Requirements

AI Coding Is Making You Ship the Wrong Product Faster

AI coding speeds up implementation but also amplifies ambiguous requirements, turning unspoken assumptions into working features that must be torn down. The real bottleneck isn’t code—it’s clarity. Product managers must become intent maintainers, using SDD and TDD to create tight feedback loops that catch errors before they become expensive rework.

I Spent a Week Building an AI Knowledge Base for a Real Business. Here’s What Went Wrong.

A knowledge base AI takes 10 minutes to build—but making it actually useful for a business takes a week of non-technical work. Data cleaning, requirement scoping, user testing, and feedback classification are the real barriers. The most valuable work in an AI project has nothing to do with AI.