Mike Bespalov@bbssppllvv
open on x ↗Mockdown is alive again. AI agents read markdown better than they read your mind. Draw a wireframe in ASCII, paste it into Claude Code, get a working page back. www.mockdown.design
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▶@michaelmicasso≡ 2
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@LiorOnAI
▶@DataChaz
@everyAnnouncing Paper Desktop + MCP
Now any agent can read or write with Paper
Paper is connected. To your code. To your agents. To your data. To your teammates.
Download Paper Desktop at http://paper.design@paper
@ctatedev
▶@bbssppllvv
@emilkowalskiI built http://markdown.new
Put http://markdown.new/ before any URL → get clean Markdown back.
Cloudflare's Markdown for Agents is great, but only works for enabled sites. http://markdown.new works for ANY website on the internet.
80% fewer tokens. Also converts PDFs, images, audio.
Free. No signup.
http://markdown.new@elbeyoglutool is live, show me what you cook: https://ascii.0xbalance.xyz/@0xLauge
@matsugfx
▶@TheAhmadOsman
▶@zkgoudan
▶@0xLauge
@ctatedev▶@bbssppllvv@emilkowalskiI built http://markdown.new
Put http://markdown.new/ before any URL → get clean Markdown back.
Cloudflare's Markdown for Agents is great, but only works for enabled sites. http://markdown.new works for ANY website on the internet.
80% fewer tokens. Also converts PDFs, images, audio.
Free. No signup.
http://markdown.new@elbeyoglutool is live, show me what you cook: https://ascii.0xbalance.xyz/@0xLauge@matsugfx▶@TheAhmadOsman▶@zkgoudan▶@0xLauge
▶@PaulSoltI'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):@johnrushxI 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_WorseyIntroducing Vibe SDK@rauchg
▶@ctatedev
▶@bnj
@chrstnerode≡ 11+11
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▶@iannuttall
@rohanpaul_ai