Perplexity Previews Agentic Personal Shopper

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. In product launches, Arav Srinivas announced that the Windows build is now ready, early tester invites have gone out with detailed feedback channels for bug reporting, the Android build is running ahead of schedule with early access, and iOS updates are slated to arrive in the next few weeks. On another front, Arav Srinivas also previewed an agentic Personal Shopper in Perplexity, complete with memory of past interactions and real-time browsing capabilities. This feature allows it to recall your preferences, scour online stores, and surface the best deals. In related news, the LangChain team launched a Smart Document Assistant for enterprise workflows. This tool uses retrieval-augmented generation to tackle multi-file queries, letting product teams upload documents in PDF, Word, or spreadsheet formats and ask complex questions across datasets to get precise, accurate answers. Additionally, the LangChain group published a practical Conversational Memory Guide for large language models. The guide covers session-level memory, long-term storage, trimming outdated context, and summarization techniques, complete with code snippets to streamline implementation. On a different front, product strategist Claire Vo released a tool selection framework for AI prototyping. Her model maps team expertise to recommended platforms—from no-code automations in DevIn for beginners, through GUI-driven tools like Cursor, up to advanced scriptable engines such as O3 for power users. She also provided comparison tables and decision trees to streamline tool evaluation. Turning to strategy, Aakash Gupta explained why building a simple AI wrapper often fails. He outlined the right approach, focusing on clear use case definitions, robust data pipelines, iterative model training, user feedback loops, and performance monitoring to ensure scalable AI products. Separately, Teresa Torres advised adopting essentialism in product management. Drawing on Shane Parrish’s article "Much of What You’re Going to Do or Say Today Is Not Essential," she recommended timeboxing tasks, using prioritization matrices, and conducting regular portfolio reviews to eliminate low-value work. In industry developments, Logan Kilpatrick discussed how coding agents have accelerated Gumroad’s product velocity in an unfiltered chat with Sahil. These autonomous agents have automated refactoring, test creation, and release scripting—cutting days off typical development cycles. Finally, Lenny Rachitsky shared insights from a former VP of Product at OpenAI, emphasizing that AGI is necessary but not sufficient for value creation. He stressed that builder hustle—rigorous prototyping, domain expertise, and hands-on problem solving—is essential to turn advanced models into user-facing features. 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!