How AI is done for real
Honest guides on AI agents, automation, and processes: the method, the tools, and the real cases. No hype, just what works; and when AI isn’t the answer.
Why AI agent projects fail and the 6-month method to land in the 5% that work. With a decision matrix and a practical test.
Why AI stays a throwaway chat, and the method to give it a memory with Cowork: structure, rules, routines. With a free kit and a mockup of the result.
What manual data entry costs, how to drop it starting Monday with Claude Cowork, and when a plain spreadsheet still does. With a calculator and a mockup of the result.
The formula, total cost of ownership, a baseline and control group to isolate the AI’s contribution, and a calculator to estimate payback and return.
The 4-step funnel to find the first process to automate: map it, filter with signals, find the constraint, score it with the scorecard.
The five steps to make a process repeatable and measurable before automating it: map the as-is, capture tacit knowledge, make the rules explicit, unify the data, write the SOP.
Adoption is the last link: without it, all the upstream work produces nothing. Champions, training in the flow, leaders who model the behavior, and how to measure real adoption.
Shadow AI, how to classify the risk, and the 30-day plan to govern AI in your company without a compliance department.
The real cases where we advise against AI: low volumes, unstable processes, AI for show, a broken process upstream. Honesty before the project.
What they actually do, lock-in vs your own code, costs, and when each one makes sense. A comparison with no marketing.
Want to apply all of this to your own process?
The guides explain the method. On the free call we apply it to your case and tell you, honestly, whether it makes sense to start.