For engineering leaders
AI-native development for engineering teams, done safely. I roll out Cursor and Claude Code, train developers, and rebuild review and CI/CD around AI-generated code so output stays fast and trustworthy in production.
+25% developer productivity, measured against a pre-engagement baseline across 5+ teams.
+25%
developer productivity across 5+ teams
5+
companies advised
millions
events evaluated (Dashly)
6+
years shipping production code
Six focused engagements, from curious about AI tooling to shipping AI-assisted code safely.
Cursor and Claude Code set up across your teams with shared rules, prompts, and project context, so every developer starts from the same baseline.
Cursor and Claude Code set up across your teams with shared rules, prompts, and project context, so every developer starts from the same baseline.
Hands-on sessions on driving AI tools against your real codebase, not toy examples.
Pipelines restructured so AI-generated changes are tested, typed, and verified before they reach main.
A review process built for AI-written code, so larger, faster diffs still get human and automated scrutiny.
Evaluation and classification systems that catch bad AI output before users do : the same approach I used on millions of chatbot events at Dashly.
Find what makes AI assistance unreliable in your codebase, then prioritise the fixes that unlock the biggest gains.
AI ships far more code, far faster : the speed can't cost you reliability. Every engagement leaves behind the review, CI, and evaluation systems that keep AI output safe in production.
A review process for larger, faster diffs : human checklists plus automated review, so AI-authored changes still get real scrutiny.
Pipelines tuned for the volume AI tooling produces : tests, types, and checks catch regressions before anything reaches main.
Merge gates on linting, types, and tests, plus dependency and security checks : faster output never lowers the bar.
Evaluation and classification systems for AI-driven features, drawn from evaluating millions of chatbot events at Dashly.
An open-source hiring marketplace where the ranking is the product: jobs surface the right candidates, candidates surface the right jobs, and both sides are scored by the same rules. Built as a reference for search that gets measured instead of guessed at.
Not a portfolio from three years ago — this is the last six months.
4,025
Contributions
773
PRs
53
Week Streak
1
Day Streak
Does not include automated bots, issue resolvers, or software factories.
Flexible options to meet your project needs and budget
For standard projects with flexible timelines
For time-sensitive projects with specific deadlines
Pay per deliverable, tailored specifically to your business goals
Expert guidance for AI transformation initiatives
Scope, price, and turnaround settled before we start. Pick one, or ask for something in between.
Running agent server
Your own coding agent server, set up on your machine with your keys and ready by end of day.
Findings, then the setup merged
20 h × $80/h
I go through your repo the way an agent has to, then build the missing pieces, so coding agents follow your conventions instead of inventing their own.
CLAUDE.md and AGENTS.md rules, skills, and reusable workflows, mergedAgent server, phone-controlled
The same agent server plus Telegram control, so you can start and steer runs from your phone.
Eval suite running in CI
32 h × $60/h
A test set and scoring harness for a prompt already in production, so you can change it without guessing.
One day, up to 10 developers
12 h × $140/h
One day with your team on your own codebase, setting up the tools and the rules the way I run them day to day.
Standing advisory access
10 h × $140/h per month
Async access and a weekly call for a founder or engineering lead who needs decisions checked and blockers cleared.
Tell me about your codebase and where your team is with AI tooling. I will map out how to roll it out and keep the output production-safe.
Book a free call