Autoresearch applies to a lot more areas than ML, below is a short list of 20 applications areas for founders and builders: what other areas you think it applies to? https://t.co/yLOyfkXtEu https://t.co/FZt0o4pyA9
— Misbah Syed (@MisbahSy) Mar 10, 2026
Read about AlphaGo’s incredible impact over the past 10 years and our vision for the future: https://t.co/utLIKwSGqg
— Demis Hassabis (@demishassabis) Mar 10, 2026
What if you could optimize a model overnight without any ML experience? What if an AI agent runs hundreds of training experiments autonomously, keeping only the improvements? That is the idea behind autoresearch. Yes, the early results are small scale, GPT-2 speedups, a 0.8B https://t.co/MbkFEYgBbq
— Philipp Schmid (@_philschmid) Mar 10, 2026
Our GTM agent is easily the single most widely used and loved agent we’ve built internally The GTM agent has: - saved reps >40hrs per month, each - lead-to-qualified-opportunity conversion rate up 250% - 50% of reps use it daily and 86% use weekly Want to work on similar https://t.co/5j0xDJMh2a
— Brace (@BraceSproul) Mar 9, 2026
https://t.co/9WLIjS8Lrk
— LangChain (@LangChain) Mar 9, 2026
🚨 Holy shit.. Karpathy just open-sourced a repo that lets AI agents run their own ML research experiments autonomously. 630 lines of code. Single GPU. No human in the loop. Every dot in his graph is a full LLM training run that took 5 minutes, and the agent just keeps going, https://t.co/Aunm5NKja4 https://t.co/RsPSgaR5uL
— Alex Prompter (@alex_prompter) Mar 9, 2026
What this means for non-developers: Claude Code now automatically reviews code changes before they go live. When someone submits new code, a team of AI agents checks it for bugs. The business application: automated quality control. Imagine this same concept applied to: → https://t.co/VIZjDH4fTn
— Corey Ganim (@coreyganim) Mar 9, 2026
