Tokens
5 articles about tokens.
100M Tokens Tracked: 99.4% Were Input and Parallel Agents Make It Worse
After tracking 100M tokens, 99.4% were input tokens. Running parallel Claude Code agents multiplies the input cost problem. Here is how CLAUDE.md scoping helps.
Browser Automation: Accessibility Snapshots vs Screenshots - Saving Tokens by Skipping Pixels
Switching from screenshots to accessibility snapshots for browser automation saved us massive token costs. Here is why structured data beats pixel analysis for AI agents.
Embeddings vs Tokens - How AI Agent Memory Actually Works
Embeddings aren't tokens. They're dense vector representations that capture semantic meaning and power similarity search for AI agent memory retrieval.
The 1M Context Trap for Opus - More Context Makes the Model Lazier
The 1M token context window is a double-edged sword. You can fit more information, but the model gets lazier and less precise the more context it has to process.
Opus Token Burn Rate - Watching It Write, Delete, and Rewrite 200-Line Functions
Opus does not just burn tokens - it vaporizes them. The write-delete-rewrite cycle where Opus creates 200 lines, decides it does not like them, and starts over.