Ship It Live — $1,999 flat
Design + build + deploy · kickoff in 24h · limited slots
Ship It Live · AI agent sprint
An AI agent that does the work, live in 21 days.
Not a chat box — an agent that reads, decides and acts in your systems, with a human able to see and stop everything it does.
Quick answer
An AI agent that takes real actions in your own tools can be built and running in 21 days from a fixed $1,999. That covers the task definition, tool integrations, an approval step on anything consequential, run logs and a review interface. An agent with no human checkpoint is not something I will build.
The plan
Day one to day 21, written down.
You get this schedule before you commit, not after. If a phase slips, that is mine to absorb — the price and the date were agreed before anything started.
- 1
Days 1–3
Pick the task
The narrowest valuable loop, its inputs, and what a wrong answer costs. Agents fail when the task is vague, so most of the risk is removed here.
- 2
Days 4–9
Design the loop
The decision points, the approval gates, and what the human sees. Designed on paper before anything is wired to a live system.
- 3
Days 10–16
Build
Tool integrations, the agent loop, logging and the review interface. Run against real data in a sandbox where nothing it does is permanent.
- 4
Days 17–19
Shadow mode
It runs on real work but only proposes — a human approves everything. This week tells you how often it is right before it can be wrong at your expense.
- 5
Days 20–21
Launch
Selected actions unlocked with approval still in place on the rest, monitoring on, and a clear kill switch.
What from $1,999 gets you
Everything needed to launch — nothing padding the invoice.
Who books this
Built for
Teams with a repetitive process that is judgement-heavy but low-stakes
Operations doing the same research-and-update loop dozens of times a day
Founders who want agents doing work, not demos of agents doing work
Real situations
Five ways this shows up, and what actually fixes it.
Not hypothetical — the shape of the problem before someone books this sprint, and the specific part of the build that resolves it.
Situation 1
Doing the same research-and-update loop dozens of times a day
An operations team repeats a judgement-heavy but fundamentally low-stakes research-and-update cycle many times daily, consuming hours that could go toward higher-value work.
That narrow, well-defined loop gets automated with an approval step on anything consequential — a real agent doing the work, not a demo of one.
Situation 2
Wants agents doing real work, not another chatbot demo
A founder has watched multiple 'AI agent' demos that look impressive but never actually complete a real task inside their own systems.
A narrowly defined task with real tool integrations — CRM, sheets, inbox, database — ships in 21 days, doing the work rather than demonstrating it.
Situation 3
Afraid of an agent doing something consequential unsupervised
A team is interested in AI automation but hesitant to give any system unsupervised access to actions that could cost money or damage a customer relationship.
An approval step on anything consequential is a hard requirement of the build — nothing irreversible happens without a human checkpoint, ever.
Situation 4
No visibility into what an automated system actually did
A previous automation attempt worked, mostly, but left no record of what it saw, decided, or changed, making it impossible to audit after the fact.
Full run logs capture what it saw, what it decided and what it changed, with a review interface so a human can inspect, correct and re-run.
Situation 5
Worried about a runaway process quietly racking up costs
A team considering agent automation is concerned that an unattended loop could spiral in cost without anyone noticing until the bill arrives.
Rate limits, per-run token budgets and a spend cap are part of the build, with the API key held by the client so spend is visible directly.
The honest part
When 21 days is the wrong answer.
A fixed deadline only works when the scope genuinely fits inside it. These are the cases where I will tell you so rather than take the booking.
Fully autonomous agents acting on money, contracts, customers or production infrastructure without a human checkpoint. I will not build that, and you should not want it yet.
Agents whose task nobody can describe precisely. If two people in your team define the process differently, we settle that first.
Replacing an entire role. A good agent takes a defined loop out of a job; anyone selling you the whole job is selling you a rebuild in six months.
Inside the 21 days
- A narrowly defined task the agent is actually good at
- Tool integrations — your CRM, sheets, inbox, database, or internal API
- An approval step on anything consequential, before it happens
- Full run logs: what it saw, what it decided, what it changed
- A review interface so a human can inspect, correct and re-run
- Guardrails: what it may never touch, and when it must stop and ask
- Cost controls and rate limits, so a loop cannot quietly spend thousands
- Source code, prompts and configuration yours at handover
Quoted as one number before day one. A week running long is mine to absorb.
Outside the line
- Fully autonomous agents acting on money, contracts, customers or production infrastructure without a human checkpoint. I will not build that, and you should not want it yet.
- Agents whose task nobody can describe precisely. If two people in your team define the process differently, we settle that first.
- Replacing an entire role. A good agent takes a defined loop out of a job; anyone selling you the whole job is selling you a rebuild in six months.
Real work, sized and priced separately. You hear it before you book, not at handover.
Questions
Before you book
A chatbot answers; an agent acts. It reads from your systems, decides, and writes back — creating records, sending drafts, updating fields. That is why approval gates and logs matter far more here than in a chatbot.
Task charter (what the agent owns / where it stops)
An agent sprint is for a bounded task with a human on the consequential step — not unsupervised autonomy cosplay.
Write the charter before tools
The agent owns [task] using [inputs / systems]. Done-when looks like [observable outcome]. It must not do [out of bounds] without a named human approval.
If you cannot fill that without saying “it just figures it out,” you do not have an agent yet — you have a demo with permissions.
| Belongs in this 21-day sprint | Becomes a different project |
|---|---|
| One reversible first job | Open-ended “run the company” |
| Propose → review → act path | Skip-the-human forever |
| Named approval owner | Shared inbox with no owner |
| Spend ceiling written down | Unlimited keys on a shared card |
Sibling: if the deliverable is a user-facing product around one job (with uncertainty UX + evals), see /shipitlive/ai-app-in-30-days. If it is a billable SaaS workflow with light AI, /shipitlive/saas-mvp-in-30-days may be the sharper slug.
Shadow mode as a hard gate
The live page already says consequential actions need a human checkpoint. Make the gate checkable.
Definition
Shadow mode: the agent proposes; a human executes — until exit criteria are met. It is not optional theater for week one.
Exit criteria (leave shadow only when these pass)
| Gate | Pass looks like |
|---|---|
| Task charter | Written, shared, no “and then anything else” |
| Reversible first job | Failure does not burn money or customers by default |
| Review path | Named human can approve / reject in one place |
| Action log | Every run leaves a readable trail (see below) |
| Kill switch | Named owner who can stop runs |
We do not claim unsupervised autonomy after day 21. Soft autonomy: scoped tools, approvals on consequential steps, human ownership of the kill switch.
Action log + spend ceiling
“Run logs” on the page are not a vibe. After each run, a human should be able to answer three questions without digging through provider dashboards alone:
- What did it see? (inputs / context summary)
- What did it decide? (proposal or action)
- What changed? (writes, drafts, skips)
Spend as a done-when (process, not a vendor promise)
- Hard spend ceiling or per-run budget in the product or provider account you control
- Alert path when spend spikes
- What happens when the ceiling hits (pause, queue, message)
- API key held by you at handoff so spend stays visible
We do not invent runaway-bill dollar figures here. The fear on this page is real; the fix is a written ceiling and a named kill-switch owner — not a scary number we made up.
Tool access (email, CRM, sheets): least privilege for the charter job only. Exact connectors are scoped on the call — no invented integration list in this insert.
Extra questions
Existing FAQ already covers chatbot vs agent, cost, what if it does something wrong, tools, schedule, spend, and ownership.
AI agent vs AI app — which page?
Who publishes / who can approve consequential actions?
Can it get email / CRM access in the same sprint?
Is day 21 a guarantee the agent never does the wrong thing?
Other sprints
21 days from now, this could be live.
A 30-minute call decides whether the scope fits. If it doesn't, I'll tell you what would.