What actually works when building sustainable AI companies?
With global AI investments projected to reach $1.8 trillion by 2030, the panel explored the fine line between innovation and short-term hype. Simon brought a data-driven perspective from his groundbreaking study of 100,000+ engineers, diving into what AI really means for developer productivity in today’s world.
Key insights from the session:
LLMs ≠ instant productivity – success requires solid measurement, experienced teams, and the right org structure.
No shortcut to scaling – automation, task quality, and rework metrics matter more than ever.
Remote ≠ unproductive – high performers thrive with the right systems; AI can help streamline communication and task structuring.
Reality check on “vibe coding” – without proper oversight, AI-generated code can become a bottleneck.
Together with Ant’s experience powering 40% of recent YC startups through Supabase, this panel was a goldmine for founders and technical leaders building for long-term impact, not just fast demos. We're inspired by Simon’s sharp take on what the AI revolution really demands—and we’re proud to have a leader who brings both academic depth and real-world experience to the table.
