A technically superior product can fail if its business model—pricing, deployment, and procurement process—doesn't align with market readiness. Go-to-market strategy is as critical to product-market fit as the technology itself, a lesson learned from a 2005 ad-tech venture that was too early with its cloud API model.
As AI makes building cheaper, the bottleneck shifts from engineering execution to product discovery and judgment. This could invert the traditional 1:5 PM-to-engineer ratio, creating a future where more product managers are needed per engineer to focus on co-creation, ideation, and defining what to build.
As AI collapses building costs, the CPO’s value shifts from managing teams to directly prototyping and testing. Judgment and taste become the new bottlenecks, requiring leaders to get deeply involved in product creation to maintain a coherent vision and keep pace with developer innovation.
The challenge of the AI era is not adopting tools, but unlearning old habits. Deeply embedded processes like sprints, detailed roadmaps, and estimation are based on the outdated assumption that building is the bottleneck. Overcoming this organizational inertia is the leader's primary focus.
To find PMs who are thoughtful and prepared, share interview questions beforehand. This shifts the evaluation from quick thinking under pressure to the candidate's ability to prepare, research, and structure their thoughts—skills more critical for the actual role.
Treat AI not just as a tool, but as a meta-tool that can teach you to improve your own usage. Regularly asking prompts like "How could I be using you better?" or "What questions should I be asking?" can reveal new capabilities and refine your prompting skills.
Successful products require a dedicated "Go-to-Market Triad" (Marketing, Sales, Product) working in parallel with the traditional Product Triad (PM, Design, Engineering). This ensures market positioning, distribution, and sales strategy are considered from day one, not after the product is built.