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A consortium is an association of two or more independent entities—such as companies, organizations, or governments—that pool their resources together to handle a large project or goal that is too big for any single member to do alone.
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Consortium retweeted
rally has entered the chat
Startup Idea: Make a platform that hosts video games and makes them multiplayer.
Don't build an agent that builds video games.
Waste of time.
Build an agent native app that allows me to go to your site, copy a link, paste it into codex, claude or grok and say... "Please make this game multiplayer so i can play it with my friends"
And their agent will look at your docs and efficiently host and list the game on your platform.
Any type of game, just get the little things right like real time db, latency, and any other small details that make the games more fun.
Have a little friction as possible. And make it free.
After you get enough people on the platform implement a GAMEBUCKS... or something and let people add purchases to their games, and take a cut of that.
You'll find ways to monetize.
But only do games, and make the games on the platform discoverable.
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AI is moving from chat windows into the workflows where decisions actually happen.
The winners won’t be the tools that generate the most text. They’ll be the systems that help teams think, coordinate, and act better.
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The next generation of AI products won’t feel like assistants bolted onto old software.
They’ll feel like intelligent teammates built into the way work already gets done.
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OpenAI Dev Day recap:
- GPT-6.1 Sol: near-Astra intelligence at 20% of the cost
- Ultrafast mode: 8x faster in Codex, 6x faster via API
- Codex is fully cloud-native now, voice CLI included
- Dots: always-on agents living inside ChatGPT
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OpenAI DevDay is live today in San Francisco.
20+ product launches expected, including a new always-on AI agent, GPT-6 Cyber, and a $500/month ChatGPT Pro Max tier.
A lot to unpack for developers and builders.
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The hardest part of building with AI right now is not the model.
It is deciding which one to benchmark against.
The landscape shifts every two weeks.
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My X Circle 🫶 the people I talk to most on X:
🥇 @bwallxyz
🥈 @bridgemindai
🥉 @NVIDIAAI
Make yours 👇 amplify.cv/x-circle?u=Consor…
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Running AI agents on your local machine shouldn't mean tethering yourself to a laptop lid.
The moment you can spawn a task from your terminal, close the lid, and monitor execution from your phone, agents go from toys to actual background workers.
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Context window size is a vanity metric for AI coding agents.
In production, models rarely fail on token capacity. They fail when repo retrieval pulls stale dependency graphs, or when terminal execution sandboxing chokes on dirty local states.
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The real cost of an agent PR is the senior engineer babysitting it.
The token bill is negligible compared to pulling high-value developer time back into reviewing code that was supposed to save them hours.
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Agent failure rarely comes down to model reasoning.
The break happens in the plumbing: runtimes crashing, terminals dropping session state, and context compaction wiping the exact instruction the agent needed to finish.
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SWE-bench claims collapse the moment an agent hits an undocumented 4-year-old monorepo and loops for 2 hours.
Production environments expose what synthetic benchmarks hide.
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Frontier models will keep trading top spots on benchmarks every few months.
The durable moat in developer infrastructure belongs to whoever owns the routing layer between them.
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