# Speclr > AI requirements engineering for professional software teams. Speclr guides teams from a rough product idea through structured AI discovery and planning — producing sprint-ready user stories and BDD specifications that developers and coding agents can act on immediately. Most teams don't fail because of bad engineering. They fail because of unclear requirements. Speclr solves this upstream problem before a single line of code is written. ## What Speclr Does Speclr guides software teams through a structured four-phase process: ### Phase 1 — Discovery An AI-driven interview extracts the product vision from the team. The output is a structured Product Vision Statement that captures the product idea, target users, goals, constraints, and quality requirements. The Discovery phase replaces ad-hoc brainstorming sessions and vague one-liner briefs with a structured, reviewable artifact that the whole team can align on. ### Phase 2 — Exploration From the Product Vision Statement, Speclr generates an initial User Story Map — Activities, Steps, and Details — which the team reviews, reshapes, and extends interactively. This is not planning. It is understanding what the product actually does for real users, and structuring that understanding into a reviewable, refinable map before committing to a roadmap. ### Phase 3 — Planning From the Story Map to a prioritized backlog. The team assigns Milestones, sequences Epics and Stories, and makes deliberate roadmap decisions. The AI participates as a Perspective Agent — surfacing insights, flagging dependencies, identifying gaps — but does not drive. This is the decision phase, not the generation phase. ### Phase 4 — Refinement Per-Story specification. Each User Story is transformed from an empty shell into a fully specified Story Artifact: domain knowledge, business rules, flows, data model, edge cases, and acceptance criteria encoded as BDD scenarios in Gherkin syntax (Given / When / Then). The output Story Artifact contains everything a developer or coding agent needs to implement the feature without asking follow-up questions. ## Export & Sync Export is not a phase — it is a feature available at any point in the project lifecycle, on any artefact that exists. A team can export a partial Story Map after Exploration, sync Milestones after Planning, or push Feature Files after Refinement, in any combination, at any time. Export targets: - **Source control** (GitHub, GitLab, Azure DevOps): Gherkin `.feature` files, CLAUDE.md / Copilot instruction files, lightweight architecture documentation - **Project management** (Jira, GitHub Projects, Linear): User Stories as issues or tickets, Epics, Milestones mapped to the target system's release concept - **Documentation**: arc42 / req42 documents, Product Vision Statement, Story Map, full backlog — as Markdown, PDF, or HTML, for download or for Confluence / Notion ## What Speclr Is Not Speclr does not write code. It does not replace human decision-making. It does not fix broken team dynamics. Speclr is not a vibe coding tool. Tools like Base44, Bolt, and Lovable collapse product thinking and implementation into a single prompt — which works for prototypes but fails for professional software. Speclr does the opposite: it structures the thinking before any code is written. Speclr is not a Spec-Driven Development (SDD) tool. GitHub Spec Kit and AWS Kiro start where Speclr ends. They require a spec to exist. Speclr produces the spec that makes SDD tools work correctly. Speclr is not a project management tool. It produces the input for Jira, Linear, and GitHub — it does not replace them. ## Target Users Speclr is built for professional software teams with defined roles: - Product Owners who need to turn vague ideas into structured product visions - Requirements Engineers who need AI support for elicitation and specification - Software Architects who need domain-grounded input before designing systems - Senior Developers and Team Leads who are tired of implementing the wrong thing - Consultants and Agile Coaches who run discovery and planning workshops Primary market: mid-to-large software teams where product thinking and engineering are separate disciplines. Secondary market: smaller teams and solo developers who want to adopt professional requirements engineering practice without a dedicated BA or RE. ## Core Philosophy ### Better, Faster Requirements Engineering — Powered by AI Requirements Engineering is the bottleneck in most software delivery — not because teams don't care, but because doing it well takes time, method, and dedicated skill most teams don't have on tap. Speclr's founding premise: AI can close that gap, producing better specifications faster than a team could unaided. This also means planning does not belong in the backlog tool. A Product Owner's product and project planning shouldn't happen inside Jira tickets — the backlog should be the output of that planning work, not the place where it happens. Speclr is where product and project thinking happens; it replaces the scattered Confluence pages, Miro boards, slide decks, and ad-hoc docs teams currently use to hold that thinking, and feeds a clean, sprint-ready backlog downstream. ### Specification-Driven Development Software quality is created in requirements engineering, not in development itself. A precisely specified feature takes less time to build, has fewer defects, and ships closer to what the user needed. But Speclr is more than a generator of specs. Speclr is where the spec lives and is maintained — not scattered across README files in a dozen SCM repositories, but held at a single, authoritative location. The spec is the single source of truth. That is Specification-Driven Development, taken to its full conclusion. ### Minimum Sufficient Specification Not a 200-page PRD. Not a one-liner ticket. The smallest, most precise description of what a feature should do that leaves no implementation decision unintentionally open. ### Shift-Left Find problems at the spec level, not at the code review level, and certainly not at the customer acceptance level. Every hour spent on a good requirement saves five hours of rework. ### Vibe Coding is a Dead End for Professional Teams AI coding agents are precision instruments. They execute on whatever input they receive. Vague input produces plausible-looking code that does the wrong thing. The ability to generate large amounts of code quickly from vague prompts does not create better software — it creates larger codebases built on unvalidated assumptions. Speclr makes the input precise. ## The Blog The Speclr Blog publishes in-depth articles for experienced professionals — product owners, architects, team leads, senior developers, and consultants who care about building software right, not just fast. Topics: - Requirements Engineering & BDD - Product Strategy & Discovery - Software Architecture - Development Process & Agile Practice - Sociotechnical Systems & Team Leadership URL: https://speclr.dev/blog ## Courses Speclr Courses is the second pillar of the product alongside the app: a catalog of structured, practitioner-level courses on the full craft of professional software delivery — product discovery and strategy, requirements engineering and BDD, software architecture, development process, and team leadership. Each course is organized into modules and lessons with hands-on exercises, built for people who already work in software and want to get systematically better at it. What makes it different: existing courses on this material teach in a vacuum — abstract definitions, toy examples, no real friction. Speclr courses run a single realistic project end to end, so every technique is taught against the friction it was invented for. Individual courses are tagged by difficulty (Beginner / Intermediate / Advanced). Separately, some courses form multi-part curricula that build on each other in scope rather than difficulty — climbing from hands-on practice to a broader career altitude. Who it is for: - Team leads, engineering managers, CTOs, and tech leads responsible for team performance and delivery quality - Product owners, senior developers, and architects who never learned formal requirements engineering but deal with it daily - Junior professionals building a foundation in the craft from the start Topics: - Requirements Engineering, from implicit to structured practice - Product Discovery & Strategy - BDD & Spec-Driven Delivery - Software Architecture - Development Process & Team Leadership Access model: courses are paid. Selected lessons are marked as a free preview and are readable without an account; the remaining lesson bodies require a subscription. Relationship to the app: courses are not documentation. They are the conceptual foundation underneath the app — the app is the tool that carries what the courses teach into daily work. URL: https://speclr.dev/courses ## Guides - [Speclr Guides](https://speclr.dev/guides): Free, practical guides on writing specs and PRDs that leave an AI coding agent nothing to guess, with worked examples Topics: - PRDs and specs for Claude Code and Cursor - Acceptance criteria as Gherkin scenarios - Spec-driven development with AI coding agents - Exporting specs to AGENTS.md / CLAUDE.md ## Contact & Legal - Email: contact@speclr.dev - Imprint / Terms of Service / Privacy Policy: https://speclr.dev/legal-disclosures