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Hacker News - Newest: "AI"

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The PRD Isn’t Dead, It’s Evolving for the AI Era
Bandan Singh · 2026-02-08 · via Hacker News - Newest: "AI"

The goal of a PRD is simple: to align a team on what to build and why.

Yet, somewhere along the way, we started worshipping the artifact instead of the outcome.

We’ve all seen PRDs go wrong. Massive, stable documents that nobody visits. Over-prescribed solutions that leave no room for design or engineering to breathe. Outsourced thinking overgeneralized by modern tools.

On the flip side, the trendy “anti-documentation” culture has left many teams with massive alignment gaps.

And in others, prototyping has become the stand-in, making it harder to separate production-ready decisions from what’s merely technically possible.

No matter the method, speed without alignment is a liability. As AI compresses discovery, delivery, and the entire PDLC, the advantage moves upstream i.e to choosing the right problems to solve. Without that alignment, teams produce polished outputs that customers simply don’t care about.

So, we’re left wondering: how should a PRD actually function in today’s product environment?

There’s no singular answer. Each project and team needs something unique that reflects their own approach. What follows is guidance on how to think about PRDs as the way we build continues to change…

To understand where we’re going, we have to look at where we’ve been…

Beginning in the 90s and into the early 2000s, PRDs followed the “Waterfall Artifact” architecture. They consisted of a 20–30 page document capturing “every detailed change.”

During this era, Marty Cagan rose to fame with early guides as a response to teams not thinking about users at all. The PRD was the central record and the “instruction manual” for engineering. But, as the process evolved and new work styles emerged, this fell to the wayside.

By the 2010s, heavy specs were quickly falling out of fashion. The industry increasingly embraced Agile and Lean methodologies, which focused on reducing wasted effort, moving faster, and embedding the customer’s voice directly into how teams work.

User stories became the hero of this era, essentially flipping the focus from requirements to the requirement-holder and effectively shrinking the PRD into the backlog. Success was no longer measured by the thickness of the document, but by the team’s ability to solve customer problems in real-time through iterative loops.

From 2020 to 2024, the pandemic-driven shift to distributed work changed where we worked, radicalizing the PRD’s primary function , to that of alignment. This era necessitated the “living hub”: we moved from static documents to integrated ecosystems like Productboard, Notion, and Confluence.

Documentation evolved from a post-meeting summary into a real-time multiplayer environment. During the pandemic, the EPD trio (Engineering, Product, Design) struggled with passive knowledge loss, and teams started using visual collaboration tools.

Pragmatism finally beat dogmatism. Alignment was prioritized over traditional formatting to keep development cycles from stalling.

And, of course, ChatGPT launched.

When generative AI went mainstream, it didn’t just add another tool to the stack; rather, it rewired expectations for how fast product teams could move.

Just over half of product executives report that leadership now expects a focus on AI in both products and workflows.

Suddenly, anyone could spin up a plausible PRD or product brief in minutes. Volume became cheap, and in the process, it exposed a deeper problem. It became dangerously easy to mistake more documentation for better, delivery-ready decisions.

But LLMs don’t do the hard work behind the draft. They don’t deeply understand your customers, your product’s history, or your business’s context. Trained on generic industry patterns, they produce outputs that look complete but lack the evidence and judgment real decisions require. That’s the core issue with AI-generated PRDs: they’re finished quickly, but “finished” isn’t the same as sound.

The real value of a PRD has never been its word count. It’s the judgment required to decide what not to build. As drafting becomes instant, the PM’s role shifts from author to orchestrator. The work moves toward synthesizing raw inputs from customer feedback, market signals, and AI-generated scaffolding into a coherent “Why.”

It’s why 59% of product executives say strategy and business acumen will be the most critical skills for PMs in the coming years, while only 22% prioritize AI or ML fluency.

And, in this high-velocity environment, a modern PRD must show, tell, and validate.

One of the biggest debates today is whether prototyping should replace the PRD. While “show, don’t tell” is valuable for feedback, prototypes without a narrative make the business case and vision opaque, getting caught up in the “excitement of creation” and losing sight of the “why.”

Not to mention, without consulting design and engineering, we can never be 100% certain of the technical feasibility.

The modern PRD ensures clarity through these fundamental qualities:

  • Clear Vision: Where are we going? It isn’t enough to list features, but you must define a “North Star.”

  • User Evidence: Why do they need this? (40% of leaders consider customer insights the most important input for strategy, Product Leadership Trends & Insights).

  • Market Awareness and Business Value: How does this win? (63% of leaders now measure success via revenue impact, while only 8% focus on delivery velocity, Product Leadership Trends & Insights).

And for that reason, PRD is becoming more synonymous with “product brief.” A product brief is a concise document used early in product discovery to frame the opportunity before committing to a solution.

The overall format is becoming…

Modular

Dynamic

A 1-pager for the problem, a 2-page spec for the solution, and mini-PRDs for specific features.

A hub linked to backlogs, prototypes, and metrics that live in shared tools rather than a static folder.

The best teams are adapting by…

  1. Writing to think: Use the PRD/brief to test logic and expose gaps. If a section feels “fuzzy” or hard to explain, you haven’t done enough discovery. Highlight your assumptions to signal where you need more data.

  2. Using AI to explore (not decide): Feed AI your raw discovery notes and ask it to draft the “Problem Statement” or “Edge Cases.” You provide the intent and judgment; let the AI handle the formatting and scaffolding.

  3. Shifting prescribing to enabling: Be rigid about the “why” (the customer problem) but leave the “how” (the solution) open for engineers and designers. Your PRD should set the boundaries, not the blueprints.

  4. Right-sizing it: Match the document to the task. Use a 1-pager for experiments, a full spec only for high-stakes architectural shifts, and so on.

  5. Keeping it alive: Bring the PRD into your rituals, making it the living hub that evolves with your understanding and knowledge, but keeps everyone connected to the “why.”

So, the PRD isn’t dying, it’s just evolving. What used to be a 30-page waterfall artifact became a user story, then a living hub, and now it’s evolving again for the AI era. But through every shift, one thing has remained constant: the teams that win are the ones who stay aligned on what to build and why.

In the AI era, where release cycles are faster than ever, that alignment is your greatest competitive advantage. In fact, Productboard’s recent CPO survey found that leaders who are “leading the business” are 37% more likely to be fully aligned with their stakeholders.

Because when AI can help you build anything, the real competitive edge is knowing exactly what’s worth building.

And with Productboard Spark (learn more), product teams can create product briefs in hours, not weeks, turning their scattered customer and product signals into clear product plans — all while building shared product knowledge that makes their entire organization permanently smarter.