Integration Guide
Delvyn + Linear
Linear Agent writes engineering specs from operational context. Delvyn writes product specs from strategic context. Know when each is enough — and when you need both.
When is Linear Agent enough?
Linear Agent + Skills is now free on every Linear plan. It's genuinely powerful. Here's when it's all you need.
Linear Agent is enough when…
- Small team (< 10 people), engineering-led
- No formal product strategy or OKR practice
- Engineering leads prioritization decisions
- Specs are primarily technical (API design, refactors)
- One PM or tech lead owns the full picture in their head
- MCP context from Notion/Granola/PostHog is sufficient
You need Delvyn when…
- PMs are accountable for product strategy
- OKRs drive what gets built (not just backlog priority)
- Multiple stakeholders need alignment on specs
- You practice product discovery before building
- AI agents should build strategically, not just technically
- You want a learning loop: specs improve over time
The core difference
Linear Agent writes engineering specs from operational context — what's in Linear, Slack, Notion, PostHog. Delvyn writes product specs from strategic context — vision, OKRs, discovery insights, guardrails, and past learnings. One is technically correct. The other is strategically aligned.
How they work together
Delvyn writes the product spec. Linear + AI agents execute it. The result: strategically aligned features, shipped fast.
1. Think
Define vision, validate through discovery, set OKR success criteria in Delvyn
2. Specify
Generate agent spec with full strategic context from Delvyn
3. Push to Linear
Spec becomes a Linear issue via MCP integration
4. Agents Execute
Linear Agent + Claude Code + Copilot implement with full context
Pricing comparison
Delvyn Studio
$9/leader/mo
Engineers & stakeholders are always free
A 10-person team with 2 product leaders costs $18/month total. Unlimited engineers.
Linear
$8/user/mo
Every user pays
A 10-person team costs $80/month. All members need a seat.
Add the strategic layer to your Linear workflow
Start free and generate your first product specification. Push to Linear and let AI agents implement with full strategic context.