Services

What does your product need next

Three problems I get hired for. Pick the one that sounds like your week — how the work runs, and what it costs, comes after.

Start a projectSee the work

01

Build a product

You need real users on a real product before the window closes.

What this involves →

02

Make AI reliable

The demo works. Production is a different question.

What this involves →

03

Fix and scale a system

Delivery is slowing down, or you are one incident from a bad week.

What this involves →

How the work runs

Three ways to engage

Which one fits depends on the problem. A diagnostic needs something that already exists to measure — a running system or an AI workflow in production — so a product being built from nothing starts as a delivery project or an embedded month. Everywhere else, start with the cheapest mode that answers the question.

Diagnostic sprint

From $1K

From 3 days

A fixed-scope, fixed-price review of one system. It covers how it performs under load, how it fails, and where it is exposed. You get a written report: what I found, ranked by what will hurt first, with the evidence behind each finding and the direction I would take to fix it. You own the report — if you hand it to your own team and implement it without me, that is a good outcome and I will say so on the call.

Best for Anyone who needs a decision backed by evidence before spending a build budget.

What the floor covers For a system: one codebase, one running site or app, and the infrastructure under it — hosting or VPS, storage, database, and the paths between them. For an AI workflow: the pipeline and its prompts, a representative slice of your own data, traces and outputs from real runs, and whatever evaluation you have today. Either way it is one thing, not an estate: if you run a dozen services across several teams, the sprint takes the one that worries you most and we agree what is in it before it starts.

What I need from you Read-only access to the codebase and the infrastructure — plus real traces and a representative data sample if it is an AI workflow, since there is nothing to measure without them. Nothing else: I do the reading myself, so no walkthrough sessions and no standing meeting with your engineers.

Delivery project

From $5K

MVPs 3–6 weeks; AI and architecture work scoped to complexity

Fixed scope and fixed price wherever the requirements are clear enough to define, which puts the estimation risk on me rather than you. Weekly demos, so direction is steered while it is cheap to steer. An overrun is my cost; a scope change is re-quoted before the work, never after.

Best for Work with a definable end state, where you want a number you can plan against.

Embedded engineering

From $5K/month

From 1 month, flexible

I join your team as a senior or lead engineer: in your Slack and your standups, writing code in your repo, reviewing PRs against your standards, and mentoring where it helps. You get direct access to me rather than an account manager, and I raise risk and tech debt when I see it rather than at the end. Start with a month; extend only if it is working.

Best for Teams that need experienced hands now and cannot wait on a twelve-week hiring cycle.

01

Build a product

Your technical co-founder, temporarily.

Runs as
Delivery project · Embedded engineering
Proof
Invygo: MVP live in 6 weeks, $5M raised aftercase study

I take an idea to a production MVP: lean architecture, the features your first users actually need, and no scaffolding for a scale you do not have yet. It is designed to evolve as you learn rather than to be thrown away at the first real traffic — what you build after that depends on what those users tell you, and I would rather scope the next step honestly than promise you never rewrite anything.

Best for Founders who need a live product with paying users, fast, without hiring a team first.

Not for Teams who already know exactly what to build and need delivery volume rather than product judgement. You want more engineers, not me.

What's included

  • Technical architecture design
  • Full-stack development
  • Cloud infrastructure setup
  • CI/CD pipeline
  • Launch support & monitoring

How it runs

  1. 01We talk through the idea: I challenge assumptions, you sharpen the vision
  2. 02I design lean architecture that ships in weeks, not months
  3. 03Weekly demos: you see progress, steer direction, no surprises
  4. 04Launch day: deployed, monitored, and ready for real users
Talk about build a product →

02

Make AI reliable

AI that holds up under real traffic, not just in the demo.

Runs as
Diagnostic sprint · Delivery project · Embedded engineering
Proof
Writing: RAG does not enforce groundingwriting

RAG pipelines, agents, embeddings and LLM integrations built for real traffic. Getting a model to answer is the easy part. The work is knowing how often it is wrong, catching it when it is, and keeping the cost predictable: evals against your own data, grounding and abstention checks, guardrails, fallbacks, and monitoring that tells you when quality drifts rather than leaving you to hear it from a customer. Where a model cannot be made dependable enough for the job, I will tell you that instead of shipping it.

Best for Teams with a real data asset and a workflow worth automating, who need it to survive contact with users.

Not for Proof-of-concept demos with no intention of running in production. The evaluation work that makes this valuable is wasted if nothing has to hold up.

What's included

  • AI architecture & feasibility review
  • LLM integration with an eval suite
  • RAG pipeline development
  • Guardrails, fallbacks & cost controls
  • Production deployment and monitoring

How it runs

  1. 01I identify where AI moves the needle versus where it is hype
  2. 02We prototype fast, so you validate against real data before committing
  3. 03Production-grade pipeline: measured, monitored, explainable
  4. 04Knowledge transfer so your team owns what we built
Talk about make ai reliable →

03

Fix and scale a system

Find what breaks first, then fix it.

Runs as
Diagnostic sprint · Delivery project · Embedded engineering
Proof
Yojee: 50% faster, 80% fewer crashescase study

Three questions, answered with evidence rather than opinion: what breaks when traffic multiplies, where the system is exposed, and what takes it down at 3am. A short audit is usually enough to answer them. The design and implementation work that follows is about making sure the answers stop being true — on a migration path that avoids a rewrite wherever one can be avoided.

Best for Teams whose velocity is dropping, or whose system is one incident from a bad week.

Not for Greenfield work with nothing running yet. There is no system to measure, so an audit would be opinion dressed as evidence.

What's included

  • Scalability and bottleneck audit
  • Security review and threat modelling
  • Reliability, failover and incident review
  • System design & documentation
  • Migration plan that avoids a rewrite

How it runs

  1. 01A short audit finds the bottlenecks, exposures, and single points of failure
  2. 02You get a written findings report, ranked by what will hurt first
  3. 03I design the target architecture and a migration path that avoids a rewrite
  4. 04I implement the critical changes hands-on, not just diagrams
Talk about fix and scale a system →

Questions

Before you ask

Not sure which one you need

Most people aren't. Send me the situation, or book thirty minutes, and I'll tell you which of these fits — or that none of them do.

Start a project