🔖 Bookmark this post to start building with the updated Gemini Live model.
Google AI Developers@googleaidevs
open on x ↗🔖 Bookmark this post to start building with the updated Gemini Live model.
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@interjc
▶@DataChazBest Model Per Use-Case
Presentations - Gemini 2.5
Full-stack apps - GPT-5 Codex, Sonnet 4.5
Docs - Gemini 2.5, GPT-5 thinking
Videos - Sora 2
Images - Nano Banana
Coding - Sonnet 4.5, Grok Code Fast
Browser use - Sonnet 4.5
Doc Processing - Gemini Flash
Enterprise Search - Sonnet 4.5
Data analysis (complex) - Opus 4.1
Agentic workflows - Sonnet 4.5, Haiku 4.5@bindureddy
▶@prathamgrv
@everyA single place to browse, compare, and install Clawdbot skills by intent.
Built for fast discovery and practical use.
GitHub Repository:
https://github.com/VoltAgent/awesome-clawdbot-skills@GithubProjectsCheck it out:
https://ai-sdk.dev/docs/agents@nicoalbanese10
@PrajwalTomar_
@bbssppllvv@uAghazadae @Zai_org should work perfectly with http://eve.dev / http://ai-sdk.dev@rauchg
@Zai_org
▶@aidenybai
▶@ctatedev
▶@coderabbitai
@amilabsI've tried all ( 74 😵💫 ) AI Coding Agents & IDEs
[Rork, CodeRabbit, Anima, Zed, Factory, Cursor, Windsurf, Copilot, Lovable, Bolt, v0, Replit, MarsX, Canva, Devin, Github Spark, Vercel, Lindy, Warp, Figma, Cline, Vibe Coder & more]
The most complete list ever made (with demos & notes):@johnrushx
@Dr_Singularity
@GithubProjectsI took the @karpathy autoresearch loop and pointed it at markets.
25 AI agents debate macro, rates, commodities, sectors, and single stocks daily. Every recommendation scored against real outcomes. Worst agent by rolling Sharpe gets its prompt rewritten by the system. Keep or revert. Same loop, prompts are the weights, Sharpe is the loss function.
Trained the agents on 18 months of market data. 378 iterations. 54 prompt modifications, 16 survived.
The system learned which agents to trust using Darwinian weights — geopolitical, commodities, and the @BillAckman quality compounder rose to the top.
The agents even figured out their own portfolio manager was the weakest link before we did!
Deployed the trained agents. +22% in 173 days. Best pick: AVGO at $152, held for +128%.
The final prompts are evolutionary products — shaped by market feedback, not human intuition. Now running live with my own capital.
https://github.com/chrisworsey55/atlas-gic
Part hedge fund, part research experiment :)@Chris_Worsey
▶@evilrabbit_≡ 2
