Platform Engineering
An internal developer platform — delivery pipeline, environments, standards and a foundation for AI agents.
01 · The problem
Every team builds its own pipeline, its own environments and its own rules. A new service means weeks of setup. A new developer means weeks of onboarding.
For AI this matters twice as much: an agent cannot work where the project doesn't build with a single command and the tests can't be trusted. The platform is the foundation on which AI starts to pay off.
02 · When you need it
- Launching a new service takes weeks
- Teams solve the same infrastructure problems in different ways
- Environments aren't reproducible, and deployments require manual steps
- Agents are planned, but there is nowhere to run them
03 · What we analyze
- The path from commit to production — steps, waiting, manual work
- Environments — reproducibility, cost, provisioning time
- Standards and templates — whether they exist and whether anyone uses them
- Observability and operations
- AI readiness — model gateway, context, agent environment
04 · How we work
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step 01
Assessment
We measure the path of a change to production and the developer experience — where time is lost.
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step 02
Target platform
The minimal set of capabilities that removes the biggest losses — without building a “platform for the platform's sake”.
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step 03
Golden paths
Ready-made paths for routine tasks — a new service, an environment, a deployment.
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step 04
AI layer
Unified model access, a context layer and an isolated agent environment on top of the existing pipeline.
05 · What you get
The exact set of deliverables is agreed after the diagnostic. I don't promise effect figures in advance — they depend on the starting point and are written into the plan as criteria.
- 01An assessment of the current pipeline and environments
- 02A target platform architecture with priorities
- 03Golden paths for common scenarios
- 04AI layer architecture — model gateway, context, agent environment
- 05A phased rollout plan
Related services
Next step
Let's discuss your project
Tell me what is happening with your development and what you expect from AI. I reply personally and suggest a format — a diagnostic, an audit or a consultation.