Posts

Anatomy of a Claude Code Setup

A visual guide to configuring Claude Code: what goes in your global config, what goes in the project, and how to keep personal settings out of git.

Is That Improvement Real? A visual guide to eval statistics

You changed the prompt and the score went up. Should you ship it? An interactive companion to Anthropic's eval guide that walks through variance, standard error, and paired comparisons on a concrete example — with less assumed stats background.

Tree of Thoughts: What happens when you let a model explore before committing

How treating reasoning as search — generating, evaluating, and pruning candidate thoughts — unlocked planning capabilities that CoT and ReAct couldn't reach.

Self-Refine: What happens when you let an LLM critique its own work

How a single model can generate, critique, and revise its own outputs — improving 5–40% across seven tasks without any training.

Replicating Reflexion: What happens when you actually run the code

A reimplementation of the Reflexion framework with modern models reveals that stronger models don't improve reflection — they make it worse.

Reflexion: What happens when an agent can learn from its own mistakes

The Reflexion paper added memory across attempts — letting agents reflect on failures in natural language and improve without retraining.

ReAct: How giving LLMs the ability to think and act changed everything

How the ReAct paper established the think-act-observe loop that powers every modern agent system.

Chain-of-Thought: The prompting trick that unlocked reasoning in language models

How a simple prompting technique unlocked multi-step reasoning in LLMs — and why it only works above a critical scale threshold.