--- slug: prd-vs-spec-vs-brief title: "PRD vs Spec vs Brief: Which Does Your AI Coding Tool Actually Need?" excerpt: "PRD vs spec vs brief: three near-synonyms with different jobs. Here's what each one is, who it's for, and which one your AI coding tool actually consumes." primaryKeyword: "PRD vs spec" publishedAt: 2026-04-14 readingTimeMin: 7 author: "Robert Boylan" tags: - prd - spec - app-planning - ai-coding-tools - definition --- You sit down to plan an app and three words show up in the same Google search: PRD, spec, brief. They look interchangeable. They aren't. They evolved in different rooms for different audiences, and feeding the wrong one to your AI coding tool quietly produces the wrong app. Here's the honest distinction between PRD vs spec vs brief, and which one Cursor, Lovable, or Claude Code actually wants from you. ## The PRD: the canonical product document PRD stands for product requirements document. It's the artifact a product manager would hand to an engineering team in a company of more than one person. The PRD answers four questions in this order: what we're building, who it's for, what success looks like, and what's deliberately not in scope. A real PRD is comprehensive. It includes user personas, the problem being solved, success metrics, the feature list with priorities, edge cases, dependencies, and usually a section on what won't be built so nobody has to argue about it later. It's written assuming the reader has business context but no engineering context, and the engineering team will translate it into something actionable. PRDs are great when you have organisational distance to bridge. The product person isn't the engineer. The engineer isn't the designer. Everyone needs the same source of truth before specialised work begins. For a solo indie builder talking to an AI tool, a full PRD is overkill in some sections (you don't need stakeholder sign-off paragraphs) and underkill in others (you actually do need the technical detail a real PRD usually punts to engineering). There's a longer post on [what a PRD actually is and why it matters for AI tools](/what-is-a-prd) if you want the full definition. ## The spec: the engineer's working subset A spec, in the engineering sense, is the implementation-facing version of the PRD. It describes how the thing should work, in enough technical detail that someone can build it without making major shape decisions on the fly. A spec usually includes: the feature broken into discrete pieces, the data model, the API surface, key user flows, error handling, performance constraints, and acceptance criteria for each piece. It's tighter than a PRD on the "why" and looser on the "should we build this." The decision to build it has been made; the spec is about how. Engineers writing for engineers tend to call this a spec, a tech spec, or a design doc. The format varies by company. Google's design docs are famous. Most spec templates are not. For AI coding tools, the spec is closer to what you actually need than a PRD is. The AI doesn't care about success metrics. It cares about what the function should do when input X arrives. Acceptance criteria, the heart of a good spec, are also the heart of [what makes an AI coding tool stop guessing](/blog/acceptance-criteria-for-ai-coders). But specs alone often miss the audience and tone information that AI tools need to make good calls about UI, copy, and the visual feel of an app. ## The brief: the hand-off A creative brief, an agency brief, a project brief: short, punchy, single-purpose. The brief exists to align a builder (designer, writer, contractor, agency) on a one-off piece of work. It says what's needed, who it's for, when it's due, what the constraints are, and what success looks like. Done. Briefs are great when the relationship is one-shot. You're handing a logo project to a designer. You're handing a landing page to an agency. You don't need them to understand the whole company; you need them to deliver one good thing. Briefs for AI coding tools sound appealing because the relationship is, technically, one-shot per session. But the AI tool is also building something durable, often in a code style and product context that has to compound over many sessions. A brief on its own tends to produce one good output with no consistency between outputs. The next session, asked to extend the same project, has no idea what came before. Pure briefs work for tools like v0 generating a single component or Figma Make generating a screen. They start to fail the moment the work has any continuity. ## So what does an AI coding tool actually want? Something between a spec and a PRD, with the consistency of a brief. The AI coding tool needs: - **A short statement of what's being built and who it's for** (PRD-flavoured) - **A feature list with acceptance criteria** (spec-flavoured) - **A tech stack and data model** (spec-flavoured) - **A design and tone direction** (brief-flavoured) - **A note on what's explicitly out of scope** (PRD-flavoured) Most AI coding tools, faced with just a brief ("make me a habit tracker"), produce something. The something is usually fine for a prototype and not fine for a real app, because all the decisions the brief didn't make were made by the AI defaulting to whatever was statistically common in its training data. Faced with a full PRD, the same tools tend to drown. Hundreds of words of organisational context are wasted on a model that just wants to know whether the buttons should have rounded corners. Faced with a focused spec that has the personas and the design tone (the bits that pure specs skip), the AI produces noticeably better output. This is the shape that sits between the three older artifacts and is genuinely the right one for the job. ## A worked example Picture a small SaaS for tracking weightlifting workouts. Here's how each artifact would describe the same thing: The PRD opens with: "Strength athletes between 25 and 45 want a low-friction way to log workouts and see progress over time. Existing apps are bloated. Success looks like 60% of trial users still active at 30 days." The spec opens with: "Workout entity has fields: id, user_id, date, exercises (array). Exercise has: name, sets (array of {weight, reps}), notes. POST /api/workouts creates a workout. Acceptance: a user can log a workout in under 30 seconds on mobile." The brief opens with: "Workout tracker for serious lifters. Clean, dark UI, fast input. Done in 4 weeks." The shape AI tools want is closer to: "Workout tracker for serious lifters aged 25-45. Three core features: log workout, see history, see progress chart. Tech stack: Next.js + Supabase. Data model: User, Workout, Exercise (fields listed). Design: minimalist, dark, low-chrome. Tone: confident, no fluff. Out of scope: social features, video form-checks, AI form analysis." That's not exactly any of the three older formats. It's the right one for this job. ## What Draftlytic produces, and why Draftlytic deliberately produces something that isn't a PRD, isn't a pure spec, and isn't a brief. It's the shape AI coding tools actually need, captured by asking the questions whose answers go into the right boxes. The export includes the PRD's audience and out-of-scope sections, the spec's data model and acceptance criteria, and the brief's design tone and copy direction. There's a more detailed walk-through in [a section-by-section tour of the Draftlytic PRD export](/blog/inside-an-exported-prd). The point of the format isn't novelty for its own sake. It's that no existing format was built for the job of describing a small app to an AI coding tool, and so the right thing to do was build one that fits. The next time you find yourself asking "do I need a PRD or a spec for this", the more useful question is: what does the AI tool actually use? Once you know the answer, the older categories stop mattering, and you can stop arguing about which template is correct.