Research Methods
10 articles
A Starter Kit for the Economist’s First Week in Claude Code
A small set of copyable files that gives our second Claude Code session everything the first one forgot: seven files, installed in about ten minutes.
A Pre-Analysis Plan for Your Coding Agent
A three-layer architecture, rule, gate, and verification, for keeping an AI coding agent disciplined, and why trained priors beat a system prompt.
What Agents Actually Do (And What They Don't)
An agent is a specification-bounded process. Its output quality depends on prompt precision and project context, not hidden model capabilities.
What We Mistake for AI Capability
AI output quality tracks specification precision, not model capability. A task with wide tolerance makes the model look smart.
Research Phases Need Different Prompts
Exploration, implementation, and documentation require different AI prompting strategies. Match the prompt to the phase.
The Verification Tax: Every AI Output Needs Checking
Every AI output needs checking. Building verification into the research workflow to catch fabricated citations and errors before they compound.
Context Window Budgeting: Treating Tokens as a Finite Resource
Treating an AI context window as a finite budget: when to spawn sub-agents, when to work directly, and how to keep a long session from degrading.
End-of-Session Hygiene: What to Capture Before Context Resets
What to capture before an AI context window resets, and how five minutes of end-of-session notes saves twenty minutes rebuilding context tomorrow.
Claude Charts Not Working? Fix AI Research Graphics
When Claude and ChatGPT get research figures wrong, structured Antigravity prompts produce the publication-quality graphics we need.
The Cold Start Problem: Why the First Five Minutes Matter Most
Why the first five minutes of an AI coding session matter most, and how a CLAUDE.md context file solves the cold-start problem before work begins.