Tagged: productivity
48 posts
From Autoresearch to Autoimprove: Generalizing the Agentic Experiment Loop
MetaClaw: Continual Meta-Learning for LLM Agents
Teaching Your AI Agent to Learn From Its Mistakes
Your AI coding agent makes the same mistakes over and over. What if it could learn from corrections, track which skills cause failures, and tell you whether it already fixed the problem? I built a closed-loop learning system for my coding agent, inspired by a meta-learning paper, and here's how it works.
Best Practices for Claude Code
CLAUDE.md Best Practices from Prompt Learning
How Claude remembers your project
How to Write a Good CLAUDE.md File
Writing a good CLAUDE.md
Quote
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Your CLAUDE.md Is Probably Too Long
Most CLAUDE.md files are bloated with instructions the model already knows, documentation meant for humans, and duplicate rules that compete for limited attention. Here's how to fix yours.
17% lower on comprehension tests
Anthropic published a study
highly-upvoted post on r/ClaudeAI
large-scale study with 234 students
Observing Without Doing: Pseudo-Apprenticeship Patterns in Student LLM Use
one post with 2,700+ upvotes
put it well on X
senior developer on r/learnprogramming
University of Saarland study on knowledge transfer in AI pair programming
Shadowing AI: What I Learned by Watching Agents Code
I've been learning new programming languages by watching AI coding agents work — like shadowing a colleague. The research says this should make me worse. Here's why I think it's more complicated than that.
1.7x more issues
Agentic Engineering Patterns
AI Doesn't Reduce Work - It Intensifies It
AI Agents and Code Review
As one practitioner put it
between 0.7% and 94%
CIO.com described it well
Faros AI study
HBR study from UC Berkeley
Making Coding Agents Reliable
METR randomized controlled trial
METR Study: AI Tools and Developer Speed
new paper from MIT and Washington University
Some Simple Economics of AGI (arXiv)
Some Simple Economics of AGI
Stack Overflow 2025 Developer Survey - AI Section
Stack Overflow 2025 survey
State of AI vs Human Code Generation Report
The 80% Problem in Agentic Coding
The AI Coding Trust Gap
The AI Productivity Paradox Research Report
The New Asymmetry: When Generation Outpaces Verification
Transitioning to the Verification Economy
Using Linters to Direct Agents
Why Your AI Coding Assistant Keeps Doing It Wrong
The Verification Bottleneck: Why AI's Real Cost Is Human Attention
AI scales execution to near-zero cost. But verifying that output stays biologically bounded. The bottleneck was never intelligence. It's human verification bandwidth.
Shrinking the Verification Gap: Practical Patterns for AI-Assisted Development
If AI scales execution and verification is the bottleneck, the winning move is to make verification cheaper. Here are the patterns that actually work.