The Golden Rules of Agent-First Product Engineering

Key Takeaways

• Agents must support every user action via API tools.
• Expose high-level abstractions like SQL to simplify agent reasoning.
• Front-load universal context to reduce token usage and improve performance.
• Write skills as flexible guidelines, not rigid step-by-step manuals.
• Treat agents as real users, employing dogfooding and trace reviews.

Pulse Analysis

The rise of conversational AI has shifted product design from button‑click interfaces to agent‑first experiences. Companies that embed agents as a core interaction layer can automate complex tasks—such as setting up A/B tests or querying analytics—without requiring users to navigate multiple screens. This paradigm shift demands that every user‑visible capability be exposed through well‑structured APIs, allowing agents to act with the same authority as a human operator. By generating OpenAPI specs and TypeScript validation schemas, PostHog demonstrates how a systematic pipeline can keep tool creation scalable while preserving product integrity.

Abstraction is another critical lever. Rather than exposing low‑level CRUD endpoints, offering agents a higher‑level language like SQL lets them reason more efficiently and reduces the number of calls needed to answer business questions. This approach not only cuts token consumption for large language models but also aligns with the mental model developers already use when analyzing data. The result is faster, more accurate responses that feel native to the product, a competitive edge as enterprises increasingly rely on AI to surface insights in real time.

Finally, treating agents as real users reshapes quality assurance. Traditional unit tests cannot capture the nondeterministic nature of LLM outputs, so teams must adopt practices such as headless dogfooding, manual trace reviews, and iterative evaluation loops. These methods surface subtle errors—like mis‑stated feature‑flag capabilities—that automated tests miss. By embedding this human‑in‑the‑loop mindset, product engineers can maintain trust, iterate safely, and ensure that AI agents enhance rather than hinder the user experience.