Subhash Kumar

thirty years in, still shipping · mumbai

Subhash Kumar

I design enterprise AI platforms — the kind that have to survive production, not just a demo.

Thirty years from Visual Basic to LLM agents. These days I work where site reliability engineering meets agentic AI: systems that reason, plan, call tools, remember — and still answer to governance and an error budget. Lately that has meant designing agentic SRE systems for enterprise estates — autonomous triage, routing and recovery that have to convince architects and auditors, not just a demo audience.

System diagram

every architect draws themselves eventually · fig. 0

  • 19,755 bookmarks
  • chai, unmetered
  • production incidents (unsolicited)
  • model release notes, daily

Subhash v30.0

uptime: 30 years · unplanned restarts: 0

cache — three decades of production incidents. never expires.
legacy module — Visual Basic. deprecated 2002, still loaded.
governance — runs "is this the right layer?" before any other process.
  • agents that fix incidents
  • this site — wiki, library, a curriculum
  • opinions (unthrottled)
30years shipping
19,755links curated
42wiki topics
2learning tracks

Now building

Agentic incident management

Autonomous agents that triage, route, and recover incidents — reasoning, tool calls, memory, and a policy engine, event-driven and observable end to end.

The coding-agent craft

Getting real work out of AI coding agents — and knowing which one to reach for. Claude Code as the daily driver: harness design, hooks, skills, subagents, and docs written for agents as much as humans. Benchmarked honestly against GitHub Copilot and Codex. And always the bill: token economics, cache behaviour, the right model for the job.

This site — an AI mentor in training

devopsmantra ingests my bookmarks, builds the wiki and the searchable library — and now teaches me back: a knowledge-graph curriculum, placement diagnostics, AI-graded recall and spaced repetition, two tracks live. 19,755 links in, the student became the syllabus.

The arc

1995

Programmer analyst. Built software for whoever walked in the door — printers, perfume makers, financial firms, coaching classes, car-rental agencies. Visual Basic, FoxPro, SQL, and a lot of listening.

2007

Enterprise consulting for European government and industry: document management, .NET, and a thirty-application portfolio that taught me estimation the hard way.

2010

Team-lead years: audit reporting systems and insurance platforms. Where I learned that trust in a system is built from its reports — and that reliability was a discipline before it had a name.

2014

Solutions architect for a very large UK retail estate. Architectural governance, migrations measured in millions, technology roadmaps that occasionally survived contact with reality — and a client hackathon won with an IoT build.

2019

DevOps architect for a national-scale estate. Pipelines in Azure DevOps, infrastructure written down in Terraform instead of clicked into existence, monitoring wired into ServiceNow — the plumbing autonomous operations would later stand on.

2023

The pivot. From keeping big systems boring — the highest compliment in SRE — to teaching them to fix themselves: LLMs and agentic AI, governed by policy, watched by telemetry.

2026

Built an adaptive learning engine in public: knowledge graphs, AI-graded recall, spaced repetition. Learning agentic engineering the way I'd architect it — systematically.

BSc

Physics, University of Mumbai. Microsoft-certified across three decades — first in 2000, most recently on Azure. The tools change; the habit doesn't.

The obsession, measured

live from the vault · one dot = 25 saved links

Say hello

If you're building agentic systems that have to survive a real enterprise estate — or want to compare notes on getting serious work out of coding agents — I'd like to hear from you.

Not ready for hello? Start with the AI-agents wiki or wander the library.