From the team
Joust field notes.
Operator-level writing on how the work actually moves, what AI is good at, and what it isn't.
From the team
Operator-level writing on how the work actually moves, what AI is good at, and what it isn't.
Featured
Most of the AI cases I am asked to look at are true and useless at the same time. The technology really can do the thing, but that was never the question. One test, run in both directions, separates a business case from a bet on a price you do not control.
AI systems are predictive systems, not intelligent ones. That single shift in framing explains why they use tools, why they hallucinate, and where human judgment still matters.
The thing that makes your company hard to copy usually lives undocumented in a few people's heads. It is your most valuable asset and your largest single point of failure, and most companies only price it the week someone gives notice.
Most teams do not run on a plan. They run on whoever's inbox is loudest. It is the most expensive operating habit we see, and it stays invisible because the cost is spread across everyone's day.
Three patterns I keep seeing after 20+ consults, and what to do instead. The model is fine. The pilots die for reasons that have almost nothing to do with AI.
A walkthrough of a Joust Operating Review. Sector-anonymized findings from a $200M B2B distributor: $1.84M in operations tax mapped across three workflows, with a 12-month implementation roadmap.
Companies that have tried AI usually share a pattern: a high-energy pilot, real engineering effort, and then nothing in production six months later. The model is rarely the bottleneck.
There is a recurring cost inside every operating business that technology could replace. It hides in salaries, not vendor invoices, which is exactly why it never shows up in a procurement review.
We've seen this hype cycle before. The grounded version of AI is real, useful, and worth defending from the loudest pitch. A practitioner's read on what works, what it costs, and what to actually watch.
After thirty years inside the systems that run enterprise companies, the pattern was hard to miss. Smart teams pay for strategy. Then nothing changes.
There are 8,000 AI tools on the market. Picking one before you understand the work is how you end up with eight subscriptions and zero hours saved.
The most valuable thing we hand a client isn't a roadmap. It's the answer they were already half-suspecting but no one had said out loud.
Capture rate is one of the most misunderstood numbers in AI ROI math. Here's what it is, what it isn't, and how to set it realistically.
The build-vs-buy decision changed when LLMs got cheap. The new question isn't which one to choose. It's which parts of the stack each one belongs to.