It’s been nearly a year since we launched Leaders of Code, a segment on the Stack Overflow Podcast where we curate candid, illuminating, and (dare we say) inspiring conversations between senior engineering leaders. An impressive roster of guests from organizations like Google, Cloudflare, GitLab, JPMorgan Chase, Morgan Stanley, and more joined members of our senior leadership team to compare notes on how they build high-performing teams, how they’re leveraging AI and other rapidly emerging tech, and how they drive innovation in their engineering organizations. To kick off 2026, we wanted to collect some overarching lessons and common themes that many of our guests touched on last year, from the importance of high-quality training data to why so many AI initiatives fizzle to what the trust/adoption gap tells us and how to bridge it. Read on for the most important insights we heard last year. Poor data quality undermines even the most sophisticated AI initiatives.…