The ultimate vision for AI in product isn't just generating specs. It's creating a dynamic knowledge base where shipping a product feeds new data back into the system, continuously updating the company's strategic context and improving all future decisions.

By creating a central repository infused with company strategy and market data, AI tools can help junior PMs produce assets with the same contextual depth as a 20-year veteran, democratizing product intuition and standardizing quality across the team.

Dylan Field predicts that AI tools will blur the lines between design, engineering, and product management. Instead of siloed functions, teams will consist of 'product builders' who can contribute across domains but maintain a deep craft in one area. Design becomes even more critical in this new world.

The traditional, linear handoff from product spec to design to code is collapsing. Roles and stages are blurring, with interactive prototypes replacing static documents and the design file itself becoming the central place for the entire team to align and collaborate.

AI and cataloging tools have compressed the competitive research phase from days to minutes. This frees designers from tactical UI comparison and empowers them to focus on higher-level strategic work: crafting product narrative and system architecture, a role previously reserved for senior leadership.

AI tools are collapsing the traditional moats around design, engineering, and product. As PMs and engineers gain design capabilities, designers must reciprocate by learning to code and, more importantly, taking on strategic business responsibilities to maintain their value and influence.

As AI tools empower individuals to handle tasks across the entire product development lifecycle, traditional, siloed roles are merging. This fundamental shift challenges how tech professionals define their value and contribution, causing significant professional anxiety.

AI's rise means traditional product roles are merging. Instead of identifying as a PM or designer, focus on your core skills (e.g., visual aesthetics, systems thinking) and use AI to fill gaps. This 'builder' mindset, focused on creating end-to-end, is key for future relevance.

The traditional tasks of a product manager—writing specs, building plans, prototyping—are being automated by AI. The role will likely evolve into a hybrid "Experience Engineer" who combines product, design, and engineering skills to build experiences, or a highly commercial "GM" role with direct P&L responsibility.