The future of product management is a hybrid with UX design. PMs will be expected to be 'builders' who go beyond specs to create initial designs and functional prototypes, using AI tools to accelerate this process and enabling smaller, more agile teams.
Google differentiated Gemini Gems by focusing on personal and team productivity, correctly anticipating that a monetized "GPT store" model would struggle due to the lack of defensible IP in custom instructions, a strategy that has proven prescient.
A robust framework for measuring an AI agent's success requires a tiered approach. First, establish baseline quality (is it working correctly?). Then, measure user engagement (adoption, retention). Finally, connect these to top-line business impact (revenue, savings).
When hiring AI PMs, prioritize "grit" over direct experience. A top candidate stood out not with AI credentials, but by independently watching hours of TikTok videos to deeply understand the target user, demonstrating proactive, sleeves-rolled-up research.
Aspiring AI PMs shouldn't use the lack of an official AI project at their company as an excuse. The best way to gain experience is to proactively use widely available consumer AI tools like Claude, OpenAI, and Gemini to build side projects and demonstrate initiative.
Building reliable AI agents for finance, where accuracy is critical, requires moving beyond pure LLMs. Xero uses a hybrid system combining LLM-driven workflows with programmatic code and deep domain knowledge to ensure control and reliability that LLMs inherently lack.
Gemini Gems creator Lisa Huang identifies three indispensable custom AIs for PMs. A 'writing clone' masters your communication style, a 'strategy advisor' acts as a thought partner using company docs, and a 'research synthesizer' instantly distills user data.
The idea that AI agents will autonomously choose and use software is futuristic but overlooks a crucial step: user trust. Most businesses are still in the early stages of adopting AI and are not yet ready to delegate high-stakes tasks without significant human oversight.
An ex-PM from all three giants offers a masterclass on their distinct product cultures. Apple prioritizes product perfection above all, Meta is obsessed with data and rapid execution, and Google demands deep technical expertise from its product managers.