Technical Writing
First-principles engineering essays on multi-cloud architecture, data platform governance, and AI workload realities. Grounded in production systems, Zero Trust discipline, and 25 years of platform lessons.
“We just built an MCP server so our AI agents can query the production database directly.”
Read postA Slack Message Is Not a Release Control
There is a moment in post-incident meetings that plays out across tech organizations with painful predictability.
Read moreAutomating with AI is not adopting AI
There is a pattern that repeats itself every time a team seriously starts working with AI tools.
Read moreYour AI workload is not your infrastructure's problem. Until it is.
There’s a conversation happening in the software architecture community about how bad code design inflates LLM token consumption. It’s a valid point. But it misses an entire layer of the problem — the one Platform Engineers and SREs actually own.
Read moreAWS Cost Explorer Just Got Conversational — And That Changes the Workflow
AWS just closed the last friction gap in cost analysis.
Read moreAI Observability: the problem nobody is solving well in 2026
We’ve spent years building AIOps — using AI to observe infrastructure. But there’s a more urgent problem taking shape: who observes the AI itself?
Read moreFrom ticket to PR with agents: how to use Claude to automate platform changes without breaking SLOs
In Platform Engineering and SRE, the hardest part of change is rarely writing the change itself. The hard part is everything around it: understanding the intent behind a ticket or incident, locating the right context, identifying the systems involved, deciding what should change, validating the blast radius, documenting rollback, and...
Read moreMulti-Layer Cost Controls for Cloud Data Platforms
Managing costs in cloud data platforms is challenging, especially in sandbox environments where analysts experiment freely. A single misconfigured query can run for hours, consuming resources and exploding budgets.
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