There's always a gap between a great demo and a great product. Doubly true with AI agents. No wonder: the whole domain just appeared, keeps evolving at a crazy pace, and to make matters worse – the technology is fundamentally non-deterministic. At PostHog, we've spent the last year and a half building an agent for product research. Then rebuilding it once, twice, thrice, finally launching, and… rebuilding again. Don't go through this hell yourself. Instead, join me for this crash course on building an AI agent as a product. We'll get into easy mistakes (that we made), unobvious trends (that we're looking to ride), and business dilemmas (that the industry is facing).
Michael Matloka is a senior product engineer and team lead at PostHog. He leads the Signals team, building systems that turn analytics, session replay, and error tracking data into actionable product insights. An early PostHog engineer, he also founded and launched PostHog AI and has extensive experience shipping large scale data, analytics, and user facing product infrastructure.
