AI evolution for Product work
What areas of product management get replaced?
Like everyone, I've been exploring the application landscape as new shiny-new-ai-things appear weekly. Productivity and workflow enhancement apps have been my favourite category, apart from using voice-GPT as a gallery guide.
I will react to Reforge's AI impact on PM activities and update you on my best AI-enhanced workflows.
Three sentence summary
AI is eliminating the time-consuming admin layers of product work.
This puts pressure on PMs to deepen judgment, taste, and storytelling.
The builders who can think clearly and communicate value will thrive.
What parts of product management get replaced?
I don't have a clear-cut answer or elaborated vision, but I can share what changed for me and my people.
AI enhances
These are areas where AI doesn’t replace the PM — it augments their thinking and accelerates output.
Strategic Direction: Competitive analysis or market research in deep research mode. Synthesizing survey responses, customer interviews, and chat transcripts. What used to take days now takes minutes.
Builder mentality: A prototype is worth a thousand Jira specs, and tools like V0, Lovable, Cursor, or Bolt have become essential for telling the product story.
Decision-making: I'm keen to see more development in this area. There is a case for prioritizing managers who process live backlog data and maintain some prioritization score, as you do. I also look forward to seeing more applications from experimentation platforms.
AI replaces
These are no longer PM differentiators; it's admin work delegated to systems. The best PMs are letting these go fast.
Meeting summaries: I've tried a few tools in this space, but Circleback worked like magic and became integral to my note-making system.
Product artifacts: I experimented with many tools to move faster with documentation, right now my toolkit looks like this:
Chat GPT Pro Projects, for PRD templates used in Jira epics or user stories for engineering tickets, where I share examples of templates to keep in memory.
Reforge AI extension in Jira is handy for release notes and comment summaries.
Notion AI for exploring the knowledge base (yes, I moved away from Obsidian)
If I had to highlight the top three workflows where AI feels like complete magic for me:
From meeting note to Jira ticket ready for developers: I ask the Circleback bot for a summary of requirements as we diligently repeat ourselves for the bot to capture the right decisions during calls. Copy and paste that transcript into the GPT Jira ticket writer bot template.
From UI inspiration to mobile-friendly prototype on your phone: You have a new feature you found from an adjacent industry that could be added to your product. You get that screenshot to ChatGPT, ask for a V0 spec, build the thing in V0, and get the prototype share link. With screenshots of the prototype and the specs, get the engineering ticket from the GPT Jira ticket writer to investigate the feature.
Talking to technical documentation: I export all API integration docs into a PDF and load them into a Claude project as a knowledge base, then I talk to the documentation and run audits on my systems.
Taste and judgement
I appreciate how Shaun and Fareed contextualize taste and judgment as key attributes for product people; I see both as integral parts of personal branding that influence the most powerful leadership tool: storytelling.
Product people are always crafting narratives that take people on a journey to understand what they're building and why it matters.
So what are you being paid for?
The confidence that I have in my taste and my ability to express what I feel has proven helpful for artists.
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