01
Vague requirements survive
When wishes, decisions and open questions travel together and nobody knows what to ask, the mismatch surfaces in the middle of development.
Requirements, handled. Progress, visible.
AI-native delivery management for the AI era
Requirements, handled.Progress, visible.
Anyone can run deliverywith AI agents.
Drop in your meeting notes and AI pulls out the vague requirements and the open questions, then asks them in Slack. Answers come back into requirements and tasks, and pull request activity flows into progress. You never stall on what to ask or how to keep track.
PMs, clients, owners building an in-house team and engineers all read the same delivery map, from requirements through to progress.
See where delivery stands at a glance
Requirements, tasks, delays and progress in one dashboard.
Delivery management that AI agents keep moving
Spot vague requirements, ask in Slack, fold answers back in, create tasks, link pull requests, update progress. Management follows the flow of development instead of interrupting it.
01
Requirements
02
Slack follow-ups
03
Task handoff
04
Progress
The problem
Requirements and progress break down when you chase them separately.
When meetings, Slack, tasks and pull requests are disconnected, requirements stay vague, answers scroll away and progress goes stale. PM on Rails closes those gaps with AI agents.
02
Answers scroll away in Slack
If the answer you got never lands back in a requirement or a task, nobody can say where the real spec lives.
03
Progress never reaches the board
When pull requests and code live apart from the management view, both the PM and the client spend their days chasing the current state.
How projects catch fire
One small open question becomes a large rework late in the project.
The longer an answer stays out of the requirements and tasks, the more expensive the fix. That is why finding, asking and reflecting has to be one continuous flow.
1
Vague requirement
2
Answered in Slack
3
Never reflected
4
Rework and firefighting
After adoption
Requirements and progress get lighter for everyone involved.
This is not automation for its own sake. Development and management finally move in the same flow.
PM
Post-meeting homework moves without the PM chasing it
Meeting notes turn into organised requests, open questions, Slack follow-ups, in-scope and out-of-scope calls, acceptance criteria, tasks and pull request status. The PM stops being the person who asks around and goes back to being the person who decides.
Engineer
AI can start implementing without guessing
Claude Code and Codex receive the background of the request, the design, the Gherkin acceptance criteria, the dependencies, changes made after work started and the pull request link. Less spec hunting and board updating, more time writing code.
Client
Delegating no longer means flying blind
Even without knowing what to ask or how to track it, your requests, the agreed scope, the acceptance criteria, the roadmap, the board and the change history stay in one flow. Delegation instead of a black box.
Owner building in-house
In-house development stays out of the black box
After you hire engineers, the business side can still follow requirements, priorities, progress, delays and the reason behind each change. Going in-house does not have to mean relying on individual heroics.
The answer
Find the vague requirement, ask about it, reflect the answer.
From not knowing what to ask, AI extracts the open questions and puts them to stakeholders in Slack. What comes back returns as proposed updates to requirements, acceptance criteria and tasks.
Catch vague requirements
AI separates decisions, open questions, out-of-scope items and things to ask, straight from your meeting notes.
Ask in Slack
Open questions become questions a stakeholder can actually answer, and you ask them where the team already talks.
Feed answers back into specs and tasks
Replies come back as proposed updates to requirements, acceptance criteria and tasks.
Send development activity back to progress
Tasks and pull requests stay linked, so completions and status changes show up in progress.
Requests get organised
Meeting notes and documents become requirement cards with the request, its background and its acceptance conditions.
See when things will land
Track the big picture on the roadmap and check what is being built right now.
Daily work keeps moving
Tasks move across the board and stay linked to their pull requests.
Connected to your AI agents
Claude Code and Codex read the same requirements, tasks and acceptance criteria while they build.
Automation
From meeting notes to shipped progress, run by AI agents.
The strength of PM on Rails is not the number of features. It is that requirements, Slack follow-ups, task creation, AI-assisted development, pull request links and progress all move in one flow.
01
Requirements
What AI does
Split meeting notes into requests, decisions, open questions, things to ask and out-of-scope items
What people check
Check that it is right
02
Follow-up
What AI does
Turn each ambiguity into a question you can ask in Slack
What people check
Adjust the wording if needed
03
Reflection
What AI does
Return answers as proposed updates to requirements, acceptance criteria and tasks
What people check
Approve the update
04
Ready for dev
What AI does
Weigh acceptance criteria, priority, effort and dependencies before work enters a sprint
What people check
Spot what is missing
05
Implementation
What AI does
Hand the request, acceptance criteria and task context to Claude Code or Codex
What people check
Do the implementation
06
Progress
What AI does
Send pull request activity back into tasks and progress
What people check
Read the current state
Check before work enters development
Requirement is clear
Acceptance criteria exist
Dependencies sorted
Stakeholders agreed
Features
Requirements, progress and delivery in one flow.
This is not a menu of screens for a PM to operate by hand. It is a delivery map that AI agents can read, connecting requests all the way to progress.
Requirements
Turn meeting notes into requirement cards, open questions and explicit out-of-scope items.
Slack follow-ups
Turn ambiguity into questions and pull the Slack answers back in.
Acceptance criteria
State what done looks like in a form both engineers and AI agents can act on.
Task breakdown
Expand requests into user stories, acceptance criteria and tasks.
Pull request links
Pull requests link back to their task, and merging moves the status forward.
Progress tracking
Pull requests, due dates, sprints and burn-down charts in the same flow.
What people do
People get to focus on reviewing and deciding.
AI handles classification, drafting questions, reflecting answers, preparing work for development and updating progress. People judge whether it is right, whether to proceed and whether the priority holds.
Review what was flagged as ambiguous
Approve questions and the answers reflected back
Decide priority and how to proceed
Comparison
How this differs from a typical tool
PM on Rails is not a place you keep typing into for the sake of management. It is where AI agents keep delivery management running.
| Aspect | Typical tools | PM on Rails |
|---|---|---|
| Position | A requirements tool, or a task tracker | A delivery management OS run by AI agents |
| Input | People register information they already organised | Meeting notes, Slack answers and pull requests move it forward |
| Requirements | The PM re-reads everything and sorts it by hand | AI catches the vague parts and turns them into questions and proposed updates |
| Progress | The PM updates tickets | Pull request and schedule activity flows back into tasks and progress |
| AI coding | Engineers explain the background every time | The links between request, acceptance criteria and task go to Claude Code and Codex |
| Outsourcing / in-house | Hand it all to an agency or an engineer and hope | Without technical expertise you can still see what is open and how far it has gone |
Try it on the web
Experience requirements handled and progress visible.
Bring one set of meeting notes and start the flow: catch the vague requirements, ask in Slack, reflect them into requirements and tasks, then track progress.
Talk to us
Let's talk about running outsourced or in-house delivery with AI agents.
Whether you want an external agency to work this way, you are building an in-house team, or you simply want the PM to stop doing manual clean-up: we will map which parts of your current meeting, Slack and task routine belong in PM on Rails.
The first win
Turn meeting notes and Slack answers into requirements and a clear list of open questions.
The next win
Extend it through tasks, pull requests and progress so delivery management runs on its own.
Free consultation