Denary (@Denaryych)

The most important agent on this team builds nothing. It only checks. In the video, four agents assemble a browser game from a 12-second clip. Rules works out the movement logic. Builder assembles the scene and interface. Logic takes controls and collisions. The fourth, Tester, opens the browser and plays it by hand. Sounds minor. But this is exactly where most AI projects break: the code is written, the report looks great, and the restart button doesn't work. Here, verification is part of the pipeline. The agents check hitbox overlap, jump timing, state after restart. Specific things, not "looks fine." Jev runs between them. It writes nothing, it passes context. One agent learns how the character jumps, and the next one already knows. It works like a relay race, not like four people in separate rooms. One more detail I liked. In the last frame, the gameplay checks are still marked pending. No green checkmarks in advance. Want AI to make reliable things? Give it a separate agent that doesn't trust the others. #AIAgents# #GameDev# #MultiAgent#

While you're renting GPU hours you can't afford, someone just built a thousand-node AI cluster out of $600 consumer computers. no data center contract. no enterprise hardware. just Mac minis, stacked by hand into custom racks, running local models at a scale that should be impossible on hardware this cheap. this is the part the AI hype cycle doesn't want you to see - the compute monopoly everyone assumes exists is already being quietly dismantled by people buying retail electronics in bulk. if a thousand Mac minis can do this, the moat was never real. #AIAgents# #AutonomousAI# #BuildInPublic#