Blogs
a collection of my thoughts
You're Paying for the Wrong Guardrails
Most AI teams waste money on generic content moderation while ignoring the guardrails that actually prevent production failures -- business logic validation, decision-point controls, and architectural constraints.
E-Commerce Chatbot Guardrails: What Major Companies Learned the Hard Way
A practical guardrails framework for e-commerce AI chatbots — built from the real failures of Chevrolet, Air Canada, DPD, NYC, Taco Bell, and McDonald's. What to implement before your bot goes live.
Jailbreaking Agentic AI: How Chatbots and AI Agents Are Being Exploited in Production
A deep analysis of real-world jailbreaking attacks on AI chatbots and agentic systems — from the Chevrolet $1 car sale to zero-click IDE exploits — with documented incidents, attack techniques, and what actually works as defense.
MCP + A2A in 2026: The Real Stack for Interoperable AI Agents
A practical guide to building interoperable AI agent systems in 2026 using MCP, A2A, registries, and governance controls that hold up in production.
Production AI Agents in 2026: A Reliability Playbook That Actually Works
A practical reliability playbook for AI agents in 2026 covering async execution, tracing, evals, SLOs, and safe rollout patterns for production systems.
MLflow 3 Has Cracked the LLM Observability Code
MLflow 3 transforms GenAI from guesswork to science with production-ready observability that integrates development through deployment without lock-in.
From Chaos to Orchestration: Building Production-Grade Multi-Agent Systems with Pydantic AI
After connecting eleven specialized agents, here's how Pydantic AI enables scalable, observable, and cost-effective multi-agent orchestration in production.
Production Monitoring for Azure OpenAI: The Metrics That Actually Matter
Operational and responsible AI metrics for monitoring Azure OpenAI deployments — with KQL queries you can paste and guardrail patterns that work.
Logfire vs LangSmith for AI Agents — The Pragmatic Playbook
Pragmatic comparison of Pydantic Logfire and LangSmith for AI agents—OpenTelemetry observability vs evaluation and tracing—with copy‑paste code and recipes.
Context Engineering vs Prompt Engineering: Why the Best AI Systems Are Built, Not Prompted
Context engineering is replacing prompt engineering as the core skill for building production AI. Here is what it actually means and how to implement it.
Building Multi-Agentic Systems with LangGraph — and Evaluating Them Like Adults
A guide to building and evaluating multi-agent systems with LangGraph, covering stateful graphs, human-in-the-loop, and repeatable evaluations.