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We’ll start by examining the friction points among the people in your company, who all have different AI goals. Executives want cost and headcount down. Technical leadership wants AI in the workflows without losing accountability. Engineering managers want to meet their production goals while keeping their teams. Engineers want to build good products, learn the new tools, and still have a job next year. Almost every AI collision at work is between those four goals, and we’ll name them out loud so we can find solutions.
We’ll go through the research and what the numbers are saying instead of just the headlines. We’ll trace where the tech layoffs are really coming from, and how many of them are the result of AI efficiencies. We’ll spend a minute on the history of how the spreadsheets were going to eliminate accounts in 1983, but there are even more in 2026.
Then we’ll get hands-on. No one automatically knows how to use AI because it’s an everything tool. We’ll cut through the confusion by applying a Six Sigma process map. Originally designed to modernize bureaucracy, we’ll use it to understand where AI can be most effective and where we need to keep the creative human in the loop. This will help us focus on being more productive and using AI surgically, rather than spending a year’s worth of tokens in a month trying to do everything.
Takeaways:
- A map of the four AI goals in your org based on the current research, and language for surfacing them
- A process mapping exercise you can run on your own work
- What the six percent did differently
- A concrete plan to make the most out of AI and increase RO
