CONTEXTUAL AI NATIVE COLLABORATION

Product management for the agentic era.

SteerFlow is a product management orchestration platform where PMs, designers, and engineers collaborate with their AI agents to build multi-step, complex production-grade products.

DISCOVERY01 / 04

SPEC/password-reset

FLO synthesizes raw research into evidence-linked specs.

user_interviews.csv0%

nps_q3.json0%

support_tickets.md0%

◆ insight 87% churn cite multi-step verification fatigue.

SOLUTIONING02 / 04

DECISION/auth-method

Weigh trade-offs. FLO surfaces evidence and conflicts.

Magic link0 / 30

Passwords0 / 30

3 conflicts resolved · evidence linked

PLANNING03 / 04

EPIC/auth-reset

Stories materialize with acceptance criteria, ready for engineering.

AUTH-12Send magic link email

AUTH-13Verify token + redirect

AUTH-14Rate-limit per address

AUTH-15Recovery via support flow

Synced to Linear · Jira

DEVELOPMENT04 / 04

PR #482/auth-reset

Cursor's agent ships with full context. No re-explaining.

MCP ← 12 sourcescontext packet received

Tests passing · context preserved

Connects to
your stack

Cursor

Claude Code

Figma

Linear

GitHub

Notion

Miro

Jira

Databricks

Microsoft Teams

Mixpanel

Google Workspace

Amplitude

Cursor

Claude Code

Figma

Linear

GitHub

Notion

Miro

Jira

Databricks

Microsoft Teams

Mixpanel

Google Workspace

Amplitude

One context layer, zero information loss.

Phase 01

Discovery

Capture user interviews, market signals, and research insights into structured context assets.

In: Interviews, surveys, analytics

Out: Insight objects, opportunity map

INGESTING 0/5

0 insights

○user_interviews.csvQUEUED

○nps_data.jsonQUEUED

○support_tickets.csvQUEUED

○analytics.csvQUEUED

○competitor_audit.mdQUEUED

Phase 02

Solutioning

Transform insights into solutions. From decision making assistance to detailed spec and solution documentation.

In: Discovery, evidence items

Out: Ranked options, decision log

Option A

Modular Rebuild

Scalability0.92

Effort0.55

Risk0.20

Option B

Full Rewrite

Scalability0.55

Effort0.85

Risk0.78

→ scoring against 12 evidence items…

Phase 03

Planning

Break solutions into scoped EPICs, stories, and tasks with context-aware dependencies, and acceptance criteria.

In: Solution specs, team capacity

Out: Sprint plans, task graphs

EPIC: AUTH OVERHAUL0/5 scoped

⟳Welcome screen & account setupSCOPING…

○Profile completion wizardQUEUED

○Team invitation & rolesQUEUED

○First-run tutorial flowQUEUED

○Empty-state coaching cardsQUEUED

Phase 04

Development

Feed rich context directly into AI coding tools via MCP — so code is written with full product understanding.

In: Task graphs, specs, context

Out: Context-aware code, PRs

STEERFLOW MCP · CONNECTED

THE PROBLEM

Without a context layer, this is what happens.

Product teams generate mountains of context every week — user interviews, design rationale, technical decisions, competitive analysis, codebases and documentation. But none of it flows.

It sits in scattered docs nobody reads, Slack threads nobody searches, and meeting notes nobody references. So when it's time to build, everyone — and every AI agent — starts from scratch.

#product-strategy

"wait, didn't we decide against
that approach in March?"

↑ 12 replies · 3 weeks ago · unread

DGoogle Doc

OUTDATED

Authentication overhaul
spec — Phase 2

Last edited 6 months ago

tell maya about
the edge case ??

📝Q3 Planning · Notion

Meeting notes — Q3 planning

"Action items: TBD"
Last viewed: never

AUTH-342

Reset flow blocked

Status: unclear · 4 blockers

auth-overhaul.fig

"is this the latest?"

7 unresolved comments

Re: Re: Fwd: Re: spec

see attached →

∴ thread depth: 23

PR #1842 · stale

feat: rework session resume

Awaiting review · 41 days

why did we
ship this???

user-interview-17.mov

00:42:18 — "the onboarding
is confusing because…"

Watched: 0 / 30 people

Heard in the wild · 6 voices · 6 tools · 1 missing layer

#research2:14 PM

Maya OkaforPM

We did 30 user interviews last quarter. Nobody on engineering ever saw them.

LAUTH-342 · COMMENT3:02 PM · today

Diego Salas

The spec said one thing, the Figma said another, and the ticket said something else entirely.

session-resume v2 · FIGMA

Priya Raman

I spent two days building a feature that was already deprioritized. The decision was in a Slack thread I never saw.

cursor — auth/session.ts5:21 PM

Jonas Beckvia cursor

Our AI coding assistant writes confident, wrong code because it has zero product context.

📝Sprint 47 · Planning · NOTIONYesterday

@Reina Müller commented

Every planning session starts with 45 minutes of archaeology — digging through old docs to remember why we made decisions.

GPR #1842 · GITHUB · 8 days ago

Aiden Park

"Why was this PR closed? No reason in the thread."

One context layer

6 voices. 7 tools. One missing source of truth.

TWO MODES, ONE TRUTH

Your AI agent. Their AI agents. One shared truth.

Both modes work together. Build structured context & documentation in SteerFlow. Execute in your tools. Every agent stays aligned.

MODE 01

Collaborate with FLO

Work directly with FLO, SteerFlow's AI agent, to build and iterate on your documents at any phase. Upload research, challenge assumptions, refine requirements, generate plans. The AI is your thinking partner — it pushes back, connects evidence, and structures your output.

FLO

Connected to 12 sources

Ask FLO anything…

MODE 02

Your tools talk to SteerFlow

Use your existing MCP-compatible tools — Cursor, Claude Code, Figma, Linear, GitHub. Their AI agents communicate directly with SteerFlow to get clarifying context, acceptance criteria, and architecture decisions. SteerFlow becomes the source of truth your entire stack reads from.

SteerFlow MCP

Cursor Agent

SPEC: OFFLINE SUPPORT

9 SOURCES ●●●●●●●●●

✦ CLAUDE CODE (QA Agent)

Querying SteerFlow for acceptance criteria on offline sync...

FEATURES

What will you get on SteerFlow AI?

AI-NATIVE COLLABORATION

Expert AI Agent Swarm

Collaborate with opinionated, well-trained AI agents — from deep research and data analytics to design experts and technical architects. No yes-sir bots, structured domain experts with self-reflection at every step, scaling your output 10x.

Research Agent

analyzing 23 sources…

Design Expert

reviewing wireframes…

Tech Architect

evaluating trade-offs…

Product Expert

reviewing PRD v2.1…

▸ Describe the task in plain english, and the right Agent will pick it up...

→ 4 AI Agents active, 2 self-reflecting

DOCUMENTATION

Structured Co-Authoring

Build detailed documentation across the lifecycle — PRDs, EPICs, Stories, Personas. With AI that co-authors, not just suggests.

⟳User Personas.mdCO-AUTHORING…

○Research Presentation.pptxQUEUED

○PRD v2.1.mdQUEUED

○Epic BreakdownQUEUED

○Test Plan.mdQUEUED

GOVERNANCE

Controls your security team will sign off on

Define which agents can read which context, what they can act on, and who reviews before code ships. Every decision logged, every artifact attributable.

Scoped agent permissionsPer-epic

Approval gatesConfigurable

PII & secret redactionAutomatic

Audit logImmutable

TRACEABILITY

Evidence-Linked Decisions

Every decision documented with reasoning. Resources tagged for full audit trails.

DECISION AUDIT

📌 Magic link improves conversion

↳ 3 sources linked ✓ VERIFIED

↳ NPS +32, 5 interviews cited

📌 Drop SMS 2FA for v3

↳ 4 sources linked ✓ VERIFIED

↳ support cost -41%, deliverability issues

VERSIONING

Living Specs, Not Static Docs

Specs evolve with your product. Branch, diff, and merge — every change reviewable, every version recoverable.

PRD v2.1.md · HISTORY

●v2.1 · current2h ago

○v2.0 · scope cut1d ago

○v1.4 · approved3d ago

INTEGRATION

AI-Native Integration

External tools communicate natively with SteerFlow's knowledge base via MCP servers, plugins, or Skills — whatever your tool supports. Cursor, Windsurf, Claude Code, and any MCP-compatible agent.

→ 3 specs, 8 decisions delivered via MCP

CONNECTED TOOLS

Cursor←Skill→SteerFlow Skill

Claude Code←Plugin→SteerFlow Plugin

Jira←MCP→SteerFlow MCP

TESTIMONIALS

Built for teams who are tired of building the wrong thing.

“

We finally have one place where research, requirements, and technical specs live together. Our agents stopped guessing.

Jeyki Chen

VP of Product, InovaLab

“

The MCP connection changed everything. Our Cursor agents now query the actual requirements instead of working from half-read tickets.

Marcus Rivera

Engineering Lead, Tamara

“

From discovery to sprint planning in one workspace. We cut our spec-to-development handoff time in half.

Aisha Patel

Head of Product, G42

EARLY ACCESS OPENING SOON

Get early access to shape the product.

FAQ

Frequently Asked Questions

No. SteerFlow is the context layer across the entire product development lifecycle. It covers Discovery, Solutioning, Planning, and Development. A PRD is one artifact in phase 1. We structure 20+ documents across four phases, all linked and queryable.

Your agents are good enough.

Give them the right context for scale.

AI agents are fast enough. But every engineer feeds their agent a different version of the truth. Five agents. Five silos. Fast, confident, half valuable commits. SteerFlow is the shared context layer that keeps every human and every AI agent aligned — from first quick search to final commit.

Early access opening soon. No credit card required.