I have been a developer for a long time. Long enough that my first scripts were dBASE III, before Clipper, before compiler days. I know what a good system looks like, what a bad one looks like, and most of the awkward in-between places where things break. I pay for Claude Max so I have …
There are two kinds of AI at work in any business: the fly-fisherman on a laptop landing rare fish by hand, and the trawler running overnight to bring in the tonnage. Social media only ever shows the first. Most company “AI strategies” are really one power user with a good rod, and the real work is building the dockside between the two.
We sell clarity, so it’s time we ran our own business through the ReadyRun framework. The first score will be rough. That’s the point. We’re inviting nine more companies to take the mirror test with us through the Loop program.
AI is the engine. It can process data, make decisions, spot patterns, and work at a speed no human team can match. That part of the equation is solved. So everyone rushes to bolt an AI engine onto their operations. A chatbot here. An invoice automation there. A report generator in the corner. Each one taps into real power. And each one, in isolation, kind of works. But kind of working is the problem. The missing piece was never more AI. It was control. And that control is custom software.
The modern application stack is no longer just about code. It is about deciding, before a single line is written, whether the work belongs to a human or an agent.
Our project started with a simple goal: build world-class custom software. But we ran into an uncomfortable truth. You can’t talk about the last step…if there’s no clarity about the first. Most organisations try to solve the specific problem in front of them, the exciting one.The differentiator. The clever bit. Meanwhile, the basics remain fuzzy.Capabilities …
Read more “Before You Scale the Mountain, You Have to Find It”
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