AI Feature Sprint · From $24,000 · two to three weeks, quoted before it starts
Ship an AI feature people actually use
AI features die two ways: a demo that never ships, or a shipped thing nobody trusts. A fixed sprint to design and build one AI feature into your product: the interaction, the prompts, the failure states, and the eval that says whether it is good. One senior owning design, prompt, and production code, so there are no seams.
Or book a 20-minute call first. No pitch, just fit.
01
No seams between design, prompt, and code
Most AI features fail where the designer, the prompt engineer, and the developer hand off. Here one senior owns all three, so the model's behavior and the interface are one decision.
02
Failure states designed first
Empty, slow, wrong, and uncertain are designed before the happy path, because that is where AI features lose trust. Citations, confidence, undo, and a human in the loop where it matters.
03
A latency and cost budget
The feature is shippable, not just impressive on stage. Model choice, streaming, and caching are decided against a budget you can run at scale.
Receipts
AI shipped into real products.
Each opens the case study.
What ships
One feature, end to end.
The fit call picks the one feature worth shipping and the failure modes that matter. The number is fixed before anything starts.
Designed
- The interaction. Input, streaming, edit, retry, and the empty and error states.
- The trust layer. Citations, confidence, undo, and human-in-the-loop where it matters.
- The prompt strategy. System and tool design, with what good output means written down.
- The budget. Latency and cost per call, decided before the model is.
Built
- Production code. In your stack, typically Next.js and React, as pull requests.
- An eval harness. A test suite for output quality, run before ship and kept in your repo.
- Model wiring. The latest Claude or GPT models, chosen per task, with fallbacks.
- Handoff. Your team keeps the evals, so the feature stays honest after I leave.
Pricing
One feature, or the team.
AI Feature Sprint
From $24,000
Two to three week fixed sprint, quoted before it starts. One feature, shipped.
- One feature, designed end to end with its failure states
- Prompt and tool design with an eval harness
- Production code in your stack
- A latency and cost budget honored
- The eval suite handed off
Teach the team first?
From $5,000
The AI Workshop: a half-day or two days on your real projects, so your team ships with AI after I leave.
- Hands-on, on your real backlog
- The tool landscape, opinionated
- Prompting and eval basics your team keeps
- A written playbook
How it runs
Two to three weeks, fit call to shipped.
01
Day 0
Fit call
Thirty minutes to pick the one feature worth shipping and the failure modes that matter. The number is fixed here.
02
Week 1
Map
The interaction, the prompt strategy, and what good output means, written down as evals before any code.
03
Weeks 2 to 3
Build
UX, prompts, and evals built together against the latency and cost budget. Pull requests in your repo.
04
Ship
In production
The feature live, the eval suite green and handed off so your team can keep it honest.
Fit check
Built for some, not everyone.
This is for you if
- A funded product adding its first real AI feature
- A team with a demo that won't survive real users
- Founders who want it shipped, not slideware
Not built for
- Pure research with no product to ship into
- A full AI platform. That's a team, not a sprint
Built with these models every day
Artyom Sklyarov
I design the UX, write the code, and write the prompts, so the model's behavior and the interface are one decision. The tools on this site are AI-shaped, and the products in the receipts above ship AI to real users. This is not a slide deck about the future of AI; it is how I work.
The fit call is the scope. If the feature is not worth shipping, I say so on the call.
AI Feature Sprint · From $24,000
Tell me about the feature.
Name, email, and the feature in a few lines: what it should do, where it lives, and what worries you about it. I reply within 24 hours with a fit read.
The fine print
Questions, answered.
The latest Claude or GPT models, chosen per task. I build with them daily and pick by what the feature actually needs.
A test suite for model output quality: run before ship so 'is it good' has an answer, not a shrug.
One feature, clear scope. The fit call sets the number before anything starts.
From $24,000 for one feature designed, built, and shipped with its eval suite, in two to three weeks. The exact number is fixed on the fit call and does not move after.
Read access to the product and the repo, one person who can answer product questions the same day, and a decision on what good output means by the end of week one. Everything else is on me.
01 / 05
Which models?
The latest Claude or GPT models, chosen per task. I build with them daily and pick by what the feature actually needs.
Ready? Request a fit call. The eval suite is part of the deliverable, so you will know it is good before your users do.