Demand intake and delivery governance for engineering managers
From vague demand to a
clear delivery decision.
Turn raw work requests into structured, decision-ready demands before you commit people, budget, or a date.
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What's the request?
Title
Mobile Checkout Performance & Conversion
Problem
Checkout drop-off rate is 34% on mobile, above benchmark. Likely a mix of load time and UX friction.
Outcome
Reduce mobile checkout drop-off from 34% to under 25% by end of Q3.
Likely owner
TBD — suspected Mobile Team
Vague asks don't become clear by themselves.
Most demands start as a Slack message or a meeting ask. What happens between that moment and committing to delivery determines whether you succeed or scramble.
- ✕A Slack message lands: "can we improve mobile checkout before Q3?" — vague, no owner, no success metric
- ✕You spend an hour extracting a real ask from three threads and a meeting note
- ✕You commit before the scope, owner, and risks are clear
- ✕Two months later: delivery surprises that could have been caught at intake
- ✕You prep a leadership update from scratch, again, every week
- ✓The hour of digging through threads is gone — the title, problem, outcome and scope are already drafted for review
- ✓Review and edit structured fields, with AI available inline for any weak field
- ✓Spot the gaps before committing: missing owner, unclear outcome, no out-of-scope
- ✓Mark it shaped and export a one-pager ready for the VP review
- ✓Every demand captured the same way — searchable and auditable
From a vague request to a clear decision — in three steps.
Not a capture tool. AI surfaces what's missing so you decide with eyes open — before you commit people, budget, or a date.
Capture the request
Paste any raw ask — a Slack message, an email, a leadership note. AI drafts it into a structured demand in seconds. If it's too thin to act on, you get two questions instead of a silent bad ticket — that's the point.
Clarify what's missing
The clarification brief separates what you know from what AI assumed — and the high-impact questions to answer before committing. Add what you find out, or send it to a time-boxed discovery.
Decide what happens next
With the delivery risk in front of you, decide: plan, commit, pause, or decline. Share a leadership-ready one-pager when you do.
And then all the way to the close
A demand walks one line. Small work skips the heavy steps; nothing skips the decision or the close.
- CapturePaste the ask as it arrived
- ShapeTurn it into something decidable
- DecidePlan it, explore it, park it or decline it
- PlanWho does it, what blocks it, what could go wrong
- CommitLock the baseline you will be measured against
- DeliverCheck in against the promise
- LearnClose it with what actually happened
Where this sits next to Jira or Linear
DeliverySheet runs the part before the tracker — the raw ask, what's still missing, and the decision to commit. Today it doesn't replace Jira or Linear: the ticket is still what you write once that decision is made. What it adds is the record of why you committed, which no tracker keeps. The full comparison →
What it actually looks like
Built for engineering and product leaders.
Engineering Managers, Directors and VPs of Engineering, and Product Managers. If you receive demands, shape work, and report upward — this is for you.
Built by one person who spent 18 years on the other side of this problem.
I'm Tan Gravam. Eighteen years in SAP, treasury and enterprise systems — now turning recurring problems into focused software, from Amsterdam. DeliverySheet exists because I kept watching teams commit to work nobody had made clear yet, and no tool would tell them what was still missing before the commitment was made.
It's a small product with a narrow promise, and I answer the support email myself — tan.gravam@gravam.com.
Why the product is built this way
Every constraint in DeliverySheet came from an argument I'd rather have in the open. These are the arguments.
- Turning a request into something you can decide on
Requests arrive as topics, solutions and half-sentences. What has to be added before one can be shaped, decided on, or refused honestly.
- How to decide what to commit to
What has to be true before a request becomes a promise, and what to do with the requests that never should become one.
- Capacity and what to measure
Sizing work in a unit that survives a budget meeting, and measuring what people are committed to instead of what they spend.
- After the commitment: tracking, closing and learning
What happens once the promise is made — status that says something, an outcome that is not just done, and a retrospective that is not theatre.
- Planning that stays honest
Separating fact from assumption, modelling cross-cutting work as what it is, and knowing exactly where AI belongs.
The short answers
- What is DeliverySheet?
- DeliverySheet is a demand-intake and delivery-governance tool for engineering managers. It turns a raw work request into a decision-ready demand — the problem, the outcome, an owner, capacity in FTE-months, dependencies and risks — and keeps a record of what was committed and what actually happened. It is not a task tracker.
- Who is DeliverySheet for?
- Engineering and delivery managers in product and engineering organisations of roughly 50 to 1,000 people, where requests arrive from Slack, email, leadership and customers, and one person has to decide what actually gets promised.
- Does DeliverySheet replace Jira or Linear?
- No. It owns the decision before the ticket — whether a request is understood, owned, sized and unblocked enough to promise. Day-to-day execution stays in Jira or Linear. There is no integration today, so a committed demand is written up in your tracker by a person.
- How much does DeliverySheet cost?
- $189 per workspace per month, tax-inclusive, with unlimited members and demands. The 7-day free trial needs a card and nothing is charged if you cancel before it ends. If a subscription lapses the workspace becomes read-only; data is never deleted.
- Can I try it without a card?
- Yes, partly: the free request check shows whether a request you paste states the need, the impact and why now, and which questions to send back. The full lifecycle — shaping, deciding, planning, committing, tracking and closing — needs the trial.
- What does the AI do, and what does it not do?
- It drafts structured fields from the text you paste, asks for what is missing, and suggests next steps. It never decides: every owner, plan and commitment is confirmed by a person. Processing runs server-side through the Anthropic API, which does not train on API inputs by default.
Shape your first demand today.
Paste a real ask from your backlog. You get a structured demand back — or the two questions that turn it into one. Takes two minutes.
$189/mo per workspace · Card required · Cancel any time during the 7-day trial to avoid being charged