AI Radar
Other people's articles on AI agents, LLMs and AI-assisted development. I read what comes through and keep what's worth your time.
- · vercel.com
Agent responsibly
Learn how to responsibly use coding agents in development. Discover the risks of blindly deploying agent-generated code and strategies for safe deployment.
- · generativeai.pub
Your AGENTS.md is probably making your coding agent worse
Discover why a lengthy AGENTS.md file might hinder your coding agent's performance. Learn to optimize it by focusing on essential, project-specific details.
- · platform.claude.com
Reduce hallucinations
Learn how to minimize hallucinations in Claude, ensuring more accurate and trustworthy AI-driven solutions. Explore strategies like allowing 'I don't know' responses.
- · storybook.js.org
Storybook MCP for React
Learn how Storybook MCP enhances AI agents with component metadata, enabling them to reuse components, self-verify with tests, and generate UI faster.
- · generativeai.pub
NVIDIA Releases NemoClaw to Improve OpenClaw's Security
Learn about NVIDIA's NemoClaw, a security-focused runtime layer for OpenClaw that enhances the safety of autonomous agents by enforcing strict policies.
- · openai.com
Introducing GPT-5.4 mini and nano
Explore GPT-5.4 mini and nano, OpenAI's new small models designed for speed and efficiency. Learn about their capabilities in coding, reasoning, and tool use.
- · inceptionlabs.ai
Introducing Mercury 2 – Inception
Discover Mercury 2, Inception's new diffusion-based language model, offering >5x faster reasoning and real-time performance for production AI applications.
- · ejholmes.github.io
MCP is dead. Long live the CLI
This article argues that the Model Context Protocol (MCP) is unnecessary and that CLIs offer a superior, more practical approach for LLMs to interact with tools.
- · addyo.substack.com
My LLM coding workflow going into 2026
Discover a structured approach to AI-assisted coding for 2026. Learn how to plan, scope, and test with LLMs for efficient and accountable software development.
- · boristane.com
The Software Development Lifecycle Is Dead
AI agents have collapsed the traditional SDLC. The new workflow is a tight loop of intent, build, and observe, emphasizing context engineering and observability.