9 Observations from Building with AI Agents

Tomasz Tunguz shares practical insights from a year of building AI agent systems, covering model selection, fine-tuning strategies, code safety through static typing, multi-agent collaboration, tooling integration, cost-performance trade-offs, automated prompt optimization, and debugging approaches. Key takeaway: modern open-source models now deliver sufficient performance for workflow automation at a fraction of proprietary model costs.