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Platform tour

The agentic PM OS.
End to end.

Specky is an operating system for product work — not a feature set. Here's how every layer fits together, from raw signal to shipped feature to closed outcome loop.

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How it works

From signal to shipped feature in four steps.

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01

Connect your stack

OAuth connect Slack, Jira, Gong, GitHub, PostHog in under 5 minutes. Specky starts indexing signals immediately into your Product Graph.

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02

The graph compounds

Every night, agents cross-reference new signals with your OKRs, open opportunities, and past decisions. Patterns surface. Opportunities get scored.

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03

Wake up to decisions, not data

Your PM Inbox has a drafted PRD with inline citations, staged tickets with acceptance criteria, and a queued interview campaign — all grounded in real signals.

04

Close the loop

When the feature ships, Specky tracks whether it moved the number. Experiments → insights → next quarter's bets. The outcome loop closes automatically.

Every PM pain, solved in one place

The product operating model, made tractable.

45+ views covering the full PM loop — from signal ingestion to shipped feature to measured outcome.

Signal Intelligence

Product Graph

Every signal, decision, spec, ticket, interview, and outcome stored as a connected node. Context compounds over time instead of rotting in silos.

PM Inbox

Wake up to drafted PRDs, staged tickets, and queued interview campaigns. All grounded in real signals. Review, approve, ship.

Insights Dashboard

AI-generated insights synthesised from your product graph. Surfaces patterns and recommendations from all connected data sources.

Customer Intel

Aggregated signal hub: live feeds from Slack, Gong, Intercom, Zendesk. Trend alerts with % change. Call recordings with AI-extracted action items.

Intelligence Playbooks

Multi-step AI research workflows. Run competitive analysis, market research, launch readiness checks, and discovery sprints as structured playbooks.

Session Intelligence

Connect PostHog, Sentry, or Pendo. Specky reviews every session recording, clusters recurring bugs into one issue with instance counts and affected users.

Spec & Planning

PRD Generator

From raw signals to a full spec in minutes. Problem statement, success metrics, user stories, acceptance criteria, edge cases — grounded in real evidence.

Opportunity Tree

Visual hierarchy mapping customer problems to bets and experiments. Three-level tree: objective → opportunity → solution, with evidence panels.

Roadmap

Quarterly timeline view of planned, in-flight, and shipped work. Aggregates opportunities, tickets, documents, and objectives into a single view.

Prioritization Matrix

Score and rank features using RICE or ICE frameworks. AI auto-scores features from graph signals. Table and quadrant views.

Decision Log

Structured log of product decisions with rationale, outcome tracking, and evidence linking. AI can extract decisions from documents.

Strategy Canvas

Assumption inventory, risk radar, competitive moves, and strategy narrative — all in one place. Decisions stay alive and linked to the evidence that made them.

Research & Validation

Alex Research Agent

The only PM tool with a built-in AI researcher. Alex conducts JTBD interviews autonomously via shareable campaign links. Themes and quotes flow into your graph.

Synthetic Users

Test any concept against AI personas before spending a dollar on research. Get adoption estimates, top blockers, unmet jobs, and a clear verdict.

Discovery Workspace

Automated synthesis of signals into themes and opportunities from connected tools. Surfaces patterns you'd never find manually.

Experiment Tracker

Plan, run, and review product experiments with hypothesis tracking, method selection, and evidence recording. Links to strategy canvas assumptions.

OKR Tracker

Full OKR management with key results, progress tracking, and AI-powered risk analysis. Links OKRs to experiments and feature outcomes.

Stakeholder Map

Power/interest quadrant map of stakeholders with stance tracking and AI engagement advice. Champion/supporter/neutral/skeptic/blocker.

Execution

Execution Bridge

From approved PRD to Jira tickets in one click. Each ticket includes acceptance criteria, effort context, and the customer signals that created it.

Tickets View

List view of all AI-generated engineering tickets with filtering, bulk actions, and push-to-tool capability. Bulk AI grooming included.

Kanban Board

Drag-and-drop delivery board for tickets across Open → In Progress → Blocked → Done columns.

Custom Workflows

Build and run custom multi-step AI workflows with 16 available tools. Supports scheduled (cron) and manual triggers, team sharing.

Knowledge Base

Internal wiki-style knowledge management. Create knowledge bases with articles, backlinks, and compiled summaries. Supports document import.

Templates Library

Pre-built document templates (PRDs, research briefs, specs) that can be instantiated into the editor with one click.

Revenue & Outcomes

Outcome Intelligence

Track whether shipped features actually moved their metric. AI synthesises patterns across validated outcomes and tells you where to focus next quarter.

Revenue Intelligence

Business signal dashboard connecting Stripe MRR, Salesforce pipeline, and HubSpot deals to product signals. Churn risks, deal blockers, expansion opportunities.

Feature Adoption

Analyzes feature usage data from PostHog, Pendo, Mixpanel, or Amplitude. Produces graduate/keep/sunset recommendations per feature.

Risk Radar

Upload a roadmap CSV and get AI-powered risk scoring per initiative. Identifies scope creep, dependency risks, resource conflicts, and timeline risks.

OKR Outcome Check

Automated cron checks OKR progress and flags at-risk objectives. Links experiments and feature outcomes back to key results.

Competitive Intelligence

Background agents monitor competitor changelogs, pricing pages, and product announcements. Briefing delivered to your inbox before your standup.

45+ product views26 AI tools in chatSOC 2 alignedEU AI Act alignedData never trains AI

Session Intelligence

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.

Watches every session, not samples

AI reviews replays, console errors, and rage-click signals end-to-end. No dashboard-staring required.

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 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.

Close the loop with one click

Mark fixed → every affected user gets a personal email. Support tickets close themselves.

Live · Session Issue
2 min ago
Visual bugPostHog

Checkout CTA clipped on iOS Safari

“Pay now” button renders below viewport after keyboard opens. Users rage-tap header, then abandon.

48
instances
31
users
High
severity
Auto-linked to graph · Jira ticket created
Works with PostHog session recordings Sentry errors & replays Pendo friction signals

The leverage loop

Every decision closes back on itself.

Most PM work is linear — you ship a feature and never know if it worked. Specky is a loop. Customer signals become decisions, decisions become experiments, experiments close back to validated outcomes that inform the next bet.

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01

Discover

Alex interviews customers end-to-end. Slack, Gong, Jira signals indexed automatically.

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02

Synthesise

Insights surface from the graph. Opportunities scored against your OKRs overnight.

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03

Decide

PRDs and decisions logged with full context. Evidence-backed, never based on memory.

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04

Experiment

Hypotheses tested systematically. Results flow back into the graph automatically.

05

Validate

Did it move the metric? Outcome intelligence closes the loop — and seeds the next cycle.

The loop never breaks.

Every validated outcome seeds the next round of discovery. Specky tracks which bets paid off — so next quarter's roadmap is built on evidence, not instinct.

Start the loop

Agentic architecture

PM work is a system. Specky is its agent.

Specky is built like an OS — 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. 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.

The full loop in one workspace.

Connect your tools, let your AI coworker build the graph, and wake up to work done.

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specky

The agentic PM OS.

Turn signals into shipped features, automatically.

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