Product decisions live in your head
Feature ideas, customer complaints and half-remembered support tickets don't accumulate anywhere. Every decision starts from scratch.
The Product Operating System when you're the PM.
You're the founder, the PM, and often the QA. AI made your builders faster. Feature1 keeps your product decisions from becoming the bottleneck — the product capacity you haven't hired for yet.
Not Prompt → PR. Reality → Evidence → Decision → Execution → Outcome → Learning.
- Your product brainFeature1 continuously understands what your product does today — so you don't rebuild that context every week.
- The customer firehose, synthesizedFeedback, support noise and calls become evidence attached to what to change next — not another Slack you have to read.
- Product knowledge that survives youEvery decision, its evidence and its outcome stay linked. Six months in, you (or your first PM) can still answer why.
Works with GitHub, GitLab, Bitbucket and your existing workflow.
You're the founder, the PM, and the customer researcher.
AI made coding cheap. That made deciding what to build cheaper too — but only if someone is actually deciding. And that someone is you. Feature1 is the product capacity you haven't hired for yet.
AI builders wait on you
Cursor, Claude Code and mvpfy can implement in an hour — but not without a clear PRD, acceptance criteria and constraints. Which is another hour of your day.
Your first PM inherits nothing
When you hire someone, they get a codebase, a Slack, and a folder of stale docs. The reason behind six months of decisions is gone.
Product context gets fragmented across tools.
Each tool can do its job well while the decisions and evidence connecting them disappear between handoffs.
Business strategyDocs and presentations
Customer feedbackCalls, CRM and Slack
Product planningRoadmap tools
ExecutionJira or Linear
ImplementationGit + coding agents
QA and releaseTest tools, docs and Slack
The context and product operating layer.
- Strategy and insights
- Objectives and initiatives
- Capabilities and features
- Criteria and sprint work
- Implementation and QA
- Shipped product reality
Your tools can stay. Feature1 keeps the product context connecting them.
A single customer signal, followed into product reality.
Not a diagram of how it could work. This is the trail Feature1 leaves behind for one real change, and every step links back to the one before it.
- 1SIGNALFour enterprise accounts raise account-recovery friction in support and in two interviews.VOC · 4 sources
- 2OBJECTIVEScored against the north star and attached to an existing objective, not a new one.OBJ-2
- 3PLANA structured analysis produces a PRD with the dependency map and the open questions surfaced.PRD-118
- 4CRITERIAThree acceptance criteria written as Given / When / Then, each independently testable.AC-001 → 003
- 5SPRINTPulled into the sprint carrying the objective and the criteria with it.US-2041
- 6SHIPPEDImplemented criterion by criterion, each approved before the next begins.PR #482
- 7PRODUCT REALITYTrigger a capability scan and the evidence reflects what the software can now do.SYNC · COMPLETE
Open the shipped change and the objective, PRD, acceptance criteria and updated product capability remain connected. Nothing was re-typed.
The questions your product team should always be able to answer.
Feature1 keeps the context needed to answer them continuously — for humans, for AI agents, and six months later when someone asks why something exists.
- What does our product actually do today?
- Why are we changing it?
- What evidence supports this decision?
- Does this duplicate or contradict something that already exists?
- Which part of the product needs to improve?
- Is execution still aligned with the original decision?
- Did what we shipped actually work?
- What did we learn — and what changes next?
The ticket remembers why it exists.
Feature1 does not stop at generating planning artifacts. It keeps the product decision attached as work becomes software.
Planning that interrogates the request
F1 asks the relevant product, implementation and strategy questions, checks feasibility against the product, and surfaces assumptions before a PRD is approved.
This one argues with you first.
Implementation that stays inside the gates
Developers and coding agents receive the objective, feature intent, acceptance criteria, constraints and architecture context — not an isolated ticket.
Implementation stays inside the acceptance criteria.
One product context. Every human and every AI agent.
Every squad and every AI agent loads from the same evolving model of what the product does, why the last change was made, and what customers said about it — not their own guess.
Nothing gets rebuilt from scratch every sprint.
Roadmaps become capability changes, not disconnected feature lists.
Start with what the product can do today, state the outcome, then plan only the changes needed to close the gap.
Current capabilityBulk order managementDepth 3 / 5
ObjectiveReduce enterprise onboarding time by 40%Required depth 5 / 5
Planned changes
- Bulk validation
- Bulk editing
- Error recovery
- Progress reporting
Your roadmap should know when the code changes.
When implementation lands, Feature1 can rescan the connected repository and update its evidence-backed understanding of product capabilities. Strategy stays grounded in what the software now does.
- 01Product intent recorded
- 02Implementation lands
- 03Capability scan triggered
- 04Capability evidence updated
- 05Strategy remains grounded
Your existing stack stays where it is.
Feature1 gives GitHub, GitLab, Bitbucket and MCP-compatible coding agents (Cursor, Claude Code, Codex) the product context around every change — so they consume the same product model your team does.
GitHubGitLabBitbucketClaude CodeCodexMCP
Plans are scoped to the product team, not every person who reads a ticket.Talk to us about pricing →
Manage. Build. Grow. One product context across all three.
Feature1 manages the product. mvpfy builds it. BeyondWebsite grows it. Same understanding of the product powers all three — plus the open-source tools that extend the platform.
Growth engine
LaunchedBeyondWebsite
Take what you have built to market and keep it current.
View product →
Open-source PM IDE
Open sourcemvpfy
Help PMs and founders safely work against real codebases.
View product →
Open-source system
LaunchedAgentify by F1
Turn software APIs into conversational agents.
View product →
Open-source system
Launching soonChatify by F1
Turn organizational knowledge into conversational interfaces.
View product →
Trusted by 10+ product teams shipping at AI speed
Sharper thinking for product delivery.
PRODUCT STRATEGY
From feature shipping to capability evolution
Manage durable capabilities instead of disconnected feature output.
FEATURE PLANNINGStop using ChatGPT for feature planning
Feature planning needs context, collaboration and executable output.
ENGINEERINGDriver-navigator pair programming in the AI era
Keep AI-generated code aligned with intent and review quality.
Bring your roadmap. Bring the repo.
We will use a real objective and real product context to show how Feature1 connects planning to implementation.