Engineering in AI
Thoughts on AI strategy, product thinking, and digital leadership.
From Vibes to Specs: The Ultimate AI Coding Workflow Using BMAD and Task-Master
Discover the ultimate spec-driven AI development workflow. Learn how combining BMAD's architectural planning with Task-Master's strict execution can scale your AI coding projects from vibes to production.
The Agentic Commerce Opportunity: What McKinsey’s Research Means for Engineers and Digital Leaders
A deep dive into McKinsey’s report on agentic commerce and how AI agents could transform digital commerce. Learn what engineers and digital leaders must build to prepare for AI-mediated transactions.
Universal Commerce Protocol (UCP): Engineering the Backbone of Agentic Commerce
The Universal Commerce Protocol (UCP) is a new open standard designed to enable agentic commerce at scale. This article explains how UCP works, why it matters for AI engineers and architects, and how it reshapes payments, checkout, and machine-driven commerce.
Vertex AI Agent Builder: Engineering Production-Grade AI Agents on Google Cloud
Vertex AI Agent Builder is Google Cloud’s enterprise-grade platform for building, deploying, and governing AI agents. Learn how it supports production-ready agent systems at scale.
Data Pipelines Are the Real AI Product: Why Models Commoditise but Pipelines Compound Value
AI models commoditise quickly. Data pipelines don’t. Why robust AI data pipelines are the real product — and the true source of long-term advantage.
Machine Learning Algorithm Types Explained: A Practical Guide for Engineers in 2025
A practical engineering guide to machine learning algorithm types—supervised, unsupervised, and reinforcement learning—and how to avoid overfitting vs underfitting in real systems.
Data Readiness Report Framework: 5 Steps to Engineer AI-Ready Data and Governance
Learn how a data readiness report framework and robust data governance turn messy enterprise data into AI-ready assets. Practical guide for engineering in AI.
The Original ChatGPT: Insights from the 60s ELIZA
Discover how to design AI products users trust — from the first chatbot ELIZA to modern systems like ChatGPT, learn 7 key principles for trustworthy AI product design.
From Schemas to MCPs: Engineering AI Product Discoverability for Agentic Shopping
Learn how to engineer AI product discoverability via Model Context Protocols (MCPs) in the age of agentic shopping — a practical guide for brands.
Lovable.dev: A Powerful AI App Builder for Rapid MVPs
A comprehensive review of Lovable.dev—an AI-powered no-code app builder—examining its ease of use, MVP-ready workflow, pricing tiers, pros & cons, and ideal use cases for both developers and non-technical creators.
The Hidden Stack: What Every Engineer Needs to Know About Building with LLMs
LLMs are more than just chatbots — they’re a new runtime layer for software. This deep dive into the LLM application stack reveals what every engineer should know to ship real-world, AI-powered features with GPT-4, LangChain, and vector databases.
Why Frontend Engineers Should Care About LLMs
Large Language Models (LLMs) like GPT-4 are transforming how users interact with digital products — and frontend engineers are at the heart of this shift. It’s time to think beyond chatbots and embrace the future of intelligent interfaces.