For owners and tech leads who've seen the AI demos and want to know what it takes to run AI against live business systems. Written by someone who builds and runs these systems: MCP servers, agents with real permissions, AI content pipelines. Write about design decisions, what broke, the guardrails added and the trade-offs. NEVER invent client stories, outcomes, figures or "I've seen…" experience; where no fact supports a claim, write it as advice ("the pattern to watch for…"), not as something that happened. No AI news commentary, no tool roundups, no hype. Don't end every post with a sales pitch.
Articles in Building Real AI Systems
Where AI Ordering Agents Break Down in B2B
A customer can say, “just reorder the usual,” and a model can sound brilliant right up until it hits a freight threshold, a credit hold, or an account price that only exists in one dusty exception…
12 min read
How to Stop Ordering Agents Over-Automating Edge Cases
An ordering agent usually doesn’t fail on the easy stuff. It fails when a line item is half available, a backorder is sitting in the ERP, and someone in sales already promised the customer a…
10 min read
Which support tickets are safe to automate?
A refund request looks routine until the customer is on a multi-year contract, mentions a missed SLA, and asks for a credit against next quarter’s invoice. That is the moment most support automation…
12 min read
How to Decide MCP Server vs Custom Action Layer
The better question is, how do you decide which internal systems should be exposed through an MCP server versus kept behind a narrower custom action layer? That choice decides whether your agents…
10 min read
What Breaks in a Loosely Scoped MCP Server?
The pattern is consistent in production agent MCP setups. The server exposes a wide tool surface, the model is asked to “help”, and the first bad call is usually one of these:
10 min read