Alex Lieberman@businessbarista
Just co-led an AI training for 20 execs from one of the largest financial institutions in the world.
We covered a lot of ground from how LLMs work to what an agent is and how to transform your work, but here were the biggest aha moments for the group.
1. Historically, leaders had to think about allocating budget for headcount and software. Now, token budget must be a serious consideration. Do you set limits per employee? How do you measure the ROI on your token budget? How much budget do you allocate to which employees? How do employees know which models to use to most efficiently spend tokens?
2. The models are good enough now, where most bad output is user error not technology error. And a major contributor to user error is bad context management. To have clean context hygiene you need to understand what the context window is, why separation of concerns is important, and how tactically to treat context like a precious resource.
3. A skill is a scary word. It’s nothing more than an SOP. If you asked an intern to write a one page document breaking down their step-by-step process for building a great deck, you’ve created a skill. A skill is a long prompt that codifies a repeatable process, can be edited as you see fit, and helps to generate more predictable output that meets your standards.
4. Saying you use AI gets you style points. But the real unlock is in process mapping. During the workshop, we asked every exec to write out one of their/their teams key processes step by step and place an E (eliminate), A (automate), or D (delegate) next to each step. The exercise not only revealed opportunities for AI, but also existing inefficiencies that have gone undetected.
5. Claude Cowork opened their eyes. Many people still see AI as a chat-based supercharged Google. They may have heard the phrase “agent,” but they assume it’s sophisticated tech reserved for engineers. Cowork is the layperson’s gateway drug to agents, showing the possibility of building web apps, ai workflows, and live artifacts in a single place.
6. Every company talks about the “bad guys”slowing down AI transformation: legal, compliance, and IT/security. One of the most powerful choices leadership can make is flipping the script and making them the heroes of the transformation story. Help them understand the risks of doing nothing, work with them to make calculated bets, and celebrate them publicly when they partner to drive transformation with speed.
7. Getting an AI system to perform requires four things to go right: picking the right model, teaching it the right process, providing the right context, and establishing the right guardrails. Most people assume the right model is 99% of it, they don’t think enough about giving the right context, and they don’t realize the right guardrails make things like hallucinations and mistakes less dangerous.
