5 articles in Architecture
Your lead time is not slow because of code review or approvals or sprint ceremonies. It is slow because three files do everything, four modules depend on each other in a circle, and every meaningful change has to pass through the same engineer who understands the wiring. Process is the symptom. The architecture is the disease.
Every new model release prompts the same question — is this the one that finally makes AI coding agents reliable? It's the wrong question. What keeps single-agent workflows from scaling to production is architectural, not about the model. Here's the pattern the teams shipping real code keep converging on.
Most teams treat engineering quality reactively — ship fast, catch problems in production, fix when it hurts. That cycle keeps you busy without making you better. Prevention, Detection, and Correction form a closed loop where each phase reduces the work the next must do.
AI coding agents don't understand your architecture — they pattern-match from your codebase. One boundary violation becomes a template that AI replicates hundreds of times. Clean Architecture went from best practice to survival requirement.
A new framework argues that coding agents need external "harnesses" — feedforward guides and feedback sensors — to produce reliable code. We agree. We also built one. Here's how theory maps to a production system, concept by concept.