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.

Even with AI accelerating development, a PM's core role is managing what *isn't* being built. The ability to calculate Total Cost of Ownership (TCO) and strategically say "no" is more critical than ever, as even quickly-built features have long-term costs that displace other opportunities.

While AI coding tools empower PMs to build features, Descript found it's a low-leverage use of their time. The real value is using the dev environment to gain deep technical context, vet ideas, and have more productive conversations with engineers, rather than trying to ship production code themselves.

To avoid "innovation theater," front-load the financial viability assessment to the very first stage gate. By asking about margins and P&L impact upfront, companies can kill 80% of unworkable, buzzword-driven projects before investing significant time and emotional energy.

PMs can use AI agents connected to their codebase to explore technical feasibility and iterate on ideas. This serves as a 'digital tech lead,' saving immense time for senior engineers who were previously burdened with speculative 'how hard would it be?' questions from product managers.

Use a dedicated AI chat as a dynamic feature backlog. Continuously feed it new ideas and user feedback, prompting the AI to maintain a ranked table of features based on estimated build time and potential impact. This creates a low-friction system for choosing what to build next during focused work sprints.

Standard LLMs often validate ideas to be helpful. Implement a structured "viability gate" skill with clear evaluation criteria (e.g., problem clarity, competition) designed to explicitly recommend abandoning unpromising projects, saving valuable time and resources.

With tools that make building faster than ever, it's easier to fall into the "build trap" of shipping features without validating their value. This shifts the primary bottleneck from execution to strategy, making the product manager's core job of identifying the *right* problem to solve more crucial than ever.

Use a multi-step, orchestrated LLM skill to handle initial product tasks like market research, viability checks, architectural decisions, and repo setup. This accelerates the process from idea to first commit, especially for non-technical builders.