Resh Mouli: building AI-powered workflows across the full PM lifecycle
Resh Mouli published this article on Medium in January 2026. The core argument is that most PM work — creating documents, synthesizing research, preparing presentations, managing meetings — involves execution tasks that are well-suited to AI augmentation, and that the real productivity gain comes from designing repeatable workflows around AI rather than reaching for AI tools case-by-case.
The article identifies eight workflow areas and maps specific tools and approaches to each.
The eight workflow areas
PRD development. Mouli uses ChatGPT for drafting and refining requirements, and NotebookLM for synthesizing research materials. Feeding existing documents into NotebookLM grounds the output in actual user data and reduces the risk of hallucinated or generic content in requirements.
Roadmap creation. Claude and ChatGPT function as thinking partners for translating strategy into prioritized themes. Miro AI generates visual structure from text descriptions, making the transition from strategic framing to shareable artifact faster.
Presentation preparation. NotebookLM converts existing documents into slide outlines and speaker notes. Canva AI handles layout and visual execution from that outline.
Meeting management. Zoom AI Companion, Fireflies, and Otter handle transcription and action item extraction. Mouli treats these as infrastructure — always-on, requiring no manual activation — rather than tools to reach for when notes seem important.
Go-to-market planning. AI assists with drafting positioning statements, GTM plans, and launch checklists from strategy inputs. The emphasis is on speed of iteration: getting a first draft quickly enough to pressure-test assumptions before committing to a direction.
Rapid prototyping. Tools like v0, Lovable, Bolt, and Replit AI enable quick UI mockups for user validation without waiting for engineering capacity. This changes when in the product cycle feedback can be gathered.
System visualization. Miro AI and Napkin AI transform text descriptions of processes into diagrams, reducing the gap between having a mental model of a system and being able to communicate it.
User research synthesis. NotebookLM extracts themes from interview transcripts; ChatGPT generates persona summaries from raw feedback. Both reduce the time between data collection and insight extraction.
Key framing
Mouli distinguishes between using AI tools when convenient and designing AI-powered workflows as a deliberate system. The former produces occasional time savings; the latter changes how much work a PM can complete in a given week. He draws a clear line between areas where AI adds speed — drafting, structuring, synthesizing — and areas where human judgment remains central: strategy, prioritization, and stakeholder relationships.
The article includes a sample daily workflow structured across morning, midday, and afternoon phases, which gives the framework concrete shape beyond a tool inventory.
Who it is useful for
Product managers who already use AI tools occasionally but want to move toward more intentional and systematic workflow design. Also useful for PMs building a case for AI tooling within their organizations, since the article provides a structure for explaining where AI fits into standard PM work rather than making a general argument for AI adoption.