I built a prompt dependency graph that separates everything a component can reach from the smaller set that actually needs targeted evaluation.
A lightweight runtime layer that separates instructions, evidence, memory, and tool output before they reach the model
How AI has massively changed my day-to-day workflow
Most coding agents waste 70% of their context window on irrelevant code. A compiler would never do that. It resolves dependencies, discards unreachable code, and keeps only the interfaces where implementation isn’t needed. Coding agents do the opposite—and it’s costing them the exact thing a shrinking context budget can’t afford to lose.
A production incident, a 150-line static analyzer, and the case for treating prompt changes like schema migrations instead of string edits
Maximize your efficiency with Claude Code
Your prompt doesn't need to remember everything. It needs to remember what still matters.
Enterprise Document Intelligence [Vol.1 #7bis] - Tobi Lütke and Andrej Karpathy named the practice in 2025. For a single document, each brick emits typed pieces that converge on one LLM call. Corpus, conversation, and tool extensions are follow-up work
A practical framework to detect hidden prompt regressions before they silently break production systems
Without these, Claude might end up being confidently wrong.