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.
v0 now imports GitHub repositories directly, enabling code edits and production deploys all within the platform. In related news, Google AI upgraded Gemini in Chrome with a multitasking side panel, Nano Banana image generation, deep integrations with Gmail, Calendar and YouTube, plus an auto browse feature for agentic actions—available on Windows, macOS and Chromebook Plus for Pro and Ultra subscribers.
Andrew Ng launched a course on building custom agent skills—packaged instruction folders that run across Claude Code, the Claude API and the Claude Agent SDK. Josh Woodward showcased how to use Gemini’s new side panel (Control+G) to keep the model running in the background, edit images, auto browse and compare multi-tab contexts for seamless Q&A. Meanwhile, Lenny Rachitsky demonstrated rapid prototyping by building an RPG-style product knowledge game in eight hours with Claude Code, Codex and Cursor, auto-importing libraries, music and assets.
Separately, Guillermo Rauch released vercel-labs-agent-skills, a library of installable AI skills extracted from Vercel’s iOS app—teams can add these via a simple npx command to turn institutional knowledge into reusable modules. Additionally, Brian Balfour introduced Reforge Concept Testing, which ingests wireframes or mockups, runs live voice interviews with target users at scale, and delivers analyzed feedback within hours to validate ideas before heavy engineering investment.
On strategy, Marily Nika recommended a friction-first AI workflow—using an Assumption Audit, Secret Sauce Gatekeeper and Prioritization Sparring Partner to challenge AI outputs and preserve PM judgment. Jason Zhou proposed a “recurring habit for a recurring moment” framework to structure features that drive sustained engagement and retention.
In the broader market, Andrej Karpathy argued research-driven startups can still outcompete major AI firms, citing the high probability of tenfold breakthroughs despite rapid incumbent scaling. Mistral AI announced production deployments with ASML and Mars Petcare for custom AI systems that accelerate silicon lithography and maritime logistics. And DeepLearning.AI reported that Apple struck a multi-year deal to embed Google’s Gemini models into future Siri and other AI features.
On the analysis front, AI Explained dissected Anthropic CEO Dario Amodei’s essay predicting full-job automation by LLMs, potential displacement of half the entry-level white-collar workforce and emergent multi-persona AI psychologies. Peter Yang’s tutorial showed how to set up Molt (formerly Clawd) as a 24/7 AI assistant in under 20 minutes—using Anthropic Opus on Telegram—and recommended running it on dedicated hardware with scoped credentials for security. Deeplearning.ai’s Elie Schoppik explained skills—self-contained instruction folders that agents dynamically load for tasks like code review or SQL queries—now an open standard across Anthropic’s ecosystem. Claire from How I AI shared her real-world experience with Clawdbot, praising its research strengths but warning of complex setup, security risks and occasional scheduling errors. Finally, Greg Isenberg demonstrated upgrading Clawdbot into Henry, a proactive “employee” delivering morning briefs, trend monitoring and autonomous PRs, using Claude Opus for reasoning and CodeX for coding, hosted locally with locked-down credentials.
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!