To maximize leverage, reframe every SDLC component—docs, tests, review agents—as a way to 'prompt inject' non-functional requirements into the agent. This approach teases out expert knowledge from engineers' heads and makes it part of the automated system, guided by the agent's mistakes.

Instead of just executing known tasks, use AI to explore the feasibility of complex features. By asking "what's the best way to do this?", the AI provides a ranked list of technical approaches, complete with pros and cons, which helps to de-risk development.

With models like Fable 5 capable of running complex tasks for days, the limiting factor is no longer technology but human ambition. The critical new skill is "task imagination"—the ability to conceive of and delegate large-scale, long-horizon projects that fully leverage the model's autonomous capabilities.

With AI models now capable of running complex, multi-day tasks, the limiting factor is no longer technical capability but human imagination. Users need to recalibrate their thinking to conceive of projects at a scale and scope that fully leverage the AI's power, moving beyond simple, short-term requests.

Don't limit an AI agent to tasks you can already imagine. After providing full context on your work, ask it open-ended questions like, “How can you make my life easier?” This strategy of “hunting the unknown unknowns” allows the AI to suggest novel, high-value workflows you wouldn't have thought to request.

The key skill for an AI PM is knowing a model's current capabilities. This is built by intensely using the model and, crucially, asking it to introspect on its own unexpected behaviors to understand *why* it made a mistake, revealing gaps to fix.

Effective AI planning isn't a one-shot command. It's an iterative exploration to understand system limitations, edge cases, and what you actually want. Use the agent to generate explainers (e.g., on Whisper's failure modes) to eliminate blind spots before committing to a complex workflow.

A powerful but unintuitive AI development pattern is to give a model a vague goal and let it attempt a full implementation. This "throwaway" draft, with its mistakes and unexpected choices, provides crucial insights for writing a much more accurate plan for the final version.

Intuit PM Christine Zhu argues the biggest productivity unlock comes from using models like Fable 5 for high-leverage "impact work," like product strategy, not just clearing a backlog of small tasks. Treat the AI as a sparring partner for your hardest problems.