Writing on AI, data & engineering
LLM Brand Monitoring: The Metrics That Actually Matter for Enterprise
Brand managers are asking "does our brand appear in ChatGPT answers?" — and most tools still can't answer reliably. Here's the architecture we built to do it properly, and the four metrics that tell you whether you're winning in AI search.
AEO & AI VisibilityHow to Build an AEO Monitoring Pipeline: a Technical Guide
AEO is a data engineering problem, not a marketing one. How to structure the query set, build the pipeline, fix entity clarity, and close the loop from measurement to action.
AI ToolsClaude Code in Data Engineering: How I Use AI Agents on Real Enterprise Projects
Not a benchmark post. This is how Claude Code actually fits into a real data engineering workflow — where it saves hours, where it breaks down, and what advanced usage actually looks like.
AI ToolsCursor 3.0 Agentic Architecture: What Actually Changed for Engineering Teams
Cursor 3.0 is not an incremental update — it's a shift from autocomplete to parallel agent execution. Here's a technical breakdown of git worktrees, the Agents Window, /best-of-n, and what it means for how senior engineers actually work.