July 6, 2026
6 Weeks to Production: How m00labs Ships AI MVPs at Fixed Price
$25,000. 6 weeks. Production deployment on week 6. No scope creep surcharges, no hourly billing, no discovery-phase invoice that produces a PDF you could have written yourself.
Most agencies quote 3–6 months for an AI MVP. The tools and models change inside that window. A 6-month build that started with one model version ships against a landscape that already moved. Speed is not about saving money. It is about shipping before the market shifts.
What 3–6 months actually costs
Traditional agencies quote 3–6 months for an AI MVP (Chrono Innovation, 2026). During that window three things happen.
First, the AI tooling changes. The model you picked in month 1 is not the best model by month 4. Reranking strategies evolve. Vector databases get faster. Embedding models improve. Your agency's original architecture is already stale before the first user touches it.
Second, scope creep compounds. 85% of projects that experience scope creep exceed their initial budgets, averaging a 27% cost overrun (AMPRG, 2025). On a $50,000 engagement, that is $13,500 of unbudgeted spend. Hourly billing makes this the agency's revenue model — every scope clarification is billable, every "quick question" increments the invoice.
Third, you do not see working software until the end. Month 4 demo. Discover it is wrong. Change order. Month 5 rebuild. Month 6 launch panic. You burned a quarter of the year and got one shot at getting it right — and you missed.
80% of AI projects fail to deliver intended business outcomes (Gartner, 2025). The failure is not a dramatic crash. It is the quiet accumulation of demos that never became products and budgets that evaporated into billable hours.
The 6-week sprint calendar
m00labs ships on a fixed 6-week timeline. Here is exactly what happens each week.
Scope lock and architecture
We define exactly what ships. No vague requirements document. A locked scope with acceptance criteria per feature. Architecture decisions: model selection, data pipeline design, infrastructure choices, API surface. You approve the plan on Friday. Nothing enters the build unless it is in the scope document.
Live staging with core AI pipeline
The AI pipeline goes live on a staging environment. Real models, real data, real API calls. Not a mockup. Not a Figma prototype. You interact with the product by Friday. If the core AI behavior is wrong — wrong model for the task, bad prompt engineering, hallucination surface too large — we catch it here, not in week 5.
Feature build sprint 1
Primary user flows take shape. Authentication, data ingestion, the core interaction loop. Friday demo shows working features. Not slide decks. Not roadmap updates. Working software.
Feature build sprint 2
Full feature set implemented. Edge cases handled. Error states designed. Testing covers both the happy path and the failure modes. Friday demo is the complete product — every feature in the scope document is functional.
Hardening and testing
Load testing, security review, prompt injection testing, production environment provisioning. Automated test suite validates every feature. No new features enter this week — only fixes.
Production deployment
The product goes live. DNS, SSL, monitoring, alerting configured. You get deployment documentation and a handoff session. Not a ZIP file and a "good luck." A live product your users can access.
Compare this to the traditional agency cadence: discovery (4 weeks), design (4 weeks), sprint 1–3 (6 weeks), QA (2 weeks), deployment (1 week). Total: 17 weeks. Four months. In that time, you shipped nothing while m00labs shipped three complete MVPs.
Weekly demos prevent the month-4 disaster
Founders at traditional agencies see the product at month 4 and discover it is wrong. The agency built what was specified — and the specification was wrong. Nobody tested it against real users for 120 days.
m00labs founders see the product every Friday.
Week 1: architecture review. Week 2: core AI pipeline working on staging, real inputs producing real outputs. Week 3: primary user flows functional. Week 4: complete product. Week 5: hardened and tested. Week 6: live in production.
If something is off at the week 2 demo, we fix it in week 3 — not in a change order at month 5. The fixed-price model does not penalize course correction. The agency that bills by the hour earns more when the project drags on. m00labs earns the same whether it takes 6 weeks or 8. The incentive is to ship, not to bill.
This matters more for AI products than traditional software. AI behavior is probabilistic. You cannot spec it perfectly in a requirements document because you cannot predict how a language model will behave on every input. You need to see it working, test it on real inputs, and iterate. Weekly demos make this possible. Quarterly demos make it impossible.
Fixed price means fixed price
m00labs pricing:
No discovery phase invoice. No hourly billing. No scope creep surcharges on things that should have been caught in week 1. If the scope changes mid-build, we handle it with a transparent change request — priced before work begins, not after.
The alternative is time-and-materials: the agency bills by the hour regardless of outcome. Fixed-price contracts put the risk of cost overruns on the vendor. Time-and-materials puts it on the client (Faberwork, 2025). For an MVP — where speed and budget certainty matter more than infinite flexibility — fixed price is the rational choice.
Who this is for
Founders who need an AI product shipped, not a discovery document. Teams that have raised pre-seed or seed funding and need a working product to show users, not a roadmap to show investors. Companies that need AI capabilities in their existing product and do not want to hire a 4-person ML team to get there.
If you need a 14-week enterprise RFP response with a dedicated project manager and weekly TPS reports — we are not your agency.
If you need an AI MVP that works, ships on week 6, and costs exactly what we said it would cost — email hi@m00labs.com.
Sources: Gartner AI project failure rate (2025). AMPRG "The Nightmare of Scope Creep" (2025). Chrono Innovation "MVP Development for Startups: The 2026 Guide" (2026). Faberwork "T&M vs Fixed Price: A CTO's Guide" (2025). m00labs internal sprint methodology.