Insights
Field notes from real AI engagements — what works, what stalls, and what to do first. New posts every Tuesday and Thursday.
October 1, 2026
A polished AI strategy deck is not an AI strategy. Here's what mid-market leaders get wrong when they confuse planning with execution—and how to fix it in 90 days.
September 29, 2026
Before you buy another AI tool, you need to understand what your people actually do all day. Here's how mid-market organizations can stop chasing models and start fixing workflows.
September 24, 2026
A cautionary lesson from a real mid-market engagement: moving fast on AI without mapping your regulatory exposure first can cost you more than the pilot ever saved. Here's what we saw, and what to do instead.
September 22, 2026
Most organizations stall on AI not because they lack the right model, but because their existing data is siloed, unlabeled, or ungoverned. Here's how to diagnose the real bottleneck before you buy another tool.
September 15, 2026
Most mid-market organizations think they need a bigger budget or a better model. They don't. They need to look at the data they're already generating every day. Here's how to start there.
September 10, 2026
Agentic AI systems look impressive in controlled environments. Here's what actually breaks them when real workflows, real data, and real users get involved — and how to fix it before you deploy.
September 8, 2026
Most mid-market AI deployments stall not because the technology fails, but because organizations skip the workflow design step entirely. Here's what that costs you—and how to fix it.
September 1, 2026
Most AI pilots succeed in the demo and die in deployment. Here's why the gap exists and the specific disciplines that close it.
July 16, 2026
Most AI initiatives don't fail on the technology. They fail because nobody defined what "working" means before the demo. Here's the discipline that separates deployed AI from perpetual pilots.
