SaaS MVP development · 30 day sprint
Your SaaS idea, live with real signups and billing in 30 days.
I build it myself. One core feature, signup, Stripe billing and the AI piece your users came for, shipped to production in a 30 day sprint. The code sits in your GitHub from the first commit, and every line the AI drafts gets reviewed by me before it merges.
- 30 day sprint
- Code in your GitHub
- One engineer, no handoffs
Day
30 / 30
The problem
Most MVPs fail by building the wrong thing slowly.
The expensive mistake is not a bug. It is six months of features nobody asked for, paid for before a single user logged in. By the time real feedback arrives, the runway is gone.
A 30 day sprint forces the only question that matters early: will someone sign up, use the core feature, and pay? Everything that does not help answer it waits until after launch.
43%
of venture backed startups that shut down since 2023 named poor product market fit as a root cause.
CB Insights, 2026~13 months
is the usual timeline of a software project reviewed on Clutch, at an average cost of $132,480.
Clutch pricing guide, 202645%
of AI generated code samples introduced a security flaw in Veracode’s tests. AI speed without review is a liability.
Veracode, 2025Scope check
Does your idea fit 30 days?
Pick the core feature and what version one needs. You get a planning estimate against the sprint, and a straight answer on what to cut if it runs over.
Planning estimate
23 build days
- Sprint base13d
- AI that generates from user input7d
- Email or SMS notifications1d
- 1 integration beyond Stripe2d
Fits the 30 day sprint, with 7 days of buffer
Buffer is not padding. It absorbs the questions every real build raises, so the launch date holds.
Planning estimates, not a quote. The scope call turns this into a written plan with a fixed in and out list.
How it runs
Thirty days, five checkpoints, something you can click at each one.
No status reports dressed up as progress. Every checkpoint ends with a link you can open, a login you can try, or a document you sign off.
- 01
Days 1 to 3
Scope and design, signed off before code
Together, you and I pick the one feature that proves the idea and write down everything that waits. I write a short design document: screens, data, billing, the AI piece and what it costs to run per user.
You getA signed scope with an in and out list, plus the design document
- 02
Days 4 to 12
The first real journey, end to end
Signup, the core feature, the result saved, the history page. One complete path through the product, deployed to a staging link you can use from day one of this phase.
You getA staging link where you can sign up and use the core feature
- 03
Days 13 to 21
Billing, the AI piece, and the rough edges
Stripe subscriptions in test mode, the AI feature hardened against bad input, email flows, and a basic admin view so you can see who signed up and what they did.
You getA test mode checkout you can complete yourself
- 04
Days 22 to 26
Security, monitoring and load
A security pass on auth and payments, dependency and secrets scanning, error alerts wired to you, product analytics, and a load test at the traffic you expect at launch.
You getA short launch readiness report with what was checked and what was found
- 05
Days 27 to 30
Launch and handover
Live billing switched on, production deploy, a walkthrough call, and a written guide so you or your next hire can keep building without me.
You getA live product, the repository, and the handover guide
Scrub through the sprint
Day
12 / 30
AI assisted, honestly
What building with AI does and does not buy you
Every MVP shop now says AI makes them fast. The independent evidence is mixed, so here it is both ways, next to the checks that make AI drafted code safe to ship.
What the research says
19%
slower: experienced open source developers took 19% longer with early 2025 AI tools, while believing they had been about 20% faster.
METR, 20254 to 18%
faster in a 2026 follow up with newer tools, an estimate METR itself calls an unreliable signal.
METR, 202630%
of developers report little or no trust in AI generated code. Without strong testing, more AI driven change brings more instability.
DORA, Google Cloud, 202548%
of developers trust AI output when they can easily check it. Only 16% extend that trust to most other tasks.
Stack Overflow Developer Survey, 2026What I do about it
Nothing merges unread
Claude Code drafts, I review every diff. The speed comes from drafting, never from skipping the reading.
Types and tests on every push
Strict TypeScript and tests on the paths that cost money when they break: signup, billing, webhooks.
Scans before launch
Dependency audit and secrets scanning. The launch readiness report lists what they found and what I fixed.
Staging before production
Every change lands on a staging link first, so you click it before your users do.
A budget on the AI feature
Per user limits on model usage, so one heavy user cannot quietly run up your bill.
What ships
What you walk away with on day 30
A production web app
Next.js and TypeScript, deployed to your own hosting account. Not a prototype, not a no code export.
Signup and login
Email and social login, password reset, sessions that survive a security check.
Stripe billing
Subscriptions or one time payments, a customer portal, and webhooks that do not double charge.
The core feature
The one thing your users came for, built properly, including the AI piece if there is one.
Monitoring and analytics
Error alerts that reach you before users do, and product analytics on the events that matter.
Your code, your accounts
The repository, hosting, database and Stripe all live in your own accounts. No license fees, no lock in.
The stack
A boring, proven stack, picked so your next hire can read it
I choose tools a typical engineer already knows. The AI is in how fast I build, not in exotic dependencies you will struggle to staff.
Next.js + TypeScript
The app, typed end to end
Postgres
Your data, in your own database
Stripe Billing
Subscriptions, invoices, customer portal
Auth
Auth.js, Clerk or Cognito, picked per project
Claude and OpenAI APIs
The AI feature, with per user cost tracked
Vercel or AWS
Hosting in your account
Sentry + PostHog
Error alerts and product analytics
Claude Code
How I draft code fast; I review every diff
Your options
Four ways to get an MVP built, compared honestly
Each option trades speed, cost and control differently. Here is how they actually compare for a first version.
| Factor | Working with me | Agency | Freelancer | In house hire |
|---|---|---|---|---|
| Who builds it | Me, start to finish. The person you talk to writes and reviews the code. | A team behind an account manager; seniority varies by project. | One person, quality depends entirely on who you find. | Your hire, once you find and onboard one. |
| Time to first users | 30 day sprint for a scope that fits. | Software projects reviewed on Clutch usually run about 13 months. | Varies; scope tends to drift without a written contract. | Recruiting comes before any code ships. |
| Who owns the code | You, from the first commit, in your GitHub. | Usually you, after final payment; check the contract. | Depends on the agreement and where the repo lives. | You. |
| AI written code | Every diff reviewed by me, plus tests, type checks and scans in CI. | Widely claimed; review practice is rarely shown. | Rarely formalised. | Depends on your team’s practices. |
| After launch | A handover guide so anyone can continue, or I keep building if you want. | A retainer or a new statement of work. | A single point of failure if they move on. | Continuous, at a full salary whether or not there is work. |
Who builds it
- Working with me
- Me, start to finish. The person you talk to writes and reviews the code.
- Agency
- A team behind an account manager; seniority varies by project.
- Freelancer
- One person, quality depends entirely on who you find.
- In house hire
- Your hire, once you find and onboard one.
Time to first users
- Working with me
- 30 day sprint for a scope that fits.
- Agency
- Software projects reviewed on Clutch usually run about 13 months.
- Freelancer
- Varies; scope tends to drift without a written contract.
- In house hire
- Recruiting comes before any code ships.
Who owns the code
- Working with me
- You, from the first commit, in your GitHub.
- Agency
- Usually you, after final payment; check the contract.
- Freelancer
- Depends on the agreement and where the repo lives.
- In house hire
- You.
AI written code
- Working with me
- Every diff reviewed by me, plus tests, type checks and scans in CI.
- Agency
- Widely claimed; review practice is rarely shown.
- Freelancer
- Rarely formalised.
- In house hire
- Depends on your team’s practices.
After launch
- Working with me
- A handover guide so anyone can continue, or I keep building if you want.
- Agency
- A retainer or a new statement of work.
- Freelancer
- A single point of failure if they move on.
- In house hire
- Continuous, at a full salary whether or not there is work.
Shipped, not demoed
Products and systems I have shipped
I was skeptical honestly. We had two other AI consultants before him and both delivered slide decks. Jahanzaib shipped a RAG chatbot wired to our docs. Support tickets dropped 45% in month one and 60% by month three.
What stood out was that everything worked in production. Not just a demo. Monitoring, error handling, fallbacks. He thinks about the stuff that breaks at 2am on a Saturday.
Straight answer
Is a 30 day sprint right for your idea?
A good fit when
- You can describe the one feature that proves the idea in two sentences.
- You want real users and real payments, not a clickable prototype.
- You want to own the code and be able to hand it to your own team later.
- You can give me a decision within a day when a question comes up.
Not the right fit when
- You need a native iOS and Android app in the first version.
- The product only works with three or more user roles on day one.
- Regulated data (health records, card data held by you) is core to version one.
- You are still deciding what the product is. Start with the AI Audit instead.
Questions
What people ask before a build starts
Yes, when the scope fits: one core feature, signup, billing and the basics around them. That is why the first three days are a written scope with an in and out list. If your idea needs more than 30 days, the scope call says so before you commit, and the scope checker on this page gives you a first read.
Related
Tell me the idea. I will tell you if it fits 30 days.
A short call, a straight answer on scope, and a real number. If it does not fit, you leave knowing what to cut or where to start instead.
Book Meeting