AI engineering notes that earn their bandwidth

Practical AI engineering for senior developers and B2B teams. Token economics, agent architecture, eval design, and the patterns that decide whether an AI feature ships or stalls.

Roughly twice a month. No hype, no fluff, no recycled news.

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Three things, every issue

Each edition focuses on one or more of these. No filler, no link roundups, no generic AI commentary.

Token economics that hold up at scale

Real numbers from production agents. RTK, prompt caching, model routing, and the cost-per-task math that decides whether an AI feature ships.

Agent architecture for B2B builds

Planner-executor-reviewer patterns, MCP integration, memory schemas, and the evals that prevent silent regressions when a model upgrades.

Senior engineering applied to AI

Twelve years of production engineering meets agentic coding. Claude Code, Cursor, and the senior practices that separate demos from systems.

Written by

Pooya Golchian, AI engineer in Dubai

Twelve years of production software engineering, the last three focused on AI agent systems for B2B companies. I write what I am actually building, with the numbers that matter to engineering leaders making real budget decisions.

About Pooya Golchian

Common questions about Pooya's work, AI services, and how to start a project together.

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Weekly field notes on private AI, automation, and high-performance Next.js builds. Each edition is concise, implementation-ready, and tested in production work.

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