When AI starts writing code, designing interfaces, and generating user flows, the real benefit isn’t speed, it’s coordination. The Product Requirements Document (PRD) is re-emerging as a new kind of Copilot, aligning product management with design- and tech teams with AI as the silent coordinator.
This article continues from my previous post, “How AI just changed the rules of rapid prototyping”. While that explored how vibe coding accelerates the path from idea to pilot, this one looks at what keeps that speed aligned inside modern organisations.
From ad-hoc experiments to stable releases
Vibe coding, coined in early 2025, made it possible to prototype through conversational AI rather than writing code. It gave teams super-speed but also exposed a new fragility: alignment.
Here is a short intro video from Lovable about their Vibe coding promise.
Designers and developers can now build solutions in minutes (over 40% of GitHub code is now generated by AI). But without a shared process that product management can coordinate, Vibe coding can become chaotic and unstable, development dependencies can be unclear, and user validation can be inconsistent.
AI and Vibe coding can easily amplify governance gaps if not curated well.
So to benefit from this potential, product management and their teams need a structure and a stabiliser that keeps intent, experimentation and delivery connected and coordinated.
That stabiliser could potentially be the AI-powered PRD template.
A Product Requirements Document (PRD) is the single source of truth in product development - describing what to build, why it matters, and how it should work. It aligns product, design and tech around a shared goal, translating broad vision into actionable requirements.
In the AI era, the PRD acts as a bridge between human intent and technical execution, reducing ambiguity and guiding collaboration from idea to outcome.
From documents to prompted dialogues with AI
The old PRDs were static and slow to maintain for product owners.
In the AI-first era, PRDs are becoming the platform for living conversations between teams and intelligent systems, shaping how ideas move through design, development and validation.
Applying a PRD Copilot to your product management process
Connected to your product management process, the PRD used as a Copilot can act as the connective tissue that holds together modern product work for all your stakeholders. I have broken down the Triple Diamond into a reference example of how you can benefit from the PRD in each phase.
1. Define - shared intent and purpose
Every initiative, feature request or product discovery starts with intent and purpose. In this first diamond, the PRD Copilot helps capture why something should exist, who it serves, and what outcome it should create.
Key contributions:
- Product Managers: Ensure strategic alignment with business goals, prioritise features, and gather requirements from marketing, sales and customer support.
- Designers: Provide early input on user problems and experience goals to make sure intent reflects real user needs.
- Engineers: Assess technical feasibility, estimate effort, and highlight possible constraints.
AI translates this shared input into structured PRD sections - defining user context, hypotheses, success metrics and validation plans.
The result: a unified foundation where strategy, user need and feasibility are aligned before design begins.
2. Design - context alignment
The second diamond focuses on solving the right problems and validating their relevance with target users before major investment.
Key contributions:
- Designers: Lead with user-centred design, producing wireframes, mockups and user journeys.
- Product Managers: Keep scope tied to measurable outcomes and maintain prioritisation logic.
- Engineers: Confirm technical implications and resource requirements as design evolves.
Here, the PRD acts as the shared hub connecting Figma flows, validation data and prototype experiments.
AI helps detect inconsistencies, ensure consistent terminology, and link design artefacts to functional intent — maintaining coherence between design and delivery.
3. Deliver - curating knowledge and learnings
In the final diamond, the PRD shifts from guiding creation to capturing knowledge - highlighting what was learned, how it performed and what should evolve next.
Key contributions:
- Engineers: Implement features, report back on performance and technical learnings.
- Designers: Validate usability and ensure user experience integrity through feedback loops.
- Product Managers: Document decisions, track outcomes, and refine metrics for continuous improvement.
AI coordinates updates automatically, analyses results, and feeds insights back into the same PRD.
This turns the document into a living knowledge system - reducing duplication, improving traceability, and strengthening the team’s shared memory over time.
Turning the PRD into a coordination engine
The rise of AI-assisted PRD platforms shows this evolution in motion.
These tools transform your ideas into a structured document - drafting requirements, surfacing dependencies, and even suggesting success metrics.
Integrated with toolboxes like Figma, Notion, Linear and Jira, they make the PRD a live coordination hub:
- Product leads can instantly generate draft PRDs.
- Designers can prototype user flows before alignment meetings.
- Developers can ensure that the tech stack is adopted early in the process.
- Researchers feed validation data directly into the same artefact, closing the loop between insight and iteration.
In this curated environment, AI doesn’t replace your team's collaboration; it coordinates it and makes it lean. It detects gaps, proposes consistent terminology and ensures every iteration builds on the same foundation.
ChatPRD calls this “AI as your Chief Product Officer” - maybe a provocative glimpse of a machine-assisted future, where AI-governance models keep intent, design and delivery connected to us humans. Let us look back in some years to see if they were right.
How to start
To make AI productive and sustainable, start by restarting your PRD process into a modern governance model built around four lenses: user intent, data logic, technical feasibility and business viability. By creating your relevant sections from these lenses, AI can automatically coordinate updates, trace dependencies, and maintain coherence.
With your new PRD templates as shown above, every team can be accountable for contributing early - ensuring that AI can represent all teams (and end users) interests, and to surface dependencies and trace decisions back to intent and purpose.
The result of this isn’t just improved speed, it’s more about clarity, transparency and collective learning how to work with AI across your teams.
Why it matters
While AI now accelerates the creation process, the differentiator isn’t just automation - it’s alignment. The organisations that win will be those who synchronise best: combining speed with validation and automation with human intent.
The PRD, once dismissed as bureaucracy, is becoming the operating system of collaboration, translating human goals into machine logic while keeping teams grounded in user reality.
In an age where AI can build anything, the question is no longer “Can we?” but “How do we stay aligned while doing it?”
The AI-powered PRD gives that answer shape and structure.
Closing reflection
AI has redefined how work is produced, but meaningful progress still depends on coordination from the leadership team in the transition phase.
When the PRD becomes the shared space for intent, experimentation, and validation, AI helps teams think together - not faster, but more brilliant and more sustainably.
The next evolution of work isn’t automation.
It’s shared understanding at machine speed.
Want to get started?
If your teams are exploring AI-driven design, development or experimentation but struggle to stay aligned, let’s talk.
Together, we can design your PRD templates and governance models that leverage AI to support coordination, validation, and learning across your teams.
Reach out, and let’s build AI-powered alignment that lasts.
Want to explore?
I help organisations turn intent into impact by integrating AI-powered PRD templates with rapid prototyping, vibe coding, and pilot validation.
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Andreas Markewärn
Andreas Markewärn
