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Work with me

I review Python services in production and train the teams that run them. Two fixed-scope engagements, remote, run in European working hours.

  • Memory climbs after every deploy, and a restart is the fix.
  • p99 latency creeps up and nobody can say which change did it.
  • Incidents get found by customers before dashboards.
  • AI-written pull requests merge faster than anyone really reviews them.
  • You have telemetry, and still cannot answer "why was it slow at 14:00?"

If two of these sound familiar, there are two ways I can help.

Advisory

Python Production Review

The question it answers
Why do our Python services leak, slow down, or fail, and would we catch it early?
How it runs
Remote, over about two weeks. I read your code, dashboards, and incident history, then go deep on one or two services: their instrumentation, and the review, tests, and CI gates around AI-written changes. It ends with a written report and a 90-minute readout.
You provide
Read access, and 2 to 3 hours of your engineers' time.
You get
Ranked findings and a 30/60/90 day plan your team can act on without me.
Training

Catch It Early training

Who it is for
Up to 12 engineers who ship Python services.
How it runs
Two remote half-days. Hands-on: instrument a Python service, hunt a planted memory leak and a latency bug, then validate an AI-written change with a review checklist, tests, and traces.
You get
The materials and the exercise repo, so the habits outlive the day.
Works well after
A Production Review, using what it found.
Upstream fixA memory leak inside the OpenTelemetry Python SDK, found in production and fixed in the SDK, shipped since version 1.28. The write-up.
600+ hoursof technical training delivered to 63 trainees across four cohorts, rated 4.84/5.
Every dayAs Head of Engineering, I lead a team that ships with coding agents.

Start with an email

Write a few lines about your system and what is hurting. I reply within two working days, we set up a 30-minute call, and I quote a fixed price after it.

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