Building with AI coding tools feels magical at first. You give Claude Code a PRD, start building, and features just keep coming. But after a while, something starts to go wrong — not because the model suddenly becomes useless, but because across sessions it quietly drifts from earlier decisions. One session chooses SQLite because the app is simple. A later session adds Celery workers for scheduled jobs. Another task starts doing concurrent writes. Each decision is reasonable when it is made. Together, they start creating contradictions that nobody explicitly chose. That’s the pattern I started thinking of as the Week Seven Wall: the point where AI-assisted coding stops feeling magical and starts accumulating architectural drift across sessions. This became personal while building with Claude Code. I realized I had almost no visibility into what the agent had decided or why. I was basically typing “yes” over and over while slowly losing control of my own architecture. At first, I thought this could be solved with a better CLAUDE.md, stronger prompts, or more rules. Those things help, but they don’t fully solve the problem. Many contradictions don’t come from forgetting a static instruction — they come from decisions made at different times, in different contexts, that only become problematic later. So I built Axiom Hub to test a fix. The idea is simple: store architectural decisions across sessions keep the rationale and context behind them flag contradictions when new decisions conflict with old ones let the human decide which path is…
Want more insights? Join Grow With Caliber - our career elevating newsletter and get our take on the future of work delivered weekly.
