Sergei Notevskii
I build AI platforms that work in production: LLM, STT, embeddings, agents, inference, evals, observability, cost and ownership. I write Production AI Platform Handbook: a practical map of what starts after the demo.
Practice
Field notes from production AI platform work: sanitized, practical and focused on engineering decisions.
AI platform
LLM · STT · embeddings · agents
Self-hosted inference
vLLM · GPU · routing · cache
Quality
Evals · regression · feedback loops
Economics
Scenario cost · prefix cache · tokens
Public artifacts
Habr · talks · open-source
After the demo
The demo works. Platform questions start next.
The hard part starts after the first successful model call: cost, quality, latency, ownership and operations.
Latency spikes.
Token cost grows.
Prompts break.
Agents get stuck in loops.
Evals are missing.
Nobody owns quality.
At that point, AI stops being a feature and becomes a platform.
Flagship project
Production AI Platform Handbook
A practical handbook for teams moving from API key and demo to production AI platform. Inside: a 12-layer map, chapters, checklists, tools and templates.
12-layer map
From product scenario to owner, cost and operations.
Chapters
Gateway, inference, economics, cache, evals, observability and ownership.
Tools
Prefix Cache Auditor, LLM Cost Calculator and quality checklist.
Templates
Scenario RFC, self-hosted migration, cost review and incidents.
Public work
Public work
Handbook pages, tools, articles and talks that make the platform practice reusable.
Production AI Platform Handbook
A platform responsibility map for teams moving from API key and demo to inference, routing, evals, cost and ownership.
Prefix Cache Auditor
A client-side diagnostic tool for unstable prefixes, dynamic fields, tool schema drift and cache-aware recommendations.
audit-prompt-caching
An open-source diagnostic package for prompt and prefix cache audits: stable layout, volatile fields and cache-aware recommendations.
Writing
Habr articles and Telegram notes
Long-form Habr articles and short Telegram notes.
Talks
Talks and podcasts
Videos and podcasts about model choice, platform strategy and engineering work.
Where I am useful
Where I am useful
Architecture review, platform strategy, talks and practical collaboration.
Architecture review
AI Gateway, routing, cache, inference, evals, observability, cost and ownership.
Strategy session
MaaS vs self-hosted, AI platform maturity, ownership boundaries and first roadmap.
Talk or podcast
A practical conversation about production AI without hype: inference, evals, prefix cache, economics and guardrails.
Collaboration
Handbook, open-source tools, templates and joint public materials.
About the author
Sergei Notevskii
I am Sergei Notevskii, AI Platform Lead. I work across platform architecture, inference, quality systems, observability and AI economics. This site is the public layer of that practice: notes, tools, templates and handbook material without internal details.
A model is replaceable. A platform compounds.
Start with the map
A model is replaceable. A platform is compounding.
The first release is intentionally small: map, maturity model, core platform layers and practical tools.