Technical Debt

Hold

Techniques

Design and implementation compromises that make future change harder.

Why it's here

Placed in Hold: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.

Evidence (1)

4Martin Fowler·4/2/2026research
LLMs, cognitive debt, and verification in software development
Martin Fowler highlights a framework that separates system health into technical debt, cognitive debt, and intent debt, arguing that each limits a different aspect of software evolution. He also discusses research framing AI as a “System 3” in cognition, and notes that as coding agents reduce the cost of writing code, verification becomes the more valuable and difficult work.