Alvaro Cintas@dr_cintas
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There is a GitHub repo packed with over 100 NanoBanana detailed prompts and high-quality examples. It covers almost every use case: • Multi-image fusion • Achieving consistency • Blending styles And a lot more. Link below.

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#generative-art
pinned 12 OCT 24· backfill

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@dr_cintasBest 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@bnjI 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@whosjunaidd@dhruvtwt_Check it out: https://ai-sdk.dev/docs/agents@nicoalbanese10https://www.opensourceprojects.dev/post/1944990947273519485@GithubProjects@devnamipress already exists! http://opencode.ai@iannuttall@yescynfria@iannuttall