Get your free personalized podcast brief

We scan new podcasts and send you the top 5 insights daily.

At OpenAI, engineers use AI to build ideas instantly. This inverts the traditional product model, shifting the PM's role from upfront planning to evaluating already-built prototypes and deciding which ones to ship, dramatically accelerating development.

Related Insights

The traditional workflow (Idea -> PRD -> Alignment) is outdated. Now, PMs first create a functional AI prototype. This visual, interactive artifact is then brought to engineers and scientists for debate, accelerating alignment and making the development process more creative and collaborative from the start.

Capable AI coding assistants allow PMs to build and test functional prototypes or "skills" in a single day. This changes the product development philosophy, prioritizing quick validation with users over creating detailed UI mockups and specifications upfront.

The traditional product management workflow (spec -> engineer build) is obsolete. The modern AI PM uses agentic tools to build, test, and iterate on the initial product, handing a working, validated prototype to engineering for productionalization.

The product manager's role is evolving beyond traditional spec documents and static screenshots. With AI coding assistants, PMs can now create functioning prototypes themselves. This allows for more dynamic, hands-on feedback from stakeholders and users much earlier in the development cycle.

Traditional product development (PRD-first) was designed to protect scarce engineering resources. With AI making software creation as easy as writing a document, teams can shift to a prototype-first approach, where ideas are built and tested immediately without agonizing over ROI.

In AI, low prototyping costs and customer uncertainty make the traditional research-first PM model obsolete. The new approach is to build a prototype quickly, show it to customers to discover possibilities, and then iterate based on their reactions, effectively building the solution before the problem is fully defined.

The product management workflow is evolving from documentation to creation. With AI tools lowering the barrier to build, PMs can now develop and share functional prototypes to communicate ideas and test assumptions, a much higher-fidelity approach than traditional written documents.

To keep pace with evolving AI capabilities, Floto.ai's engineers build initial prototypes based on a problem statement. The product manager then crafts the user experience around what's technologically possible, eliminating the PM as a bottleneck and ensuring the spec isn't outdated upon creation.

The product development cycle has shifted. Instead of writing a spec, Product Managers use AI coding tools like Bolt.new to build the initial working version of a product. They then hand this functional prototype to engineers for hardening, security, and scaling, dramatically accelerating the process.

Traditionally, implementation was expensive, so teams de-risked ideas with docs. With AI, building is cheap, so teams now create numerous prototypes first and then curate them. The process is now "build then decide," not "decide then build," with curation and taste becoming the most expensive part.