With the AI shift, almost everything about the industry feels like new ground. The entire market is debating model sizes, context windows, prompts — while the mainstream providers profit handsomely from the token-grinding companies building slop on top of their APIs. Almost nobody is talking about the boring engineering that decides whether an AI feature actually survives production.
After 15+ years shipping real software across IoT, telecom, real estate, and fintech, I'd seen this pattern before — different name, same mistake.
The moment it clicked
I watched a team I'd mentored years ago ship a polished, production-grade AI feature in under a month — because they already had TDD, CI/CD, and a clean domain model. A competitor down the street, with 3× the engineers, couldn't get theirs out of preview. Same tools. Same models. Different engineering maturity.
I started ioprodz in late 2025 to be the counter-voice: the one that says the boring engineering is the competitive advantage, and that a small team with the right practices outlasts a big team stacking tokens.
