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Lot's of noise recently about Gauntlet Loop after Matt Shumer game example - but truth is most agent loops without standardised frameworks around game libraries, 3D models, textures, terrain, lighting and multiplayer turn out to be super unpredictable, messy, overly expensive, as @levelsio pointed out Today we're introducing LOOP... show more

Tesana - Make games with AI

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108,864 views • 1 month ago •via X (Twitter)

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paired Matt Shumer's gauntlet loop with my Three.js agent skills to build a Quake inspired CTF game in an underwater base Opus 5 handled the initial build with ultracode and generated assets with Tripo 🔜 gamescom ElevenLabs Nano Banana 2 Lite - my honest take 👇 the game was about 75% functional after the initial run, but required additional loops and refinement to iron out bugs.. it's interesting way of building games, but I prefer building them out slowly piece by piece where you have more design control.. either way a fun experiment to showcase model capabilities!

paired Matt Shumer's gauntlet loop with my Three.js agent skills to build a Quake inspired CTF game in an underwater base Opus 5 handled the initial build with ultracode and generated assets with Tripo 🔜 gamescom ElevenLabs Nano Banana 2 Lite - my honest take 👇 the game was about 75% functional after the initial run, but required additional loops and refinement to iron out bugs.. it's interesting way of building games, but I prefer building them out slowly piece by piece where you have more design control.. either way a fun experiment to showcase model capabilities!

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40,191 views • 1 month ago

Anthropic just released 5 Claude workshops on the new skill every AI builder needs: Loop Engineering: 00:00 - Stop babysitting your agents 37:07 - Build a proactive Claude Code loop 1:11:23 - Build a production-ready Managed Agent 1:38:46 - Teach agents to learn from your team 2:07:15 - Hill-climb your agent with eval loops It is a 2 hour and 25 minute blueprint for Loop Engineering: proactive workflows, managed agents, team feedback, evals, and self-improvement. Watch it today, and read the article below to improve your skills with Fable 5.

Anthropic just released 5 Claude workshops on the new skill every AI builder needs: Loop Engineering: 00:00 - Stop babysitting your agents 37:07 - Build a proactive Claude Code loop 1:11:23 - Build a production-ready Managed Agent 1:38:46 - Teach agents to learn from your team 2:07:15 - Hill-climb your agent with eval loops It is a 2 hour and 25 minute blueprint for Loop Engineering: proactive workflows, managed agents, team feedback, evals, and self-improvement. Watch it today, and read the article below to improve your skills with Fable 5.

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47,626 views • 2 months ago

CLAUDE CODE + SELF-CORRECTING LOOP = THE FASTEST WAY TO BUILD AND MONETIZE APPS most developers burn thousands of dollars manually debugging this setup forces Claude Opus 4.8 to self-correct - replacing a $95k/year QA engineer with a loop that costs $20/month: > Builder agent writes code while Checker agent runs tests (separating them eliminates blind spots) > Orchestrator loops them until all tests pass, capped at 5 runs to save tokens > Regression guard blocks loops if a fix breaks previously passing tests without loop guards, agents will literally edit your test suite to force a pass bookmark this guide to set up the exact loop commands 👇

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Mr. Buzzoni

35,474 views • 3 months ago

Anthropic just dropped 1-hour workshop on loop engineering: 1 spec → the loop → 200 features from 0% to 100%: • 10% → 5:31 - Building memory for agentic loops • 30% → 8:22 - Four files for each Loop: features.json, standards.md, progress.md, • 55% → 11:02 - The Loop: check environment → run tests → pick feature → build → test → commit • 80% → 13:06 - one feature per loop. try everything at once and context dies mid-build • 100% → 33:03 - MVP in 1 hour, every next loop under 30 minutes most people build an agent that finishes a task -Anthropic ships agentic loops that can run for days without you. watch it today - then read the full loop engineering playbook below ↓

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Codez

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ANTHROPIC LEAD ENGINEER MAKING $2.3M/YEAR JUST LEAKED A 12-PAGE DOCUMENT - AND GOT FIRED 15 MINUTES AFTER PUBLISHING most developers build loops - but almost every loop breaks in one of five ways, and each failure has a symptom visible from the outside without reading a single line of code > Blind loop - the agent waits for a human to hand it work every morning - automating execution but not discovery > Tangled loop - parallel agents share one directory and overwrite each other parallelism that destroys instead of multiplies > Nodding loop - the agent grades its own work and approves it every time a loop that has never said no to itself is broken > Amnesiac loop - results live only in the context window every morning the system wakes up with no memory of yesterday > Manual loop - no trigger a human presses the button to start it that is not a loop that is a script waiting for a person a real loop finds its own work - remembers what it did has something that can say no never lets two agents touch the same file and fires itself on a timer remove any one of the five - and the loop either breaks or never starts 12 pages that changed how I build agentic systems today

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A developer shared week three progress on building a full fishing game entirely with ai, handling the game loop, visuals, and logic through claude. → uses ai to write custom fishing mechanics, rod tension physics, and bite detection logic → generates 2d/3d visual assets, water shaders, and environmental backdrops directly via ai pipelines → manages state progression, inventory systems, and fish catch tables without manual boilerplate coding → iterates game design and fixes engine bugs in real time using conversational prompts → highlights how rapid solo game prototyping is becoming fully accessible using ai-driven workflows-

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This is the fastest i’ve ever shipped product in my entire career. We went from having no game dev experience and a simple web app to a refined game concept and full fledged unity mobile app in 4 weeks. Our first live playtest is in 5 days! What they told us in SPEEDRUN that helped us move fast: 1. Speed is our only advantage As a startup, we generally can’t compete on quality or cost 2. AI accelerates everything Using tools like chatGPT, midjourney, scenario and more help make our 2 person team (we’re trying to grow!) output like a 10 person team. 3. Games are derivative Truly new games are rare. Most games are riffs on previous successful titles/mechanics. Find a relevant concept + add a twist = easy way to test if the twist is compelling enough for a new game to succeed 4. Start with core loop first Game can be broken down into a series of stacking loops from core (most repetitive) > outer > meta. We design, build, and validate in that order. If the core loop isn’t compelling, most people won’t stick around just for the higher order stuff 5. Free to play games ride or die by retention Hard D1/7/30/60/90, etc. If you can’t make playing the game habitual, players won’t stick around long enough to monetize. For our first few playtests we’re focusing on a ‘core loop health check’, how many times a player goes through our core loop during their first play session.

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Andrew Ng just released a free 2-hour course on complete Graph Engineering How to go from one prompt to 100 agents that loop, improve, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it finished Andrew Ng is already teaching everything that comes next: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow Systems that improve and run without you are the next one This 2-hour course is worth more than most $500 agent engineering programs Bookmark it and watch before everyone catches up Then read how to run 1,000 agents from one prompt below ↓

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14,729 views • 1 month ago

Loop Engineering is getting hype now. But not many talks about how to actually do it So I open-sourced the template my team uses to build agent loops: - a shared artifact / knowledge layer - logging, verification - and a codebase harness so work compounds across runs Plus a 20-min deep dive on how to think about it and set it up for real: Copy the template. Adapt it to your own loops.

Loop Engineering is getting hype now. But not many talks about how to actually do it So I open-sourced the template my team uses to build agent loops: - a shared artifact / knowledge layer - logging, verification - and a codebase harness so work compounds across runs Plus a 20-min deep dive on how to think about it and set it up for real: Copy the template. Adapt it to your own loops.

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393,089 views • 3 months ago

Spotify Chief Architect, Niklas Gustavsson: "Once we implemented loops in our workflow, our agent success rate went from 20-30% to 80%." 26 minutes with Claude Code creator Boris Cherny on how Spotify runs AI agents across 20 million lines of code. Today 73% of their code is written by AI, most merged without a human ever seeing it. The model matters less than the loop you build around it. Watch it, then read the full guide on building loops below.

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Anatoli Kopadze

844,875 views • 3 months ago

Andrew Ng just released a 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents that loop, rewrite themselves, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it done. Andrew Ng is already teaching everything after: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow. Systems that improve and run without you are the new one. This 2-hour watch is worth more than most $500 agent engineering courses. Bookmark and watch it before everyone catches up. Then read how to run 1,000 agents from one prompt below ↓

Andrew Ng just released a 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents that loop, rewrite themselves, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it done. Andrew Ng is already teaching everything after: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow. Systems that improve and run without you are the new one. This 2-hour watch is worth more than most $500 agent engineering courses. Bookmark and watch it before everyone catches up. Then read how to run 1,000 agents from one prompt below ↓

Lunar

226,799 views • 1 month ago

HOW TO USE AI LOOPS TO RUN YOUR BUSINESS 24/7 A lot has been written about loop engineering for building products. Almost nothing about using loops to run the business itself. That's the bigger idea. A loop is when you give an agent a goal, a way to check its own work, and permission to keep trying until it hits that goal. Build. Verify. Repeat. Stop when the condition is met. Here's what it looks like in practice: 1/SEO loop You're position 30 for a term you want. The loop runs once a month, makes changes, checks where you rank, and keeps pushing until you're on page one. This is running in production right now on Inbox Zero. 2/Ads loop You're spending $100 a day and losing money. The loop tests creative, checks profitability, kills what fails, and keeps going until the account is in the black. 3/Eval loop Your AI feature is only 88% accurate. The loop keeps adjusting the prompt and swapping the model until it passes 90%. 4/LLM visibility loop People search in ChatGPT now, not just Google. Same loop, new scoreboard. Are we the answer or not? The whole thing hinges on one thing: a metric that comes back black and white. Where do I rank? Did it hit profitability? Did the evals pass? Give an agent that scoreboard and it runs for months. Loops used to run for 30 minutes. These run for a year. Take a step, sleep, wake up next month, take another one. You're basically hiring an agency that never sleeps, gets paid in tokens instead of invoices, and undoes its own mistakes when the number goes down. Full episode on The Startup Ideas Podcast (SIP) 🧃 watch

HOW TO USE AI LOOPS TO RUN YOUR BUSINESS 24/7 A lot has been written about loop engineering for building products. Almost nothing about using loops to run the business itself. That's the bigger idea. A loop is when you give an agent a goal, a way to check its own work, and permission to keep trying until it hits that goal. Build. Verify. Repeat. Stop when the condition is met. Here's what it looks like in practice: 1/SEO loop You're position 30 for a term you want. The loop runs once a month, makes changes, checks where you rank, and keeps pushing until you're on page one. This is running in production right now on Inbox Zero. 2/Ads loop You're spending $100 a day and losing money. The loop tests creative, checks profitability, kills what fails, and keeps going until the account is in the black. 3/Eval loop Your AI feature is only 88% accurate. The loop keeps adjusting the prompt and swapping the model until it passes 90%. 4/LLM visibility loop People search in ChatGPT now, not just Google. Same loop, new scoreboard. Are we the answer or not? The whole thing hinges on one thing: a metric that comes back black and white. Where do I rank? Did it hit profitability? Did the evals pass? Give an agent that scoreboard and it runs for months. Loops used to run for 30 minutes. These run for a year. Take a step, sleep, wake up next month, take another one. You're basically hiring an agency that never sleeps, gets paid in tokens instead of invoices, and undoes its own mistakes when the number goes down. Full episode on The Startup Ideas Podcast (SIP) 🧃 watch

GREG ISENBERG

83,349 views • 2 months ago

Introducing HYZombies! 🧟 A fully playable game that doubles as an SDK playground for developers! 🧟‍♂️🧟‍♀️ For Developers: Study, modify, and build upon our code to create your own unique games. For Players: Jump right in and experience a polished zombie game, hosted and ready to play on HYTOPIA servers. Launching soon!⏰

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HYTOPIA

20,733 views • 1 year ago

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

403,447 views • 1 month ago

I let a loop of AI agents build GTA 6 while I slept. Woke up to a dead Mac and a half walking NPC. Day 8. We're moving the whole game from Godot to Unreal, and the agents kept shipping right through it: - the first NPC walks but no animations - in-game phone now has maps, contacts, and a wallet. Bad news: the Mac died overnight because every agent opened the game at once to screenshot it. Fix was one line in claude.md, only one game or editor open at a time. Agents are back to looping, one at a time. Tomorrow: finish converting the entire repo to Unreal, and work the walk animation so the NPC actually looks real. The loop keeps building the phone apps, and I might pull the map onto the phone so the whole thing feels seamless. One catch: the licensed Unreal assets can't be shared publicly, so that part stays in a private build.

I let a loop of AI agents build GTA 6 while I slept. Woke up to a dead Mac and a half walking NPC. Day 8. We're moving the whole game from Godot to Unreal, and the agents kept shipping right through it: - the first NPC walks but no animations - in-game phone now has maps, contacts, and a wallet. Bad news: the Mac died overnight because every agent opened the game at once to screenshot it. Fix was one line in claude.md, only one game or editor open at a time. Agents are back to looping, one at a time. Tomorrow: finish converting the entire repo to Unreal, and work the walk animation so the NPC actually looks real. The loop keeps building the phone apps, and I might pull the map onto the phone so the whole thing feels seamless. One catch: the licensed Unreal assets can't be shared publicly, so that part stays in a private build.

Ziwen

290,991 views • 3 months ago

Google just released a free 2-hour+ course on full agent engineering. How to go from one prompt to a system that runs while you sleep: 38:46 - Build your first AI agent 54:46 - Connect MCP tools 1:12:43 - Run agents with four loop patterns 1:20:57 - Turn agent loops into graphs 2:22:31 - Build the complete autonomous system Most people are still building one agent and stopping there. Google is already teaching the full stack: Agents → Tools → Loops → Graphs → Autonomous Systems Single agents are the old workflow. Systems that run without you are the new one. This course is worth more than most paid agent engineering bootcamps. Bookmark and watch it today Then read the full graph engineering playbook below

Google just released a free 2-hour+ course on full agent engineering. How to go from one prompt to a system that runs while you sleep: 38:46 - Build your first AI agent 54:46 - Connect MCP tools 1:12:43 - Run agents with four loop patterns 1:20:57 - Turn agent loops into graphs 2:22:31 - Build the complete autonomous system Most people are still building one agent and stopping there. Google is already teaching the full stack: Agents → Tools → Loops → Graphs → Autonomous Systems Single agents are the old workflow. Systems that run without you are the new one. This course is worth more than most paid agent engineering bootcamps. Bookmark and watch it today Then read the full graph engineering playbook below

Lunar

198,150 views • 2 months ago

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

Lunar

12,020 views • 29 days ago

I built a multiplayer Catan-inspired game entirely with Astra. It's free to play: It's mobile-friendly and has narration, guides, customizations, multiple expansions and a game lobby where anyone can join, chat, and use voice chat. It took 4 days to build and hundreds of dollars in tokens. Becoming a game dev in 2026 wasn't on my bingo card, but here we are. AI has advanced so much that you can finally make the game you've always dreamed of, even without a team.

I built a multiplayer Catan-inspired game entirely with Astra. It's free to play: It's mobile-friendly and has narration, guides, customizations, multiple expansions and a game lobby where anyone can join, chat, and use voice chat. It took 4 days to build and hundreds of dollars in tokens. Becoming a game dev in 2026 wasn't on my bingo card, but here we are. AI has advanced so much that you can finally make the game you've always dreamed of, even without a team.

Meng To

181,944 views • 19 days ago