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.
Infrastructure & AISelf-Hosted LLMs for Enterprise: Real Costs and Trade-offs
The case for self-hosting keeps getting easier to make on slides and harder to execute in production. A cost breakdown for senior engineers: hardware tiers, hidden expenses, Ollama vs vLLM, model licensing, and when the math simply doesn't work.
AI & Data EngineeringClaude vs the Field: LLMs for Data Engineering in 2026
Which LLM, for what task, at what price? SQL benchmarks, Claude Code + dbt field evidence, MCP integrations, cost routing strategy, GDPR compliance paths, and the open-source challengers closing the gap — grounded in Q1–Q2 2026 data.
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.
AI & Brand IntelligenceBest Practices for Monitoring Brand Sentiment Using LLMs
Most LLM sentiment pipelines are structurally inadequate: single-shot measurements, circular validation, no confidence intervals. A production guide covering prompt engineering, aspect-based analysis, hallucination handling and multi-platform strategy.
AI & Data EngineeringLLM Agent Memory Architectures in 2026: The Decision Most Enterprise Teams Make Too Late
Claude Code, Mem0, Zep/Graphiti, Letta, MemOS — a verified technical comparison of every major LLM memory architecture, with benchmark data and a decision framework built around governance, not just retrieval.
Infrastructure & AICentralized LLM API Gateway vs. Self-Hosted Models: The 2026 Enterprise Decision
The real question is not API vs. self-hosted — it is about routing. Cost breakdown with verified 2026 pricing, EU data residency gaps across providers, LiteLLM gateway configuration, and the security matrix that determines when self-hosting is actually required.
AI & Data EngineeringKarpathy's LLM Wiki Pattern for Brand Intelligence: A Production Implementation
The first published implementation of Karpathy's April 2026 LLM Wiki pattern applied to GEO and brand monitoring — with ingest pipeline, SelfCheckGPT-NLI hallucination gating, lint operations, and complete Python code.