Read the original at Lenny’s Newsletter ↗lennysnewsletter.com · subscriber post
By Lenny Rachitsky · lennysnewsletter.com · @lennysan on X · YouTube · LinkedIn
Tal Raviv, guest-writing for Lenny's Newsletter, offers a hands-on guide to using AI agents to offload repetitive product management work. He walks through setting up a simple customer-prep agent, a checklist for designing low-risk agents, and tips on choosing platforms, managing cost, and security. The core argument is that starting small and building trust gradually lets PMs reclaim time for customer and strategic work.
Subscriber post — summary only01Key takeaways
- Define agents by behaviors like proactivity, live data use, and action-taking rather than by label.
- Start an agent with one narrow, recurring task, and delegate only the step you dread most first.
- Limit downside by having agents draft, recommend, or DM you instead of acting autonomously.
- Stay close to raw customer signals; use AI to organize data rather than replace your own reading.
- Build trust in drops: check results, fix inputs and context, then gradually expand the agent's scope.
“Understanding a problem should be the only prerequisite to solving it.”Max Brodeur-Urbas · Lenny’s Newsletter
02Frameworks mentioned
Summary and takeaways written by PM Atlas; quotes are short excerpts. © the original author.