your target area(s). Avoid NY & CA (not landlord friendly). Make a Google sheet of the leads & use Loom to record your screen. Spend 30 mins doing this. OR, use something like Outscraper to do it for you. Be warned though, that if you don’t do this yourself the scraped results may not be as accurate. If you’re targeting a smaller geographical area I would do it by hand. If a whole state, use software. You’re looking for phone numbers. Use SearchBug . com to see if cell or landline for pennies. Or Phone Validator Go to Upwork and hire a virtual assistant to keep doing this for you, assuming you are targeting a larger area. They will cost around $4/hour. Use that same Loom link in your posting so applicants can see what the job will entail. When working, Loom it! You’ll never know when you’ll need it. When in doubt, Loom it out! More leads = better deals. 3. Call the leads Call up the owners and be real. Don't talk about any accolades. He doesn't care and it will only hurt you. You're a hard working country boy. You have a wife and kids (I hope you actually do). Are you a democrat? Don't tell the owner. (Sorry, democrats). Here's your general pitch: "I'm not a broker, I'm just looking for some good real estate and don't want to waste your time with a lowball offer. I can pay cash and close fast" Tell him about your wife and kids and what you do on the weekend. Most importantly, LISTEN. He's going to talk your ear off. This is a good sign. 4. Ask the right questions Ask him: How many pad sites? How many of those have a unit on them? How many of the units are RVs? (It's common for there to be a mix of MH/RV) Any single family homes on the property? Rent? Are the units park owned or tenant owned? (this is key) If a mix, what's the mix? Park-owned homes you have to maintain. AVOID AT ALL COSTS. Tenant-owned homes are key (lot rent). This means you only rent out the land and underground infrastructure. Depending on the state, sometimes you can sell back or give away the park-owned units to the tenants to absolve yourself of maintenance. Check the laws! You'll command half the rent but enjoy 90% less hassles. $250 - $350 is common lot rent in the midwest and SE. What's the occupancy and rental amount of each type of unit? Any outbuildings on the property? Septic or city sewer? If septic, conventional or aerobic? Sewer is best. Septic isn’t a deal breaker but you REALLY want to have it inspected. If there’s a lagoon or wastewater treatment plant I want you to throw that phone as far as you can, block their number and never speak of it again. Within city limits or no? City limits are best but rare. Outstanding municipal or zoning issues? How much is insurance? How much is landscaping? Asphalt, cement or dirt roads? Condition of the roads? Any drainage issues? Is there a manager? What do you pay them? (Best if no manager) Any pending litigation? What are total collections? How do people pay rent? How many are delinquent? What condition are the units in? Do you have a lien on the property? How long have you owned it? 30 or 50 amp? City maintained streets? City water or well? City is best. Keep in mind, that’s a lot of questions to ask. You have to feel it out, if he’s being standoffish, don’t keep pushing, just call back. This isn’t a used car lot, this is a relationship you’re trying to build. Don’t try and close on this first call. The key question: "If we were to make a deal, what's a ballpark offer you'd expect?" NEVER anchor him with the phrase "bottom dollar." Using the word "ballpark" keeps numbers loose. Whatever number he says, you want to pause and hem and haw over it. Embrace the silence and awkwardness. Back to car sales, they call this the “silent walkaround” when valuing a trade-in. Don’t say a thing about the asset, but point out the flaws with your body language. Touch the dents and scratches as you pause. Do the phone version of this. Tell him you'll get back to him tomorrow. Thank him profusely for his time and congratulate him on the park he's built. 5. Underwrite Before you do anything, check with the city to ensure the park is in good standing. Get that in writing. Don't trust the seller. Buyers are liars? So are sellers! Now's time to crunch numbers: What's a cap rate? The net operating income of the park divided by the price you'd like to pay. If you want your money back in 5 years and you're willing to pay up to $1m, you need $200k net profit per year. This is a 20% cap rate (20 cap). It's aggressive but possible on a smaller, rural park. (Yes, it really is, even in 2023) You probably won’t find a park that big in a small town for a good price, though. Start w/ a smaller park & higher cap rate. More room for error. $300k - $1m purchase price. First do some market research: Remember all your leads? Call competing parks as a potential tenant and ask what their lot rent is. Put this in a spreadsheet to get average lot rent & park-owned home rent. Keep in mind many of these parks will be undercharging as well. It's common to find parks charging $100 that could charge $250. When calculating cap rate BE CONSERVATIVE. Don't count on 100% of people staying if you increase rents, even though most will. Use $190 to be safe. Shoot for a park that will net $100k/year after rent increases that you pay no more than $600k for. It’s hard but not impossible. Or maybe you find a $30k/year park to get your feet wet. At least you're in the game. The more leads you scrape, the better chance of finding this park. Shoot for as much seller financing as you can get. Finance the rest with friends/family or savings. Once you find this park, get it under contract. Use a standard, simple real estate form that you can find on your state's real estate commission website. Texas' is called TREC. Yes, get it under contract before seeing it. Put down earnest and option money, and then go see it. Don't dress like a city slicker. Be personable and be willing to stay a while and BS. Drive a Tesla? Rent a truck. Drive a Prius? Just quit. Inspect the condition of the units, even if you aren't buying them Crappy units = more tenants willing to abandon them. And they aren't cheap to remove or move. Verify everything he said on the call If all looks good, start on the inspections: Septic or sewer lines SFH home inspection. Check with the city for outstanding issues or litigation Check for liens Wastewater treatment plant? If so, abandon ship! Electrical infrastructure Use professionals for all of these. Ask for: Rent rolls. They will likely be handwritten, that’s ok. Bank statements. Ask to speak to a few tenants to get their experience. Inspect their lease. Ask for vendor invoices or history of payments. Ask to speak to vendors. At some point before you close, list the property on Craigslist, FB Marketplace and Zillow. See how demand is for vacancies. If all still looks good, close on the property. 6. Post-closing strategy Meet all the tenants in the evening, they're at work during the day. Shake their hands. Tell them you want their experience to be amazing & you want them to stay Give them your number Ask what can be fixed If fixes are cheap, do them ASAP Tell that tenant once fixes are made. Address them by name. Clean up the park. Hire a tree guy to clear out low hanging branches. Do some simple landscaping. Find the tattletale in the park and get all the dirt. Who are the druggies and abusive husbands? Get them out ASAP if you can. They are much more expensive than the temporary vacancy hit. Fix potholes and drainage issues. ADD VALUE. Show you care. Wait a couple months before making any changes. Bring lot rents closer to market. Be upfront about this. They will understand if they've been getting a deal. Give people 2-3 more months' notice to give them time. Keep renting out vacancies at new price. This isn't self storage. You won't raise rents yearly. Don't be a jerk. Let them know what to expect. Once rents are raised and park is stabilized, you are 9-12 months in. Search Loopnet for the most active MHP brokers Hire the best one & pay what he or she commands. Sell on the market for 7-10% cap You've just 2-3x'ed your money. Rinse & repeat. I have done this over many times. Not all of my deals were bangers, but most were. THERE ARE STILL DEALS OUT THERE. There's a lot of fine print, and things can and will go wrong, so don't be dumb. Do your own research. Not everything can be explained in 1,700 words. I'm hosting a live, free webinar this Tuesday to cover this stuff in more detail. Including: 1. How to do everything above in more detail 2. How to ETHICALLY wholesale deals like these if you can't afford to buy them. 3. What hard questions to ask GPs of parks like these (like me) if you want to invest in them. 4. Live Q&A with me Comment below and me or my assistant Kelly will DM you the invite link. See you there! Or just follow me Chris Koerner for more RV/MHP content.show more

I just built my own wiki generator plugin for... my agents. My agents can now generate wikis for anything I ask. One of my favorite wikis is called PaperWiki. This is a great example of what Andrej Karpathy describes. It uses obsidian vaults to organize papers, retrieve LLM-generated summaries, diagrams, and other advanced views for paper exploration. When Obsidian UI is not enough, I use my own artifact generator inside my agent orchestrator (see clip for example). This allows my agents to build any kind of view or exploration feature that I need. The papers are all curated with automations and several rules/patterns I have manually built over the years. On the surface, this looks basic. But behind the scenes, there are advanced search capabilities, connections, metadata, derived data, and other interesting bits of information that are extremely useful for my research agents. This is mostly built for agents. The artifact preview is just a high-level way to validate and quickly assess the quality of the wiki, suggest improvements, and it's also great for research. I use tobi lutke's qmd for all search capabilities. Everything is markdown. The summaries and even the diagrams. The wiki updates on its own based on several automations I have optimized over the past couple of weeks. The wiki grows and self-improves based on several requirements important for my research use cases. This is as personalized as it gets. There is nothing like it out there. And I use my research expertise to continue improving it over time. This is a vanilla wiki. There are so many things I want to build on top of this. Different aggregations, views, artifacts, etc. All to help automate more of my research work and accelerate productivity. I think the biggest leverage here is how powerful this could be for discovery and experimentation. One of my goals is to use it to find deeper connections and insights that would otherwise elude the top human researchers and use those to generate interesting new hypotheses and research experiments. That way, my agents can use autoresearch to explore research ideas at the frontier. Stay tuned for more.show more

How to make money on your faceless youtube channel... with affiliate before ever getting monetized i made over $23,000 from my faceless channel before youtube ever paid me a cent and here's the embarrassing part i literally FORGOT to apply for monetization. didn't even notice until i hit 121k subscribers. someone in my comments asked how much adsense was paying me and i just sat there like... oh no. that's how little adsense mattered to what i was building. let me break down exactly what i was doing instead, the same way i'd explain it to a friend: so everyone starting youtube waits for the magic 1,000 subs + 4,000 watch hours/ 10m views before they think they're allowed to earn. that waiting is the biggest beginner mistake on the whole platform. you don't need youtube's permission to make money from youtube. you need three things: a channel getting views (any views), an affiliate offer that fits your audience, and a link in your description. i was running mine through Glitchy. they've got a whole range of offers costco memberships, walmart, sam's club, target gift card offers, sweepstakes, cash app style offers, freebie offers the kind of low-friction stuff where the viewer doesn't have to buy anything expensive. they just sign up or enter, and you get paid per action. that last part matters more than people realise. you're not asking your audience to spend $200. you're showing them something free or nearly free that actually interests them. that's why it converts even with a small channel. now here's the part everyone gets wrong: matching the offer to the niche. you can't just slap any offer on any channel. the offer has to feel like a natural next step from the video they just watched: - frugal living / budgeting channel? costco, walmart, sam's club offers. your viewers are literally there to save money. - finance or "money hacks" content? gift card offers, cash back, sweeps. same audience, same desire. - giveaway / luck-based content? sweepstakes offers. it IS the content. - retirement & 55+ money content? membership deals + gift cards. older audiences actually complete these. - food & grocery content? grocery store offers are a perfect fit. they're already thinking about shopping. the question i ask before picking any offer: "would the person watching this video actually want this?" if the answer isn't an obvious yes, wrong offer. keep looking. one more thing that changed everything for me and almost nobody does this: don't send people straight to the offer link. build a simple landing page first. a raw affiliate link looks like spam. a clean little page that says what the offer is, who it's for, and what to do next looks professional and it converts so much better it's not even close. same traffic, same offer, double or triple the results just because of trust. you can build one in like 20 minutes now, there's zero excuse. so my actual flow was: video = description link = landing page = offer. that's it. that's the machine that quietly made $23k while i wasn't even monetized. and the funny part? when i finally DID turn on monetization at 121k subs, adsense just stacked on top of everything. now both run at the same time. but the affiliate side is the one that taught me how to actually sell adsense never teaches you anything. if you're sitting at 300 subs waiting for youtube to pay you, you're waiting for the wrong thing. the description box under your very first video is already a business. use it. if you want me to break down how i pick offers or set up the landing pages, say so in the replies i'll make it my next post. and follow, because i share everything i learned doing this the slow way.show more

Impeccable 3.7 brings linting to design. Until now it... was a skill you asked for help. Now it's a design-system-aware feedback loop that runs while your agent builds, catching slop and design drift before they land. 🪝 Design hooks for Claude, Codex, and Cursor They run after every UI edit and quietly nudge your agent to fix slop and drift. The output isn't another wall of lint: it separates new findings from already-seen ones, flags clean scans, and asks the agent to use judgment. Fix real issues, leave intentional demos alone, save exceptions to config instead of littering your source. 🎨 Slop detection is now project-aware Reads your actual design system from DESIGN.md, your typography, palette, radius scale, and tokens, and flags drift from your system, not just generic AI slop: • this font isn't in your design system • this color is outside your documented palette • this radius doesn't match your rounded scale The same engine powers both the hooks and the CLI, and it's where we're investing next. 🖥️ Live Mode, ready for real projects Svelte/SvelteKit now preview variants as temporary framework components with live params, then accept cleanly back into your source component. Manual text edits got evidence / apply / discard routes, insertions preserve their anchors, and mapped lists and JSX slots clean up far more reliably. ⚡ Leaner core, sharper detector Rule-level evals across 3 providers and 4 niches cut guidance with no measurable lift and dropped examples that taught models bad patterns. The detector now skips hidden and screen-reader-only elements, understands OKLCH alpha and Sass-like inputs, and tightened checks for repeated kickers, oversized H1s, clipped overflow, and cramped padding. 🛠️ CLI caught up impeccable detect loads DESIGN.md by default, motion findings name the exact token or cubic-bezier instead of just "bounce," and impeccable ignores gives real CRUD for exceptions. Hooks and CLI share the same ignores. No split-brain config. Plus a much-improved interactive installer with hooks setup built in. Upgrade: npx impeccable install npm i -g impeccableshow more

🚨🚨CHARLIE KIRK CRIME SCENE PART 2 Candace Owens ELIZABETH... LANE The Dan Merrell Interview: Yesterday, as many of you saw, I posted after interviewing several people involved in the crime scene cleanup. I learned the cleanup was treated as a biohazard, which explained why the University handled it the way they did. I shared receipts and questioned whether Dan Merrell had even been there. I was quickly corrected by Sup Citizen who provided proof that Dan was indeed on site. Dan is the contractor whose interview sparked many conspiracy theories about who ordered the cleanup and how quickly it was done. This led to a lot of speculation about the speed of the work. Today I had an extensive interview with him. I found Dan to be honest, sincere, and clearly devastated by Charlie Kirk’s murder. Before getting into the details, here’s some context: During our conversation, Dan said a few things that I realized could cause him problems. I interrupted and asked, “Dan, we are on the record here — would you like me to keep that off the record?” He immediately said yes, and I respected that. Those comments may have materially changed the tone of this interview even more. For those who doubt my integrity, I have had private conversations with Buckley Carlson and others. I’ve even received recordings I could have posted, but I deleted them when asked. I don’t burn sources. In the interview, I asked Dan point blank: Did the FBI or the Governor call you or contact you in any way? He replied: “No.” Do you have direct knowledge that the FBI or Governor called anyone involved at the scene? He again said: "No." Dan then told me: “My words are being twisted so badly. The shit I’m enduring — my wife and I — this is insane.” He expressed deep regret for getting involved and especially for an emotional video he made right after the assassination. “You’ve probably seen it. I wish I hadn’t. It was such an emotional time.” (I have never seen the video) He described the constant harassment he and his family have faced. When I asked about the person who claimed the FBI and Governor ordered the rushed cleanup, Dan said, “I think he was really trying to make himself look like a big shot. He was a strange guy… a few things he did, I don’t know why.” (I would later come to the same conclusion after more interviews) Dan confirmed he was only a small part of the cleanup. The job was minor — he wasn’t even sure how much they billed. When I told him I had the invoice (roughly $6k), he verified it was accurate. He was contacted on September 14 — four days after the assassination — via text from a University employee. None of the messages mentioned the FBI or Governor. (Dan read me the text messages aloud) I asked if the FBI took any soil as evidence. He said no. An uncle of one of the crew members hauled the biohazard soil to an approved disposal site. (Dan did not witness this personally he described a 550? as hauling away the soil, again, he could not state as fact) When I asked if FBI or investigators were present while he worked, he said, “I’m not sure. There were some guys up there — security — but I don’t know for sure.” Dan is very aware his name is now tied to the “exploding mic” theory and other conspiracies. He feels his words have been distorted and manipulated. He asked me directly if he came across as misleading in the Jimmy Rex podcast. I told him no — he never stated as fact that the Governor or FBI ordered a rushed cleanup. I proceeded to tell him that people seem to draw their own conclusions. We proceeded to talk about how his words were being portrayed with certain podcasters. On Candace Owens, Dan said: “Candace has a way of… putting out a theory, then changing… you know…” (He agreed when I said she avoids painting herself into a corner.) During our discussion, Dan advised that Most people in his area believe Tyler Robinson did it. Dan’s personal view: “I don’t think a .30-06 did that damage. I just don’t think it’s possible.” We had a detailed discussion about the wound and the exact area where Charlie fell. Dan confirmed Charlie was under a pop-up tent on the grass — not on a raised platform. The paving work was done just outside the main blood-soaked area. (some people thought Charlie was on stage/platform and therefore the blood-soaked scene was exaggerated) He expressed amazement that someone could get into that shooting position without being noticed. We agreed on this point. We both agreed that this shot was straight-on, and a genuine point of concern. (How was he NOT spotted?) We mulled the possibilities. (I would get an answer later) I asked Dan if anyone had reached out to him, any of the current investigators, podcasters, journalists to ask him anything since he has come back into the focus of the investigation again. He replied, "All of these idiots saying things, you are the FIRST person to actually call me to verify any of this." At this point, I expressed shock, surely someone would have reached out to him, I repeated my question, he said adamantly "no, nobody has reached out, you are the first and only, I regret the entire thing." "We were coming together as a community for Charlie; this has been hard." This interview made one thing clear to me: Charlie was killed on September 10. The FBI had the scene for approximately three full days and eight hours before releasing it. The University was closed through at least that Sunday. (Although it appears some people did get access) Dan strikes me as an honest, hard-working man. Nothing about his answers felt rehearsed. He should not be harassed, accused, or made fun of. I’ve attached a clip of the ground crew cleaning the area. I cannot make out the words in the video, but this video seems is claimed to have been taken while the University was closed. It is not the greatest quality, but it seems genuine. I will continue releasing more interviews with witnesses, UVU police, and additional crew members. Today was long and productive. But the important thing to take away--I would learn in an interview later, that the FBI/Governor making any calls is based on a single source, who when pressed, would not show any evidence. My UVU Campus Police interview was abruptly cut short. I will detail this soon. My fear is that it will feed into the conspiracy theorists more, but I have to report what I am told accurately. No matter where this goes, I’m here for it. I appreciate respectful discourse even from those who disagree. When I make opinion posts, they are pretty clear. But when I do interview posts, I stick to the facts. Dan and I agreed to talk again. Feel Free to drop any questions you may want asked, I will let you know with a reply.show more

🚨 OPEN SOURCE PHYSICS: OPENAI JUST PROVED THE CONTINUUM... IS DEAD. THE GRAVITON IS A LIE. STRING THEORY IS A GHOST. PHYSICS IS A BRANCH OF GEOMETRY! 🚨 For 50 years, Quantum Gravity has been chasing a ghost. Academic elites have built multimillion-dollar simulators based on a fatal, mathematically absurd assumption: that gravity is a fundamental interaction mediated by a "magical" spin-2 particle called the graviton, flying through an empty, continuous void. Let's be real. Even schoolchildren don't believe in the continuous "space-time" fabric anymore! Believing in the infinite ℝ⁴ continuum is like believing in Santa Claus. OpenAI just shocked the world by announcing that their advanced AI found a negative result for the Navier-Stokes Millennium Prize problem, proving that continuous fluid dynamics breaks down into a singularity in finite time. Massive AI models (like OpenAI's o1) have also started hitting a wall, outputting negative or contradictory results for the Yang-Mills mass gap problem in ℝ⁴. Why? Because assuming the universe is an infinitely divisible, continuous void is a mathematical hallucination. But we didn’t need a 10,000-agent AI swarm to tell us this. Months before OpenAI’s announcement, I officially notified the Clay Mathematics Institute (CMI) that their Yang-Mills Mass Gap formulation on ℝ⁴ is inherently ill-posed and mathematically contradictory. I provided the exact strict mathematical proof showing that enforcing their conditions on an infinite void creates mutually exclusive geometric paradoxes. Forcing the rigid, discrete topology of the quantum vacuum into the infinite continuum of ℝ⁴ is as absurd as trying to shove an elephant into a microscopic lattice. What did CMI do with this strict mathematical proof? Did they read the math? No. They sent a boilerplate administrative rejection from a manager, telling me to go publish in a "Qualifying Outlet". And here is the ultimate bureaucratic joke: CMI rules demand you wait TWO FULL YEARS after publication before they even glance at it! But everyone knows the dirty secret of the academic cartel. If you submit a paradigm-shifting alternative theory, the coffee-drinking editors at journals like Physica D desk-reject it immediately without even looking at the math. It will never be peer-reviewed. Have you looked at modern physics papers lately? The list of co-authors is longer than the actual scientific content! Acknowledging that the ℝ⁴ continuum is dead destroys their life's work, terminates their grants, and turns their lifelong dissertations into worthless paper. They are numerologists defending a broken Standard Model with 19 arbitrary parameters. Even AI systems have been trained to aggressively protect these outdated dogmas! We are ending 300 years of fairy tales today. There is no chaos. There is only strict, beautiful geometry. The ancients were right. Here is the truth, explained simply for everyone: ➤ THE UNIVERSE IS A RIGID TOPOLOGICAL CRYSTAL. Space is not an empty, infinite void. It is a strictly compactified, constructible topological crystal. Matter is simply a topological defect-like a trapped knot of light-inside this crystal structure. ➤ GRAVITY IS JUST THE SURFACE TENSION OF SPACE. When you place two masses (defects) into this crystal, it creates structural stress. Think of two water droplets: they naturally merge into one larger droplet to minimize their surface tension. The exact same thing happens in the universe. The discrete vacuum lattice actively pushes masses together to minimize its algebraic boundary area. ➤ THE "GRAVITON" IS A LIE. Gravity is NOT a fundamental interaction mediated by a magical spin-2 particle. The graviton is entirely obsolete-it is an illusion, nothing more than a macroscopic thermodynamic drive, a phonon of the spatial lattice healing itself. I don't want their million dollars. I want humanity to have the truth. Words mean nothing. Here is the exact, parameter-free mathematics of the universe. Copy it. Test it. Prove it wrong: ■ 𝗧𝗵𝗲 𝗔𝗿𝗲𝗻𝗮: Space is NOT ℝ⁴. It is a compact 7-manifold: ℳ_tot = 𝕊⁴ × 𝕋³ ■ 𝗧𝗵𝗲 𝗖𝗿𝘆𝘀𝘁𝗮𝗹 𝗙𝗶𝗲𝗹𝗱: Generated by strict Pythagorean algebra, bounded by the √13 cascade wall: 𝕂 = ℚ(√2, √3, √5) ■ 𝗧𝗵𝗲 𝗕𝗼𝘂𝗻𝗱𝗮𝗿𝘆 𝗧𝗲𝗻𝘀𝗶𝗼𝗻 (𝗪𝗵𝘆 𝘁𝗵𝗶𝗻𝗴𝘀 𝗳𝗮𝗹𝗹): Mass is strictly proportional to confined topological nodes (N). E_tension(N) = σ · N^(2/3) Because 𝑓(𝑥) = 𝑥^(2/3) is strictly concave, the math forces sub-additivity when two masses exist: (N₁ + N₂)^(2/3) < N₁^(2/3) + N₂^(2/3) ⇒ E_merge < E_sep ■ 𝗧𝗵𝗲 𝗘𝗺𝗲𝗿𝗴𝗲𝗻𝘁 𝗙𝗼𝗿𝗰𝗲: The spatial gradient of this exact topological tension yields Newtonian gravity WITHOUT gravitons: F_top = -∇U(r) ∝ -σ(N₁N₂)/r² I am putting my money where my math is: I am offering a 5 Litecoin (LTC) bounty to anyone in the world who can mathematically destroy this theory. Name one academic who begs the world to tear their work apart? You can't. They hide their dogmas behind paywalls. My source code is OPEN. Don't take my word for it. Run the simulation! Watch the video. Watch the T(103,3) topological knots actually merge and radiate topological binding energy as the vacuum lattice heals[cite: 5, 10]. Read the proofs yourself: 🔗 🔗 If you cannot explain it simply, you are hiding behind bad math. God geometrizes. The universe is a macroscopic topological processor. 📐🌌💎 #Physics #QuantumMechanics #OpenAI #StringTheory #Astrophysics #Math #Geometryshow more

“More than that, we rejoice in our sufferings, knowing... that suffering produces endurance, and endurance produces character, and character produces hope.” - Romans 5:3-4 Last week a story went viral that says a difficult life isn’t worth living. I want to offer a different perspective: The Hard Road Is The Point. There’s a growing lie baked into modern culture that life is supposed to be smooth. Convenient. Perfect. That if things are difficult, something’s gone wrong. That suffering is a malfunction, not a feature. So people spend their lives optimizing for comfort. Avoiding friction and inconvenience. Looking for the shortcut, the hack, the easier path. And they miss the whole point. The beauty of a life well-lived isn’t found despite the struggle - it’s forged inside it. Character doesn’t grow in comfort. It grows under pressure, strain, stress and adversity. Gratitude doesn’t come from ease. It comes from having walked through something hard and making it to the other side. The ancient understanding - the one we’ve traded for comfort - is that suffering carries meaning. That the valley isn’t a detour. It is the journey. Truth is, when you strip away the hard parts, you don’t get a better life. You get a shallow one. Because the rough road isn’t a sign you’re doing it wrong. It might be the surest sign you’re doing it right. My son Iron Will has Down syndrome. He spent his earliest months in a walker just to build the strength to stand. Every step was a fight. Every inchstone and milestone was hard won. And watching him work, really work, for things that come effortlessly to other kids didn’t break my heart. It expanded it. Because what I saw wasn’t limitation. I saw determination unencumbered by societal expectations. I saw joy that doesn’t depend on easy. I saw a little boy who gets up every single time, grins, and goes again on his own terms, at his own pace. My brave little son didn’t teach me about suffering. He taught me what it looks like to pursue life fully - without fear, without shortcuts, and without ever being told what he can’t do. When we decide a life will be too hard before it begins - based on the inherent limitations of our mortal understanding - we end a story before it ever has the chance to be written. We will never tell Iron Will, or any of our children, that the hard road isn’t worth it. Because the greatest stories ever told involve suffering that produces endurance that produces character that produces hope. And hope changes everything. #TeamIronWill #DownSyndromeAdvocacy #IronWill #SayYesToPossibilityshow more

I just went through Anthropic’s threat report & woah!... This is genuinely the craziest article I’ve read all month. They documented hackers, governments, scammers and Chinese AI labs all using Claude in completely different ways. & some of the cases are insane. Here’s a TLDR; ⟣ A suspected Russian state linked group used Claude across phishing, intrusion, data theft and malware development, including rebuilding malware after security products detected it. According to the article, more than 20 organizations were targeted. ⟣ ShinyHunters-linked hackers used AI agents to scan 1.8M Android apps for exposed secrets and help run breaches across multiple companies. Anthropic says the agents did nearly all the work in some operations. ⟣ A China-based group built an automated exploit setup that could research vulnerabilities, build offensive tools and keep working against targets with little to no supervision. ⟣ Claude was also being used for government surveillance. One consultant used it to build Lakana 360 for Mali’s intelligence service, a system designed to monitor roughly 25M SIM cards across the country, including calls, messages, voice interception, watchlists and automated intelligence dossiers. The finished system runs locally, so even if anthropic bans the account, it won’t shut it down. ⟣ Anthropic found Claude being used across six weapons programs. One Yemen-based group used multiple Claude Code instances while working on guided rockets, ballistic missiles and a hypersonic-glide project. They actually tested one of the rockets, it failed, and they returned to Claude afterwards to diagnose the problem. ⟣ A Russia-based team was working on autonomous FPV kamikaze drones capable of identifying target classes, including humans, and approving lethal engagement without a human making the final call. ⟣ One China-linked project built electronic-warfare and air-defense suppression systems, then later changed its scenario to 12 targets in Taiwan, including radar sites, air bases and command infrastructure. ⟣ Anthropic found multiple influence operations too, including fake news networks, fake political accounts, propaganda operations and systems built to copy the writing style of real people. ⟣ Then there’s this fucking dating operation. More than 20 dating apps. > 4,700+ AI personas. > 25,000+ people talking to them. > Around 2.36M Claude messages in two weeks. And when someone wanted a video call or social follow, real gig workers could step in to make the fake profile look legit. ⟣ Then Anthropic gets into distillation. They say they’ve now caught campaigns from Alibaba, Moonshot, DeepSeek, Xiaomi, SenseTime and MiniMax. Alibaba alone allegedly ran 151M+ Claude exchanges between May and July, peaking at almost 3M per day. (I just wrote a piece on distillation before this) > Moonshot: 23M+. > DeepSeek: 12.1M+ in 14 days. And this is where it gets messy. Anthropic says Moonshot and DeepSeek were sometimes routing requests from their own users through Claude without telling them. Those requests included internal company documents, source code, live credentials, surveillance data and other sensitive information. ⟣ Some labs were also actively trying to extract Claude’s hidden reasoning. Anthropic says one lab tested 12,000+ different requests, each trying a different method, until it found techniques that worked and scaled them up. That’s the TLDR. Got me feeling like 👇show more

how to prompt undetectable ai shots while designing a... running scene, first think about these 3 basic questions: how does the camera move? what is it looking at? where does it stop? a good motion prompt is really just a timeline it needs to follow real-world physics, and it needs to carry story at the same time 1. start with the narrative goal of the shot camera movement is not just movement it is the storytelling so before writing the prompt, define what the shot is trying to do for example, in a 15-second one take, the goal could be: follow the female lead laterally while she runs, to build speed and tension then briefly reveal the people chasing her then let the camera hesitate for a moment and find her again that small “lose and recapture” moment adds spatial depth and makes the chase feel more intense 2. build a clear space for the camera to work in if the space is vague, the shot gets messy very fast i like breaking the scene into layers so the model knows where everything belongs foreground: passing objects, environmental motion main subject layer: the woman running midground: cafe tables, pedestrians, the people chasing her background: the vanishing point of the street, and the entrance to the pedestrian area once the space is clear, the camera has a stage to move through 3. describe motion like a physical process a good moving shot has to respect inertia if the movement feels weightless or too perfect, it instantly feels fake so instead of using broad words, describe a chain of actions the camera can actually perform what accelerates what slows down when it adjusts when it slightly overshoots when it catches itself again that little bit of imperfection is usually what makes it feel real 4. use focus as part of the storytelling in a one take, focus is one of the best ways to guide attention you can design moments where focus shifts with intention for example: focus briefly drifts from the chasers’ faces, passes beyond them, lands on the woman in the distance, then quickly pulls back again it feels like a small mistake, but that’s exactly why it works it simulates a camera operator re-evaluating the subject in the middle of a fast-moving shot that kind of temporary focus loss and recovery adds a lot of immediacy and documentary feeling 5. build the sound space with the camera sound should move with the shot when the camera turns toward the chasers, the woman’s breathing should fall deeper into the sound field, while the chasers’ footsteps and breathing move to the center when the camera finds the woman again, her breath becomes the main sound again that shift in audio perspective helps the scene feel much more immersive it’s not just about what we see it’s also about where we feel the scene from 6. use negative constraints to stop common ai mistakes this part matters a lot i usually add clear “don’ts” at the end to stop the model from breaking the shot for example: no cuts no teleporting zooms no sliding characters no body fusion no floating props the travel bag must keep believable weight and inertia these negative constraints act like guardrails they help keep the result inside a believable physical world for me, the core of a strong motion prompt is simple: organize space, camera, focus, action, and sound into one executable timeline that’s really the difference instead of prompting a vague feeling, you’re designing a physical process and that’s usually what helps ai generate a moving shot that feels coherent, grounded, and full of tensionshow more