Field notes, frameworks, and unscripted thinking from our engineers, architects, and operators. Long enough to be useful. Short enough to read in one sitting.
When AI projects pay off, when they don't, and why most plateau before the returns compound.
Read the articleThe build vs buy AI decision, made practical: buy when the task is generic and low-risk, build when it is specific to your business, and use six questions to decide.
Prompt engineering is writing clear, specific instructions that get reliable results from AI models. Core techniques, a before-and-after example, and where it fits.
Google Cloud grew 63% last quarter and Copilot ships inside most of the Fortune 500. A subscription still isn't an AI strategy. Here's where the big platforms stop.
A vector database lets AI search information by meaning, not keywords. What it is, how embeddings and similarity search work, and why it powers RAG.
AI agents and agentic AI, explained without the hype: what an agent actually is, the parts that make one work, the autonomy spectrum, and what it means for your business.
MCP, the Model Context Protocol, is the open standard that connects AI to your tools and data. What it is, why it exists, and why it matters for custom AI.
We work with leadership teams to identify the right opportunities, define the strategy, and build the systems that move the business forward.
