Most Tech Writing Explains What. This Is About Why.
I write about what actually happens inside engineering orgs. Not the polished version.
Cut Claude Code Token Usage by 60–90%: 16 Proven Techniques
Battle-tested techniques for .claudeignore, context compression, and multi-agent task splitting that cut token usage by 60–90% without losing Sonnet's predictive accuracy.
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Airflow in 2026: The Orchestrator That Became the Operating System for Data
Comprehensive Apache Airflow analysis: open source and every managed vendor (Astronomer, Cloud Composer, MWAA), pricing at three scales, Airflow 3.0 migration, operational pain points, AI workflows, and a decision matrix for choosing the right deployment.
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Dagster in 2026: The Orchestrator That Treats Data as the Product
Comprehensive Dagster analysis: pricing, asset-centric orchestration, AI/ML pipelines, learning curve, integrations, and why treating data as the product gives teams lineage and governance that task-centric orchestrators cannot match.
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Prefect in 2026: The Orchestrator Built for AI Workflows
Comprehensive Prefect analysis: pricing, scaling, deployment architecture, integrations, learning curve, and why its dynamic Python-native control flow fits AI agent workflows better than static DAG orchestrators.
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The Startup Cloud Credits Comparison No One Runs: AWS vs Azure vs Google Cloud
AWS, Azure, and Google Cloud all court startups with credits. The real comparison isn't compute pricing - it's who pays you more, who locks you in harder, and what happens when the subsidy ends.
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CTO vs VP of Engineering: The Org Split That Most Companies Get Wrong
The structural signal for splitting CTO and VP Engineering roles isn't headcount — it's a specific week when strategy and delivery both need full attention. A founder's decision framework with real failure modes.
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Why AI-Generated UI Looks Generic - and What CTOs Do About It
AI generates competent, generic UI by default. The CTO who builds a design vocabulary can direct it - and the compounding effect touches every product decision.
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Context Engineering: The Operating Discipline for Reliable AI Systems
Why AI output depends on how teams assemble and retrieve context - not on prompting. A 7-metric measurement framework with 8 charts for engineering teams.
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