8. Data Engineering for AI Agents: Pipelines, Real-Time Sync, and Vector Search
TL;DR Getting a data pipeline right is one job. Data engineering for AI agents is a different job. The agent has to actually consume that pipeline’s output,…
7. Building Real Human-in-the-Loop with LangGraph Checkpointing
TL;DR A review queue with a button looks like human oversight. It isn’t — the automated decision has already taken effect by the time anyone opens that…
6. Compliance Infrastructure: Audit Trails, Policy-as-Code, and the Append-Only Principle
TL;DR We built three pieces of audit trail architecture for a regulated AI platform: a transactional outbox so an audit event can’t be silently lost between Postgres…
5. Red-Teaming AI: OWASP LLM Top 10 and the Probes You Actually Need
TL;DR We had heard of the OWASP LLM Top 10, and we had implemented fewer than half of it. We had PyRIT installed, and we had almost…
4. Securing Agentic AI: Authentication, Authorization, and PII
TL;DR Our five-agent banking AI platform had OPA wired into exactly one agent. The MCP server had no auth middleware. All five agents shared one API key….
3. The 57-Gap Audit — What “Done” Actually Means in Production AI
TL;DR After weeks of building a multi-agent AI platform — five agents, full pipeline, red-team harness, control UI — the system looked done. It wasn’t. A config…
2. The Engineering Platform: Orchestration, Monorepo, and the Stack Decisions
TL;DR Once you decide to build a multi-agent AI system, you face three engineering choices that will determine whether the platform is governable or just functional: what…
1. From Scripts to Sentience: Building an Agentic Data Platform
Series: Building an Agentic Data Platform | Part 1 of 17Reading time: ⏳ ~12 minutes 📌 TL;DR Most data engineering tutorials teach you to move data from…
3. The Developer’s Crucible: Debugging, Patience, and the AI Partnership
TL;DR This article reveals the unglamorous but critical reality of software development: debugging. We recount the real-world challenges faced, from frustrating environment setup errors to a cryptic…
2. Deploy Anywhere: A Guide to Cloud-Agnostic, Serverless APIs
TL;DR This article covers the deployment of our API, focusing on achieving true cloud-agnosticism and infinite scalability. We detail our use of the Serverless Framework to define…