Writing

“Most BI dashboards are invisible to AI systems. drexo extracts the semantic context trapped inside Tableau workbooks into structured markdown that both humans and agents can reason about.”

• drexo
• tableau
• open-source
• data-engineering
• ai

Modern data platforms can detect failures — but they still struggle to explain what those failures actually mean. This article explores the emerging Investigation Layer in modern Data Operations.

• data-engineering
• data-ops
• observability
• ai
• analytics-engineering
• dbt
• root-cause-analysis
• ai-agents

AI is transforming engineering. Most teams are using it to go wider; the teams that scale use it to go deeper. In the AI era, depth compounds — breadth doesn't.

• engineering
• ai
• team-design
• careers
• data-engineering

The PromptOps playbook implemented end-to-end — registry, validator, evals, CI, observability, and AWS deployment. Working code for every layer of the stack.

• promptops
• ai-native
• devops
• ci-cd
• aws

Prompts are scattered, ungoverned, owned by nobody. The fix isn't new — it's the DataOps playbook, applied to a new layer.

• promptops
• ai-native
• data-platforms
• governance
• mlops

How to build serverless data platforms that don't drift into sprawl — versioned shared modules, runtime-aware packaging, and explicit deployment orchestration.

• aws
• serverless
• lambda
• glue
• data-platforms