04 kinds of work · fixed scope, audit or retainer

Services.

I take a few projects at a time. The person you email is the person who writes the code, deploys it, and gets paged for it.

1. 01

   Kubernetes & GitOps platforms

   Every change goes through Git, every pull request gets its own copy of the app, and the pipeline catches mistakes before production does. It is the setup I run at home for 12 apps.

   ProofK3s homelab platform →

   What you get

   • K3s or managed Kubernetes with Flux GitOps
   • Review apps per pull request, dev/QA/prod promotion
   • Postgres with backups, TLS, sealed secrets
   • Prometheus, Grafana, logs and alerting

   Typical engagement

   Fixed-scope build or audit of an existing cluster, then optional ongoing support.

2. 02

   Django & Python web apps

   Django apps with real tests, migrations checked in CI, and privacy and multi-tenancy designed in from the first model.

   Proofr12d →

   What you get

   • Django apps from MVP to multi-tenant SaaS
   • Auth, billing hooks, admin back office
   • Test suites that guard the rules that matter
   • Containerised, deployed and monitored

   Typical engagement

   Fixed-scope build, or a retainer to extend and maintain an existing app.

3. 03

   Data pipelines & scraping

   Scrapers that assume the source will change. Scheduled jobs, validation, a saved snapshot of every failure, and clean data in Postgres or your warehouse.

   ProofWARN Index →

   What you get

   • Scrapers for HTML, PDF, CSV and hostile sites
   • Validation, de-duplication and failure snapshots
   • APIs, exports and dashboards on top
   • Alerting when a source breaks

   Typical engagement

   Fixed-scope pipeline build, plus optional monitoring and repair.

4. 04

   AI & LLM integration

   LLMs where they actually help: enrichment and extraction with a confidence score on every answer, agents that hand a human a pull request to review, and costs you can predict.

   ProofWARN Index enrichment →

   What you get

   • LLM enrichment and extraction pipelines
   • Agent workflows that end in a reviewed PR
   • Evaluation against real data before rollout
   • Rate limits, retries and cost controls

   Typical engagement

   Short discovery to find the right use case, then a fixed-scope build.