AI feels easy right up until a team tries to ship it. Patrick Belliveau of GambitCo joins Daniel to talk about the messy middle between a promising prototype and something a business can actually trust.

In this candid conversation, Daniel and Pat reflect on what changed between year one and year two of building an applied AI company. Pat explains why Gambit moved from fixed-price projects to retainer-based partnerships, how rapid prototyping helps teams stay close to the real problem, and why so many AI projects fail before they ever have a chance to deliver.

Their conversation also explores agent orchestration, human-in-the-loop validation, the limits of black-box tools, and the organizational fear that can quietly sabotage adoption. One of the clearest ideas in the episode is that getting AI to do something once is not the hard part ...