We did not start with a product. We started with 120 conversations: developers, agency leads, internal automation owners, anyone shipping agents for real.
The Consensus from the Field
One answer came back again and again. The hardest part was not building the agent. It was discovering, after the build, that the agent broke in a way the team could have named on day one if anyone had asked the right question.
83% Put Build-Then-Fix First
Eighty-three percent of them put build-then-fix at the top of the list. Not model quality, not cost, not prompt wrangling. The cost of committing to a build and meeting the failures only in production.
That number is why Pavamana AI Labs exists, and why the product runs in the design phase instead of after it. We built for the problem people actually have, not the one that was easy to tool for.