Sancho

HE BUILT AN AI EMPLOYEE THAT FINDS HOUSES WITHOUT POOLS. THEN SELLS THE OWNERS ONE. No cold calls. No door knocking. No manual lead lists. Just three things running together, day and night. OpenClaw scanning satellite imagery across entire neighborhoods, flagging every property with a lawn big enough for a pool — and no pool in it. Fable 5 doing the reasoning behind it — sorting good leads from bad ones, understanding lot size, layout, what's actually buildable. And a mini PC on his desk running the whole thing locally, nonstop. The system finds the house. Then renders a photorealistic image of that exact backyard — with a pool already in it. That render becomes the postcard. The postcard becomes the pitch. The craziest part? He never talks to a homeowner until they're already sold on what their backyard could look like. The AI found the lead, built the visual, and made the offer feel obvious before a human ever got involved. No cloud bill scaling with every scan. No subscription eating his margin. He paid once for the hardware. Every lead after that is free. While most pool companies are still buying lead lists and cold calling... This guy built a machine that finds the house, sells the dream, and closes the deal on autopilot.

@zodchiii Best line in here isn't about Fable 5 at all: don't spend your strongest model on questions a cheaper one handles fine. That's just good tooling discipline

@EXM7777 The "run it as a manager, not a coder" mindset is underrated. Curious how you handle the failure cases — do your subagents self-correct, or do you gate every loop with a manual checkpoint?

@Dexonfxf ty bro🫶

@Sancho_Wizard Great post!

NVIDIA JUST SHRUNK AN AI SUPERCOMPUTER DOWN TO THE SIZE OF A DECK OF CARDS. No data center. No cloud bill. No rack of GPUs humming in a server room. Just a small board you can hold in one hand. The Jetson Orin Nano Super. It runs real AI models. Locally. On-device. No internet required. The same class of workloads that used to need a $10,000 GPU cluster now fits on something the size of a Raspberry Pi. The craziest part? It costs less than most people's monthly cloud API bill. One-time purchase. Zero subscriptions. Zero data leaving the device. While big labs race to build bigger data centers... NVIDIA just quietly proved the opposite bet — the future of AI isn't a warehouse of servers. It's something that fits in your backpack. Robotics. Drones. Home labs. Edge devices that think for themselves. The compute war isn't just about who has the biggest model anymore. It's about who can run intelligence anywhere, for almost nothing.

@DimaHolovatyi Yep. Nvidia CEO won't give bad advice

@Sancho_Wizard All in one, that’s crazy

A CHINESE STUDENT TURNED $0.90 INTO $408,292. AND SOMEONE REVERSE-ENGINEERED HIS ENTIRE BOT WITH FABLE 5. No leaked code. No insider access. Just screen recordings, public trades, and a model patient enough to reconstruct the logic. 53 trades. 100% win rate. A live BTC prediction market bot running in real time. Most people saw the numbers and moved on. One person saw a pattern worth decoding. They fed Fable 5 every visible data point — entry timing, position sizing, the exact moments it caught reversals before they happened. Fable 5 didn't just read the trades. It rebuilt the strategy behind them. The craziest part? What took the original student months of trial and error took the second person one afternoon with the right model asking the right questions. $0.90 into $408,292 wasn't the impressive part. The impressive part is that the edge didn't stay private for long. The next bot doesn't have to be invented from scratch anymore. It just has to be reverse-engineered by something smart enough to see the pattern first.

@Dexonfxf Indian tech enthusiasts and AI content are a match made in heaven. Nobody ships tutorials, threads, and hot takes faster than this crowd. 😅

THIS DEVICE ISN’T MADE FOR GAMING. IT’S MADE TO PRINT MONEY. A freelancer was spending over $800/month renting cloud GPUs. Every AI project cut into his profit. Then hardware got small enough to fit in his pocket. Now he can build, test and run AI agents almost anywhere. The winners in AI won’t be the people with the biggest offices. They’ll be the people carrying the smartest hardware. AI is becoming portable. And that’s a much bigger deal than most people realize.

@aiseomastery Exactly — this is just market dynamics playing out. Whoever offers the best performance for the lowest friction wins

@Sancho_Wizard Not betting everything on one model is solid advice regardless of how this rollout actually plays out.

FABLE 5 IS BACK. AND IT'S ABOUT TO DISAPPOINT EVERYONE WHO WAITED. Two weeks of hype. Two weeks of "the best model is coming home." Here's what you're actually getting. A new safety filter tighter than anything they've shipped before. Normal coding and debugging now gets flagged as "risky." And when it trips? You don't even get Fable. Your request gets quietly rerouted to Opus 4.8 without telling you. It's only free through July 7th. Capped at half your weekly usage. Then you pay per message. So the model everyone waited on is now more restricted, faster to refuse, and paywalled in under a week. Here's the good news. You never needed it in the first place. Betting everything on one "godlike model" was always the wrong play. It gets gated. Throttled. Pulled the moment it's actually good. The real move? A council of models working together. No single point of failure. No company can throttle your whole workflow overnight. While everyone's refreshing their app waiting for Fable to unlock... The smart builders already have five models running instead of one. Nobody can gate a system that doesn't depend on a single model.

@Dexonfxf That's exactly what I was talking about

@Sancho_Wizard The real moat was never the model. It was knowing how to use it

ANTHROPIC RELEASED SONNET 5. THEN REVEALED SOMETHING WILDER 99% of their engineers run swarms of 300+ agents. Not assistants. Self-improving agents. Hundreds per engineer. And Sonnet 5 now matches Opus 4.8 — for a fraction of the cost. Here's the part nobody's talking about. Code can check itself. Tests pass or fail. Green checkmark or red. The model verifies its own output for free. Now ask yourself: Did the reconciliation actually balance? Would this decision survive a regulator reading it back to you? No green checkmark for either. In code, the verifier is free. Everywhere else — the verifier IS the build. So while everyone races to copy the agent swarm... The real winners already built the grader. Your evals. Your benchmarks. That's the entire moat. Everyone else is just running agents with no way to know if they're right.

@eng_khairallah1 Curious how this holds up over a longer session first response feeling different is easy, staying consistent after 50 turns is the actual test.

this is f*cking gold Andrej Karpathy joined Anthropic five weeks ago. A friend on his team just showed me the exact LOOPS.md file he actually uses. I dropped it into my setup. The very first response was different. Not slightly different. Completely different. Claude stopped giving generic answers and started working exactly the way I think. You don't talk to the model anymore. You build the system that talks to the model for you. Bookmark it before it gets lost in your feed. Read it now, then check the article below.

@kepochnik Solid breakdown — the dreaming sequence feature alone is worth the watch.

AI builder: "Downloading Hermes and not using these features is like buying a Lambo and keeping it at 10mph." in 23 minutes, Jack breaks down every Hermes feature most people never touch worth more than a $500 AI automation course here's what he covers: > a memory system that recalls exactly what you said on any specific day > a "dreaming sequence" that plans your day before you wake up > running multiple research tasks in the background, simultaneously > connecting Hermes to your meetings, emails, and notes so it never forgets anything most people use Hermes like a basic chatbot the ones getting real value built it into a full personal operating system i wrote a guide on how to integrate Hermes Agent with Obsidian 👇

@DimaHolovatyi I hope so 😶

@Sancho_Wizard Exciting! Gaming industry is changing

ROCKSTAR OPENED GTA 6 PREORDERS AND MADE HUNDREDS OF MILLIONS IN A DAY. The internet lost its mind. Trailers. Countdowns. Sold-out editions. Everyone was watching the same thing at the same time. But while millions of people were busy preordering a game... One solo creator was quietly building on top of the hype. No code. No face. No team. He didn't make the game. He made the content around it. Every leak, every trailer breakdown, every "GTA 6 vs reality" comparison — generated, edited, and posted automatically. Claude wrote the scripts. The system did the rest. While Rockstar spent years and hundreds of millions building one product... This guy spent one weekend building a machine that prints off their marketing for free. The craziest part? He never spent a dollar on the game. He just rode the wave everyone else was paying to be part of. Rockstar made the hype. He monetized it. That's the difference between making the product... And owning the loop that feeds on it.

@DimaHolovatyi Honestly a smart use case. The fridge photo trick is genuinely clever.

She Opened Her Fridge... Then AI Did The Rest. She Couldn't Cook... So She Built An AI Agent That Became Her Personal Chef. For years, every dinner ended the same way. Burnt food. Missing ingredients. Recipes that looked nothing like the pictures. She spent hours scrolling through cooking videos, only to realize she didn't even have half the ingredients they used. So instead of learning hundreds of recipes... She built an AI agent. Every time she opened the fridge, she simply took a photo. That was enough. The AI recognized every ingredient, estimated quantities, and instantly built a recipe using only what she already had. But it didn't stop there. It remembered what meals she liked. Avoided ingredients she never finished. Adjusted recipes based on her fitness goals. Created shopping lists when supplies were running low. Even suggested healthier alternatives without changing the taste too much. The craziest part? The more she cooked, the smarter the AI became. After a few months, it knew her eating habits so well that it started recommending meals before she even asked. According to her, it feels less like using an app... And more like having a personal chef who knows exactly what's in your kitchen, what you enjoy eating, and what your body needs. In the video below, she shows how one AI agent turns a simple photo into personalized recipes, meal plans, and shopping lists in seconds. Most people search for recipes. She built an AI that creates them just for her. Like this post if you'd use an AI like this. Follow for more AI stories, side hustles, and opportunities almost nobody is talking about.

@0xMoysei Currently, construction workers and engineers seem to have better career prospects than those in IT😆

Met two guys making $1.8, $2.3 million a year. Both run engineering. Spotify's chief architect. 30 years writing code, then he stopped opening an IDE 2 months ago. Watch this interview before you write another line. Here's the part nobody clipped: their whole system is one loop. The agent writes, builds it in CI, a second model judges the result, and only clean code gets merged. No human in the loop. That loop merges 650 pull requests a month and cuts 90% of the work. Their co-CEO told investors the same week: the best developers haven't written a single line of code since December. The other guy didn't flinch. Said his team runs the exact same loop now. I watched the talk last night. Then I went looking for how the loop actually works. I've been firing one prompt at a time like it's 2023. The full loop engineering breakdown is below.

THIS ISN'T A NEURAL NETWORK. IT'S ONE PERSON'S BRAIN ON A SCREEN. Every dot is a thought. Every line is a connection between two of them. And it built itself. He didn't draw this map. He just kept writing — notes, ideas, fragments — and linking them as he went. Then one day he opened this view. Hundreds of nodes. Thousands of connections. A web that looked exactly like how memory actually works. No central plan. No folders. No structure forced from the top. Just like your real brain — meaning emerges from the connections, not the files. The craziest part? The more he added, the smarter the whole thing got. Old ideas suddenly linked to new ones he'd forgotten he had. Patterns appeared that he never consciously made. This is what a second brain actually looks like. Not a notes app. A model of how you think — that keeps thinking even when you're not looking. Most people store information. This guy is growing a mind.