High signal articles on AI, engineering, or whatever
“Essential reading on the dangers of over-contextualizing in AI systems.”
The context trap - AI is supercharging legacy leadership assumptions about context and control.
“The edit tool is the variable that matters most for coding agents.”
Improving 15 LLMs at coding in one afternoon. Only the harness changed.
“Analysis of where AI tools are headed in 2026.”
The race is to the top right, where AI agents work autonomously and have real control over your desktop.
“Data on how Claude Code usage grew from 25 mins to 45+ mins.”
Anthropic's study of its own API usage patterns measuring AI agent autonomy in practice.
“OpenAI's Harness team produced ~1,500 merged PRs with 3 engineers.”
5-month experiment: build and ship a real product with zero manually-written code.
“A shift toward file-system-based agent memory.”
Files that live alongside your AI agent. The agent can read these files just like it would when working with a codebase.
“Architectural shift from GUI to CLI-based AI agents.”
Moving away from the "VS Code clone sidebar" and towards CLI agents.
“Passive context beats active retrieval for AI coding agents.”
A compressed 8KB docs index embedded directly in AGENTS.md achieved a 100% pass rate, while skills maxed out at 79%.
“FDEs help build incrementally more valuable products from concrete use cases.”
What FDEs actually do and how to hire the right one for your team.
“Questions that tell you more than any Leetcode problem ever could.”
"You're in the middle of a refactor and the model says 8% context left before auto-compaction. What do you do?"
“How to make agents make consistent progress across multiple context windows.”
Creating a more effective harness for long-running agents, inspired by human engineers.
“MSR 2026 paper on the tradeoffs of AI-assisted coding.”
How Cursor AI increases short-term velocity and long-term complexity in open-source projects.
“Fascinating oral history of the AI paradigm shift.”
How LLMs upended the field of NLP in just a few years.
“Revolutionary approach to hallucination detection.”
LLM hallucinations aren't bugs - they're compression artifacts.
“80+ page survey of all prompting techniques.”
The most comprehensive study of prompting ever done - 1,500+ academic papers analyzed.
“The definitive guide to agent architecture from the team behind Claude.”
Best practices and patterns for building production AI agents.
“Multi-agent orchestration for terminal-based AI coding.”
Manage multiple AI terminal agents like Claude Code, Aider, Codex, OpenCode, and Amp.
“Required reading for anyone building with LLMs professionally.”
Why AI engineering is becoming the hottest role in tech.
“The canonical reference for understanding agent design patterns.”
Comprehensive overview of agent architectures and patterns.
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