The societal change brought about by AI will be unprecedented. It’s not like the Industrial Revolution, or the invention of the camera, or personal computers, or the internet, although we desperately want it to be. Most of humanity isn’t ready for what’s coming.
An alternate proposal for Code Mode that replaces MCP servers and hosted execution with SKILL.md files and OpenAPI specifications.
Clawdbot gives LLMs arms and legs and unleashes their full potential.
LLMs haven’t killed programmers, and they aren’t useless either. Arguments at these extremes mostly miss the point. What matters is whether they can build things that work.
RLMs are a novel way to keep the context of the main agent loop small, eliminating context rot for long-context tasks while reducing costs.
ForecastBench continuously evaluates the performance of LLMs against an automatically generated, continuously updated set of forecasting questions.
Practical guidelines on context engineering, like having an append-only context, using response prefill to remove/force tools, setting up restorable compression strategies, and more.
A Model Context Protocol (MCP) server that lets LLMs run code safely in isolated Docker containers.
Notes on using OpenAI Agents SDK’s MCP support to integrate DiceDB MCP.
My experience in building an MCP server for DiceDB using the MCP Go SDK.
The author is clearly trying to channel his existential crisis and crippled ambitions into a blog post.
We need to democratize AI to save our democracies.
What can the Indian Government do about artificial intelligence?
An amateur policy analyst attempts to explain why (disregarding controversies) installing AI traffic cameras in Kerala was a bad idea.
What do the recent advancements in generative AI mean for APIs?
Someone tried to open pull requests to open source projects with AI-generated code.
A conversation with ChatGPT about ChatGPT. Who are you?