The agentic PM OS
Specky — Ship right. Ship fast.
Specky connects to your Slack, Gong, and Jira — builds a living Product Graph — then drafts PRDs, queues tickets, and runs customer interviews while you sleep. Your team ships with evidence, not instinct.
We'll research your competitors, scan your category, and draft a real workspace from what we find.
14-day trial · card required · cancel before day 14 to pay nothing · full refund within 14 days of first charge
Overnight agent · how it actually works
Trusted by builders
“Specky drafts our PRDs and tickets overnight. By morning the work is queued, evidence-linked, and ready for us to review and ship.”
“In gaming, speed is everything. Specky's market intelligence caught a competitor's pivot before it launched, and the agentic PM had our response specced, ticketed, and queued the same night. It's the edge every startup team needs.”
“Our roadmap used to live in sticky notes and gut feeling. Specky synthesises member feedback, drafts our feature specs, and tracks every shipped feature back to real outcomes. We build smarter now.”
Autonomous. Not assisted.
Your PM team works overnight.
Every night, Specky's agents scan your integrations, synthesise new signals into your Product Graph, and queue work for morning review. You wake up to decisions — not raw data.
Agents pick up 3 new Gong calls, 14 Slack threads, and a Jira sprint close.
Opportunity identified: "CSV export blocking 3 deals" — cross-referenced with OKR: Expand mid-market.
PRD drafted. Tickets staged. Alex interview campaign queued for 5 target customers.
One inbox item. Review the draft. One click to approve.
PRD: Bulk CSV Export for Operations Teams
Before Specky
- ✕3h writing a PRD from memory
- ✕"I think customers want this"
- ✕Competitor launches. Surprise.
- ✕Sprint ends. Did it work?
With Specky
- ✓8min reviewing one Specky drafted
- ✓17 interviews. 4 themes. Evidence.
- ✓Flagged 3 weeks before launch.
- ✓Outcome loop closed automatically.
Chapter 1 · The pain
You were hired for Leverage.
You spend most of your day on Overhead.
Shreyas Doshi's LNO framework: PM tasks are Leverage, Neutral, or Overhead. The highest-value work gets the least time — because the lowest-value work never stops arriving.
- Writing PRDs from scratch
- Weekly status updates
- Manually syncing across tools
- Re-explaining old decisions
- Maintaining a roadmap nobody reads
Specky automates this.
- Sprint planning
- Backlog grooming
- Stakeholder alignment
- OKR check-ins
- Cross-team coordination
Specky makes this faster.
- Customer discovery
- Strategy and bets
- Insight synthesis
- Evidence-backed decisions
- Coaching the team on outcomes
This is where Specky frees you to live.
Chapter 2 · The system
PM work is a system. Specky is its agent.
Specky is built like an OS for product work — a substrate, autonomous agents, an orchestration layer, and a closed outcome loop. Every customer signal flows through the same pipes; every shipped feature is tracked back to whether it moved the number.
01 · Substrate
Product Graph
Slack, Gong, Jira, GitHub, customer interviews, AI output — every signal indexed into one searchable graph. Semantic and keyword. The substrate everything else runs on.
02 · Agents
Autonomous agents
PM Inbox curates signals overnight. Alex runs JTBD interviews end-to-end. Chat works against 26 tools. They keep moving whether you're at your desk or not.
03 · Orchestration
Custom Workflows
User-authored multi-step workflows over the same agents and graph. Versioned, executed, scored by an LLM judge. Repeatable PM work, not one-off prompts.
04 · Outcome loop
Closed-loop validation
Every shipped feature is tracked back to its outcome. Experiments → insights → next quarter's bets. The loop closes — automatically.
Three agents. One graph.
Eight steps to shipped.
Alex, Playbooks, and Chat aren’t separate tools — they’re the coworkers running each phase of the loop, on the same graph, so the next step is always smarter than the last.
Alex interviews your users — at scale.
A shareable link runs conversational JTBD interviews with your customers. Alex probes, follows up, and surfaces evidence-backed themes — not a spreadsheet of raw answers.
Playbooks scan your market overnight.
Multi-step workflows mine competitor pricing, G2 reviews, and landing pages. Each finding lands in your graph as typed evidence — ready to cite, not to re-read.
Every surface of your company becomes a sensor.
Slack threads, Gong transcripts, Jira tickets, interviews, support tickets — ingested continuously and tagged in real time alongside what the agents gather.
Signals cluster themselves into themes.
Semantic search + agentic classification collapse thousands of fragments into a handful of recurring, quantified themes with source evidence.
Themes compile into insights with a thesis.
Each insight comes with a confidence score, a quoted evidence chain, and the job-to-be-done it maps to — ready to defend in a leadership review.
Ask the graph anything — get cited answers.
A chat that actually knows your product. Every reply links back to the Slack thread, Gong call, or PRD that supports it. Drafts docs and tickets inline.
Insights become PRDs in two minutes.
Specky drafts the spec with inline citations to the original signals, the opportunity tree, and the assumption set — editable, not magical.
PRDs ship as tickets, in your stack.
One click syncs engineering tickets to Jira or Linear. The loop closes: outcomes feed back as new signals, and the graph learns.
How Specky works
Connect your stack
OAuth connect Slack, Jira, Gong, Linear in minutes. No data migration.
Graph builds itself
Signals are indexed, clustered, and linked into a living Product Graph automatically.
AI agents work overnight
PRDs, tickets, and research campaigns are drafted while you sleep — grounded in your real data.
You review & ship
Wake up to a PM Inbox with confidence-scored drafts. One click to approve, push, or discard.
Built for every role in the product org
Chapter 3 · See it work
A workspace that already knows your product.
Good morning — here's what Specky did overnight
Analyzed 47 new signals overnight, found 2 clusters reaching significance, and drafted PRDs for both. The bulk workflow management PRD has 0.92 confidence — ready for your review.
Every PM pain, solved in one place.
The product model demands continuous discovery, living strategy, and documented decisions — then gives PMs zero tooling to do any of it. Specky is the infrastructure that makes it work. Every signal compounds. Every decision stays alive. Every PRD is grounded in evidence, not gut feel.
Product Graph
Not a flat feedback board — a connected knowledge graph. Every Slack thread, Jira ticket, Gong call, and research session becomes a node with relationships. Context compounds over time instead of rotting in silos.
Alex Research Agent
The only PM tool with a built-in AI researcher. Alex conducts Jobs-to-be-Done interviews autonomously — via shareable campaign links. Themes, sentiment, and NPS flow straight into your Product Graph.
Session Intelligence
Connect PostHog, Sentry, or Pendo. Specky's AI reviews every session recording, clusters recurring bugs into one issue with instance counts + affected users, and emails everyone who hit it the moment you mark it fixed.
Execution Bridge
From approved PRD to shipped sprint in one flow. Auto-generated tickets push to Jira or Linear with one click, stay linked back to the opportunity that created them — so context never gets lost.
PM Inbox
Your AI coworker works overnight. Wake up to drafted PRDs with inline citations, generated tickets with acceptance criteria, and staged research campaigns — each with a confidence score. Review, approve, ship.
Outcome Intelligence
Track your batting average — how many features actually moved their metric. AI synthesises patterns across validated outcomes and tells you where to focus next quarter.
Your AI watched every session.
It already knows what's broken.
Connect PostHog, Sentry, or Pendo and Specky reviews every recording, screenshot, and error. Visual bugs, rage-clicks, and broken flows get clustered into one issue with an instance count and the full list of affected users. One click marks it fixed and emails everyone who hit it.
Watches every session, not samples
AI reviews replays, console errors, and rage-click signals end-to-end. No dashboard-staring. It reports what it found, with evidence.
Visual bugs you'd never catch in logs
Headless screenshots at the moment of friction. Layout overlaps, cut-off CTAs, broken modals — caught by a multimodal model looking at the actual pixels.
Grouped by instance, not by session
48 users hit the same checkout bug → one issue with "48 instances" and every affected email listed. The Lucent pattern, built into your PM workspace.
Close the loop with one click
Mark fixed → every affected user gets a personal email. "Hey, that checkout bug you hit is fixed." Support tickets close themselves.
Checkout CTA clipped on iOS Safari
“Pay now” button renders below viewport after keyboard opens. Users rage-tap header, then abandon. Screenshot confirms layout breaks at vh-100 minus keyboard.
Know your batting average.
Stop shipping in the dark.
67% of shipped features never move the metric they were supposed to. Specky closes the loop — every feature gets validated against the outcome it promised, and AI synthesises the patterns so next quarter's bets get smarter.
- Predict, then confirmSet an expected metric move when a feature ships. Specky pings you when the data is in to compare.
- Verdict in one clickMark each shipped feature as worked, mixed, didn't move, or too early — Specky learns from each call.
- Synthesis you can act onAI surfaces the patterns across confirmed outcomes — the bet types that win, the assumptions that miss.
- Closed loop, not lost loopEvery validated outcome flows back into the Product Graph, so the next discovery cycle compounds on what you've learned.
Features tied to activation OKR shipped 4× more often than retention bets — but only 2 of 7 retention experiments moved the metric. Worth re-examining your retention assumptions before next quarter's planning.
Chapter 4 · Why this isn't another AI tool
Cursor didn't make engineering judgment obsolete.
It made the mechanical work faster.
Cursor freed engineers from boilerplate so they could apply more judgment to the hard problems — architecture, tradeoffs, edge cases. Nobody confuses it for a senior engineer.
Specky is the same: eliminate the documentation tax and your capacity for the work that can't be automated — customer relationships, strategic bets, stakeholder influence — actually increases.
What Specky explicitly doesn't claim
Built for the way product teams actually fail.
Most product model transformations fail — not because PMs don't know the theory, but because the day-to-day work overwhelms them. Specky closes the gap.
Why not just use Claude?
Claude starts from zero. You paste the Slack thread, explain the backstory, describe the constraints — every session. Specky already knows your product, your decisions, your customer evidence. It compounds. Generic AI can't replicate that.
Is this just another PM tool?
The product model asks PMs to own outcomes but gives them no tooling to do it. Specky does the writing, synthesis, and tracking the model demands — while your context compounds in the background.
What makes it defensible?
Organizational memory. Companies pay consultants hundreds of thousands to implement the product model — then lose all the context six months later when the PM changes jobs. Specky is the living record of every decision, every discovery, every bet — searchable, connected, and always current.
The 7 gaps every PM lives with — and how Specky closes them
See it in action
14-day full trial. Up and running in 5 minutes.
Connect Slack and Jira. Walk away. Wake up to your first AI-drafted PRD — grounded in your real signals.
14-day full access on Solo and Growth. Full refund if you cancel within 14 days — no questions asked.
The work the model demands.
Done while you sleep.
PRDs. OKR updates. Stakeholder briefings. Discovery summaries. The product model requires a documentation cadence no PM has time for. Specky handles it overnight — grounded in your real signals, staged for your review, nothing published without approval.
Auto-Campaign
Detects significant clusters with gaps in research and stages interview campaigns with generated questions. Never auto-launches — you decide when to go live.
Auto-PRD
When evidence hits critical mass, Specky drafts a full PRD with inline citations from your signals. High-confidence PRDs auto-publish; the rest queue for your review.
Auto-Tickets
Approved PRDs automatically generate implementation tickets with acceptance criteria, story points, and edge cases — ready to push to Jira, Linear, or straight to your coding agent on GitHub.
Auto-Briefing
Stakeholder updates, board summaries, and sprint retrospectives generated overnight from your live Product Graph. Lands in your PM Inbox — nothing to prepare manually.
Custom Workflows
Save your own AI prompt workflows and trigger them from a single click. Build a library of reusable product rituals — retrospectives, briefs, discovery syntheses.
You're always in control
Every autonomous artifact lands in your PM Inbox with a confidence score. Nothing ships without your approval. Toggle workflows on or off, set your own approval thresholds.
The product model in one workspace.
With none of the overhead.
Discovery, strategy, decisions, delivery, and measurement — the five things the product model demands and most tools ignore. Every capability connected through one living Product Graph.
From signal to shipped feature.
Integrations
8+ sources
Slack · Jira · Linear · GitHub · Gong · HubSpot · Google · Notion
Compliance
SOC 2 · GDPR
Audit logs, consent tracking, data export & deletion
Get started
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PM at a Series B SaaS
Turn a 3-line brief into a cited PRD.
- 1PM Inbox clusters Slack complaints with Jira tickets and a Gong call.
- 2Draft a PRD grounded in that evidence — citations stay inline.
- 3Push tickets to Jira in one click when eng signs off.
Founder doing discovery
Validate an idea with real user evidence.
- 1Alex runs JTBD interviews with a link — no recruiter, no calendar.
- 2Themes land in the Product Graph alongside your support data.
- 3You decide what to build from evidence, not gut feel.
CPO prepping the board
Assemble the quarterly narrative.
- 1OKRs, roadmap, and experiments pull from live workspace data.
- 2Stakeholder briefings adapt tone per audience automatically.
- 3Export a shareable doc or push to Notion.
Any signal. From anywhere.
The named tools below are examples, not requirements. Specky also takes data via REST API, webhooks, file upload, URL import, and a Chrome extension — so anything you have, you can graph.
Chapter 5 · Earn the security review
Security & privacy
Enterprise-grade security, built in from day one.
SOC 2 alignment, GDPR & CCPA, EU data residency in Frankfurt, AES-256 + TLS 1.3, immutable audit logs, RBAC and SSO — every control your InfoSec team will ask about. Full security overview, DPA, sub-processor list, and pen test summary on the security page.
Everything you need to know.
Does Specky replace PM judgment?
Why not just use Claude or ChatGPT?
Do I need to replace my existing tools?
How is Alex Research different from running a Typeform survey?
Is my data used to train AI models?
How long does it take to set up?
What pricing plans are available?
How does the 14-day trial work?
What a PM’s time actually costs — and what Specky recovers.
A fully-loaded Senior PM costs $120/hour. The airfocus 2024 PM Survey found 52% of that time goes to admin work, synthesis, and context-switching — not strategy. Here’s what that looks like in real numbers.
Ticket writing, synthesis, re-reading Slack threads, context-switching — not product thinking.
airfocus 2024 PM Survey
Each wrong feature costs $38K–$55K in engineering time alone — before design, QA, and PM hours.
Industry average
Dovetail + Productboard + Pendo + Notion — before counting hours lost switching between them.
Tool vendor pricing, 2025
5-person product team: Year 1 value
Scenario assumes 10 hrs/week of admin recovery per PM and one wrong feature avoided per quarter — validate against your own team. Even at half those assumptions, the recovered value is ~$180K/yr against a $4,800/yr Growth plan. Time recovery based on the airfocus 2024 PM Survey (52% of PM time on admin tasks) and industry PM salary data (Levels.fyi, 2024–2025).
Early-stage startup? Get special pricing.
Pre-seed to Series A teams qualify for up to 50% off for 12 months — because we know runway matters. Book a 30-min call with our founding team and we'll design a plan that fits where you are.
Your product context deserves better than 8 disconnected tabs.
Connect your tools, let your AI coworker build the graph, and wake up to work done. Book a demo and see why the best product teams are switching to Specky.