Engineering standards

Fast is a scoping decision. The standard does not move.

The usual worry about a 21-day build is that someone pays for it later. Here is what ships with every project regardless of the timeline, who is accountable for code an AI helped write, and why a studio that repairs broken builds for a living does not ship them.

Talk to the engineer who would build it What happens after launch

Non-negotiable

What ships with every build, on any timeline

We narrow what the first version does. We do not narrow how it is built.

Code review before anything merges

Every change is reviewed by a senior engineer before it reaches production. This is true on a 21-day build and on a twelve-month retainer. It is the one step we do not compress.

A test suite covering core business logic

Our latest SaaS build, Loopwave, ships with 110 passing API integration tests. Tests are the safety net that makes a handover survivable, so they are written inside the timeline, not after it.

Dependency and vulnerability scanning in CI

Automated on every build. Secrets stay out of source control and are rotated at handover, and every environment gets its own least-privilege credentials.

Documented, readable handover

Code, docs and a walkthrough so your team, or your next developer, can run and extend it without us. You own the repository, the infrastructure and every account from day one.

Where AI fits

AI accelerates the work. A senior engineer owns every line that ships.

We use AI aggressively and say so openly. The rule underneath it does not bend: nothing merges on a model's say-so.

AI-assisted scaffolding

We generate boilerplate, structure, and first-draft implementations in hours, so engineers spend their time on architecture and hard logic, not plumbing.

Rapid prototyping

We stand up working prototypes fast so you react to something real, early, killing bad assumptions before they get expensive.

Automated test generation

We use AI to draft comprehensive test suites and edge cases, then a senior engineer reviews and hardens them. (A 2025 METR study found devs felt 20% faster with AI while actually being 19% slower, so we measure the real gain, not the feeling.)

AI-augmented code review

Every change passes AI-assisted review for bugs, security, and consistency, and then a human senior engineer. AI widens the net; the engineer makes the call. Nothing merges on a model's say-so.

Living documentation

We use AI to keep docs, API references, and architecture notes current as the code evolves, so you're never handed a black box you can't maintain.

Why this is engineering, not marketing

The demo is about 10% of the work

These are the failure modes we design against. Each one is documented by an independent source, not by us.

Models make things up

Language models generate plausible text, not verified facts. A 2024 Stanford RegLab study found even purpose-built legal AI tools hallucinated up to 33% of the time, retrieval (RAG) only reduces this when the data, chunking, and ranking are engineered correctly.

You can't test it normally

AI is probabilistic, the same prompt can return different answers, so "it worked when I tried it" proves almost nothing. Reliable AI needs evaluation harnesses, golden datasets, and regression suites, not a one-off demo.

Your data is the real product

The model is a commodity; your data is the moat and the bottleneck. Gartner reports organizations will abandon 60% of AI projects through 2026 that aren't supported by AI-ready data. Cleaning and pipelining that data is most of the work.

Fast, cheap, accurate, pick

Bigger models are smarter but slower and costlier; smaller ones are fast but need scaffolding. Hitting sub-second latency at acceptable cost while keeping quality high is an explicit engineering decision, not a default.

Open systems get attacked

The moment AI can take inputs or trigger actions, it's an attack surface. Prompt injection is ranked the #1 risk in the OWASP Top 10 for LLM Applications (2025). Guardrails, least-privilege tooling, and output validation are mandatory.

Someone is liable for it

"The AI said it" is not a legal defense. In Moffatt v. Air Canada (2024), a tribunal held the airline responsible for wrong information its chatbot gave a customer. Production AI needs real privacy, compliance, and accountability discipline.

Sources

Everything above is checkable

We would rather you verify the claims than take our word for them.

The strongest evidence we have

We run a business fixing other people's shortcuts

App Rescue: founders bring us Lovable, Bolt, v0, Cursor and Base44 builds that broke in production

We build and operate our own live products, including SwiftPatch and NovaX, that we cannot walk away from

Week 4 of the included 30-day programme delivers a written technical debt assessment

You own the code, repository, infrastructure and accounts from day one, not on final payment

If you want the version of this that costs money rather than words, send us a build that is already failing and read the audit we write about it.

FAQ

The questions worth asking any studio

Does a 21-day build mean I inherit technical debt?+

Fast here is a scoping decision, not an engineering one. We narrow what the first version does; we do not narrow how it is built. Code review before merge, a test suite over core logic, CI vulnerability scanning and a documented handover ship regardless of timeline. Week 4 of the included 30-day programme then delivers a written technical debt assessment, so you get our honest read in writing rather than a reassurance.

You use AI to write code. Who checks it?+

A senior engineer owns and verifies every line that ships. AI drafts scaffolding, first-pass implementations and test cases, then a human reviews and hardens them. Every change also passes AI-assisted review for bugs and security before a person makes the final call. Nothing merges on a model's say-so.

How do you know what shortcut engineering actually costs?+

Because we get paid to repair it. App Rescue is a working part of this studio: founders bring us Lovable, Bolt, v0, Cursor and Base44 builds that broke in production, and we trace the payments, webhooks, auth and data before deciding what is salvageable. Six pages of this site document how those apps fail. A team shipping the same shortcuts could not run that service.

Do you maintain anything long term, or only build and hand over?+

We build and operate our own products alongside client work, including SwiftPatch, an over-the-air deployment platform for React Native, and NovaX. Live products we cannot walk away from hold us to the standard we are describing here. For client work, a 30-day scaling programme is included with every build and most founders continue on a $2,999 per month Growth Retainer.

Are you SOC 2 or HIPAA certified?+

No, and we will not imply otherwise. We hold no formal compliance certifications. What we do have is specific and checkable: signed NDAs and clear IP assignment in every engagement, code review before merge, dependency scanning in CI, secrets rotated on handover, and per-environment least-privilege credentials. If a certificate is a hard requirement for your project, an enterprise firm is the safer choice.

Ask us the hard version of these questions

Twenty minutes with the person who would actually write the code. If we are the wrong team for what you are building, you will hear that on the call rather than after the invoice.

Book the call