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Product management is not mainly the production of a specification. It is the work of helping a team understand who a product is for, why it matters in that person’s life, and what the product should help them do. In his September 14, 2026 essay for Andreessen Horowitz, product investor Josh Elman argues that this shared story is even more important now that AI makes it cheaper to build quick prototypes.
What does a product manager produce?
Asked what artifact a product manager produces, Reid Hoffman’s question points beyond the familiar document. A specification can describe a system, requirements, and scope; it does not necessarily give a team a shared understanding of why the product should exist. Elman’s answer is that product management is about telling “the story of people who are going to use the product, and why it will matter in their lives.”
That story helps designers, engineers, and other teammates make decisions that fit together. It does not make specifications useless: teams still need to define and build a product. But a detailed spec is a means of communicating and organizing work, not a substitute for a clear account of the people the product serves.
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Elman is an Andreessen Horowitz partner focused on consumer technology and AI, according to his official biography. His argument appears in “Product Management is Still All About Telling Stories,” published September 14, 2026.
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How AI changes the path from idea to product
When prototypes are expensive, teams may spend considerable effort writing specifications and deciding scope before they can interact with an idea. Elman describes a different sequence enabled by AI-assisted prototyping: move from an idea to a quick prototype, play with it and learn, design it as a real product, then ship and keep learning.
The prototype makes an idea tangible sooner. A team can see what feels promising, what is confusing, and what should change before committing to a production build. But a persuasive demo is not a finished product. The team still has to decide whether the concept belongs in the product and do the design, implementation, and other work required to make it reliable and useful.
Ask whether an idea fits the product—not only the schedule
“Can this fit in the schedule?” is a resourcing question. “Does this fit in the product?” is a product judgment. Faster prototyping can make it easier to generate and demonstrate more ideas, but it does not make every idea worth shipping. Adding features can undermine coherence if they distract from the product’s purpose or make its core actions harder to understand.
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AI changes how quickly a team can explore possibilities; it does not remove the need to curate them. The important decision is not simply whether an idea can be built, but whether it strengthens the product’s story for the people it is meant to serve.
Define the product through purpose, actions, and cycle
Elman’s practical framework for expressing a product vision has three parts. Together, they make the story concrete enough to guide design and evaluation:
- Purpose: Why would someone choose to bring this product into their life?
- Core actions: What does that person actually do with the product?
- Cycle: How often should each core action happen?
The cycle matters because products are used differently. Some are intended for frequent, repeated use; others may provide value in less regular moments. A team needs to know what return and activity mean for its product rather than treating a high usage frequency as universally good.
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How to tell whether people are really using a product
Signups, waitlists, revenue, app-store rank, and traffic can tell a team something about attention or business performance. On their own, they do not establish that people are getting the product’s intended value. Elman frames the essential question as: “Are people really using your product?”
Look for whether people voluntarily return and perform the core actions the product exists to support. Interpret those behaviors against the product’s purpose and expected cycle. A count of visitors or accounts is less informative if it does not show whether people return for the product’s central job.
For AI products, learn from real interactions
Read user transcripts to understand what people expect, where they get stuck, and when they rephrase a request. Those moments can reveal a gap between the product’s promise and what users can accomplish with it. AI can help surface recurring patterns across conversations, but the product manager still has to interpret what they mean and decide what to change.
Make onboarding teach the product’s story
Onboarding is a high-attention moment: a new user is curious, and the product has an opportunity to explain why it exists and how to reach value. Elman distinguishes people who already know what they want from casual visitors and the larger group in between. Designing only for the eager expert risks leaving that curious middle unsure what the product does or where to begin.
A useful onboarding experience repeats the product’s central message, explains why it asks for information, introduces the product in understandable concepts, and gives each concept a clear action. For an AI product, a blank prompt box may offer flexibility but little guidance. Show what the product can do and help a new user reach a useful case, ideally using their own data.
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Twitter’s Learn Flow, as Elman recalls it
Elman recounts that early Twitter users arrived curious but often did not understand what Twitter was or what to do. He says the team rebuilt onboarding as a Learn Flow that taught tweets, following, and timelines step by step. In his account, that change moved retention more than anything else the team shipped that year. This is Elman’s recollection in the essay, not an independently measured study presented there.
The example illustrates the broader point: onboarding can teach the basic concepts and actions that make a product legible, rather than assuming people will work them out alone.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use the story to make product decisions
A product story is useful when it helps a team choose what to build, what to leave out, and what evidence to watch. Put the framework to work by asking:
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- Are the product’s core actions clear enough to guide a first-time user?
- What cycle of return makes sense for those actions?
- Do observed users return voluntarily and complete those actions?
- Does a proposed feature reinforce the product’s purpose, or merely add capability?
- Does onboarding help a newcomer reach a meaningful use case?
These questions connect vision to daily decisions. A specification may record the resulting requirements, while prototypes may help test possibilities; the story supplies the shared reasoning that keeps both aligned with user value.
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