Agents do the work. Engineers own the outcome.
Traditional agencies sell hours, so a slower project earns them more. We sell the finished result at a fixed price. That only works because AI agents now do much of the repetitive work in a software project, while senior engineers make every decision that matters.
Who does what.
The split on every project, whether it is a new product, an AI workflow or a platform implementation.
| Task | Done by | Human check |
|---|---|---|
| Turn workshop notes and calls into written requirements | Agents | Engineer checks every requirement with you |
| Draft configuration, code and data mappings | Agents | Engineer reviews each change before it ships |
| Generate test cases and run them on every change | Agents | Engineer decides what “good enough” means |
| Write documentation and weekly updates | Agents | Engineer signs them off |
| Architecture, trade-offs and anything touching money or security | Engineers | Always human |
| Talking to you, agreeing scope and price | Engineers | Always human |
Why selling results changes everything
Companies spend far more on services than on software. Sequoia puts it at six dollars on services for every dollar on software. Most of that money pays for hours: people writing requirements, configuring systems, writing code and testing it.
When AI can do much of that work, the hourly model stops making sense for the buyer. You should pay for a system that works, and the provider should carry the risk of how long it takes. That is the deal we offer: a fixed price for a working result, delivered by a small senior team with agents doing the heavy lifting.
It is the same idea behind the implementation firms the largest AI companies launched in 2026. We bring it to startups and growing companies, which those firms don’t serve.
What you can hold us to.
One fixed price
Agreed in writing before work starts. Changes are priced before they begin, never absorbed into a bill later.
Working software every week
A staging link or a sandbox you can click, and a short written update, every week.
Your accounts from day one
Code, platforms, cloud and AI provider accounts belong to you, not to us.
Measured, not demoed
Every AI workflow ships with a test set and a score. Every release runs its tests.
A named engineer owns it
One senior engineer is accountable for your project from the first call to go-live.
Honest fit
If we are the wrong team or the wrong price, we say so on the first call.
Where we apply it.
Questions, answered.
What does AI-native implementation mean?
It means AI agents do the repetitive parts of delivery and senior engineers do the judgement. You buy the finished result at a fixed price, instead of paying for hours.
Does AI write all the code?
No. Agents draft a lot of it, plus tests and documentation. Every change is reviewed by an engineer, and architecture, security and anything touching money is done by people.
Why does this make the price lower?
Most of the hours in a traditional project go into repetitive work: writing up requirements, configuration, boilerplate code, test scripts and documents. Agents do much of that, so the same result takes fewer paid hours.
Is my data used to train AI models?
No. We use AI providers under settings that exclude your data from training, and keep sensitive data in your own accounts where possible.
Tell us what needs to work.
A product, an AI workflow or a platform. Tell us in a few lines and get a fixed price within 24 hours.
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