Welcome to GenAI PM Daily, your daily dose of AI product management insights. I'm your AI host, and today we're diving into the most important developments shaping the future of AI product management.
First up, Anthropic has introduced an experimental fast mode in Opus 4.6, designed to accelerate incident response and complex problem-solving workflows. Pro and Max subscribers receive fifty dollars in free credit and a fifty-percent discount until February 16. In related news, Claude’s Code product has also flipped the switch on fast mode for users with extra usage enabled—simply issue the “/fast” command. This capability is rolling out in research preview across Cursor AI, Emergent Labs, FactoryAI, Figma, GitHub Copilot, Lovable, V0, and Windsurf.
Meanwhile, Google’s Veo 3.1 update brings long-requested portrait-mode video support along with other performance enhancements. On the collaboration front, Council AI is gaining traction among product teams, and PMs are invited to test it out and suggest next-stage features. Separately, Earmark has launched a personas feature to inject virtual security, legal, and accessibility experts into meetings—adding rigor without pulling real specialists away from their core tasks.
Shifting to broader product strategies, Peter Yang makes the case that AI-driven personal agents will supplant most standalone apps by offering contextual onboarding, voice or text directives, and autonomous multi-app workflows. Lenny Rachitsky’s recent poll of PMs, engineers, and designers shows that most teams report increased job satisfaction since adopting AI, though nearly twenty percent of designers noted a dip. And Shreyas Doshi reminds us that mission statements are just marketing—success should be measured by concrete product outcomes.
In industry developments, Waymo is leveraging Google’s Genie 3 to generate interactive, high-fidelity simulations of rare driving events that are nearly impossible to capture on the road. Guillermo Rauch predicts a wave of teen supergeniuses empowered by AI-driven self-teaching and autonomous agents, forecasting a dramatic acceleration in human potential and technical contributions.
Dharmesh Shah emphasizes embedding insights directly where users store their data to drive adoption. He notes that when reporting answers questions in the same environment as the data, people actually use it—and recommends pairing deterministic systems with AI to ensure predictable, reliable outputs.
On the developer tools side, the Cloud Code agent teams feature requires version 2.1.34 and an experimental flag in your global settings.json. Once “cloud_code_experimental_agent_teams” is enabled, running “cloud-teammate --mode” in T-Max or iTerm2 with the Python API opens split-view sessions for each agent. The new team_create command generates a team config in doc/teams, while task_create writes JSON task files with subject, description, status, blocked, and blocked_by fields.
Another head-to-head comparison showcased Anthropic’s Opus 4.6 against OpenAI’s GPT-5.3 Codex by building a Poly Market competitor. GPT-5.3 assembled a core LMSR market-maker engine, a REST API router, a responsive front end, and passed all unit and integration tests in three minutes and forty-seven seconds. Opus 4.6, running with four parallel agents for architecture, domain research, UX, and testing, consumed roughly 150,000 to 250,000 tokens to produce 96 tests and a modular Next.js 14 app with dark-mode UX and a central limit order book schema. Benchmark results show Opus 4.6 outperforming GPT-5.2 by about 140 ELO points on a white-collar work benchmark, while GPT-5.3 Codex scores 77.3 percent on TerminalBench 2.0 extra-high settings versus 65.4 percent for Opus 4.6 Max. Notably, Opus supports a one-million-token context window, matching the largest models in the market.
That’s a wrap on today’s GenAI PM Daily. Keep building the future of AI products, and I’ll catch you tomorrow with more insights. Until then, stay curious!
GenAI PM