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Spec-Driven Product Management

From product vision to AI-ready spec

Delvyn turns your strategy, OKRs, and discovery into structured specifications that AI coding agents (Copilot, Claude Code, Cursor) implement directly — pushed straight to GitHub and Linear.

Teams waste 40–60% of AI agent output when specs lack product context. Delvyn closes that gap. The spec is the product.

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GitHub
Linear
Jira
The Problem

Your AI agents can implement a feature in minutes. But who ensures they're building the right feature?

Specification Quality Gap

Vague prompts produce vague code. AI agents need structured, context-rich specifications to deliver quality results.

Based on early adopter data, up to 40–60% of AI output is wasted due to poor specs

Missing Product Context

AI agents lack your product vision, strategy, and OKRs. Without context, they build features that don't align.

3x rework cost when agents build the wrong feature

No Learning Loop

Every implementation starts from scratch. Teams lose learnings from past builds, repeating the same mistakes.

Same mistakes repeated sprint after sprint

Before & After

See the difference context makes

Same feature. Same AI agent. Completely different results.

Without Delvyn Studio

prompt.txt

"Add a dashboard page with some charts showing OKR progress"

No awareness of which metrics matter to the team
Invents random chart types that don't match the data model
Ignores existing design system and component library
2–3 rounds of rework to get it right
With Delvyn Studio

agent-spec.md

"Build an OKR progress dashboard. Product vision: team alignment through transparency. Key results tracked: revenue growth, NPS, deployment frequency. Use existing BarChart from recharts. Follow design system tokens..."

Strategic context: shows the metrics that matter to this team
Technical context: uses the existing component library
Acceptance criteria: machine-readable success definitions
Right first time — no rework needed

The difference isn't the AI agent — it's the specification. Delvyn Studio generates specs that include your product vision, strategy, OKRs, and technical context so agents build correctly on the first try.

Four pillars of AI-native product excellence

A unified model that connects product thinking to AI agent execution.

Vision & Strategy

Define where you're going and why. Export strategic context as AI agent context files that keep every implementation aligned.

Discovery & Ideas

Validate before you build. Structure risks and assumptions for AI implementation with proven discovery frameworks.

OKR Framework

Set measurable outcomes with machine-readable acceptance criteria. AI agents know exactly what success looks like.

Agent Specification Engine

Core

Generate structured specs from your product context. Push to GitHub, Linear, or Jira. AI agents implement with full strategic alignment.

AI-Native Workflow

From product vision to AI agent implementation

Every stage feeds into the next. AI agents receive full strategic context, not just task descriptions.

Vision
Strategy
Discovery
Agent Spec
GitHub / Linear
AI Agent
Learn

Strategy flows into specifications. Specifications flow into implementations. Learnings flow back into better strategy.

Compounding Value

Every implementation makes your next spec better

Capture learnings, identify patterns, and improve specification quality over time. The more you build, the smarter your specs become.

Specify

Generate context-rich agent specs

AI Builds

Copilot or Claude Code implement

Learn

Capture what worked and what didn't

Better Specs

Next iteration starts smarter

Continuous improvement loop
Integrate, Don't Replace

Delvyn Studio isn't another project management tool. It's the thinking layer that makes your existing tools smarter.

Keep Linear, Jira, and GitHub exactly as they are. Delvyn Studio adds the strategic context that turns task descriptions into implementation-ready agent specifications.

Think

Vision, strategy, and OKRs in Delvyn Studio

Specify

Generate agent specs, push to GitHub or Linear

Execute

AI agents build in your existing workflow

Push Context to Where AI Agents Work

Native integrations for AI-native teams

Push agent specifications directly to the tools your AI coding agents use.

GitHub

Push specs to Copilot Agent

Linear

Create issues for Claude Code & Copilot

Jira

Sync work items & track progress

Works with GitHub Copilot Agent, Claude Code, and any AI coding assistant.

The thinking layer your tools are missing

Your project management tool handles execution. Delvyn Studio handles what to execute and why.

Delvyn Studio
Linear
Jira
Productboard
Product Vision, Strategy & Guardrails
AI Agent Spec Generation
Spec-to-Agent Pipeline
OKR Management
Product Discovery & Validation
Learning Capture System
Project Planning & Initiatives
Issue Tracking & AI Agents

Linear excels at execution with AI agents. Productboard manages roadmaps. Delvyn Studio ensures those agents build the right things — with structured vision, strategy, and agent-ready specs.

Built for Your Role

Different roles, one platform

Whether you set the vision or implement the code, Delvyn Studio bridges the gap.

Product Leaders

VP Product, Product Managers, CPOs

Bridge the gap between product strategy and engineering execution. Define vision, set OKRs, and know that AI agents are building features aligned with your strategic goals.

Translate strategy into structured specs without writing code
Ensure every feature connects to business outcomes via OKRs
Track what your team builds against what they should be building
Validate ideas with discovery frameworks before committing engineering time

Engineering Managers

Engineering Leads, Tech Leads, Staff Engineers

Get implementation-ready specs that AI coding agents can act on immediately. No more ambiguous tickets. No more back-and-forth on requirements.

Receive specs with full product context for your AI agents
Push directly to GitHub repos or Linear issues for AI implementation
Reduce rework with machine-readable acceptance criteria
Capture implementation learnings that make future specs better
Standalone OKR Platform

Only need OKRs?

OKR Studio is a focused, standalone OKR platform for teams that want goal management without the full product operating model.

OKR Planning, Check-ins & Evaluation
Team Alignment Dashboards
Visit OKR Studio

OKR-First Teams

Starting at $9/user/month

Stop wasting AI agent output. Start specifying.

Give your AI agents the strategic context they need. Build the right things on the first try.

3x
less rework*
60%
less wasted output*
1st try
right implementation