Kevin Tupper

Right now, AI is a buzzword. Once people know you're a professional in the field they will offer their opinions, ask questions, and so forth. Personally, I don't feel the need to create a boundary at the moment. The more I can help people understand this and demystify it, the better off we all are because eventually AI will be ubiquitous and part of the world we live in. For now, though, I patiently deal with fears, anxieties, and make a real effort not to increase them. Or I redirect people that think AI is the answer to everything. And if I'm tired and don't want to talk about it, an honest, "I'm sorry, but I'm exhausted at the moment and my mind needs a break from AI. Can we talk about something else" works wonders.

Start thinking through ways to use AI to support you on your heavy workload and kill two birds with one stone. Are there any repetitive tasks in your workload that AI may be able to help with? Let your reskilling focus directly support workload reduction. For example, as you learn to implement AI tools, apply them to automate routine tasks like drafting emails, ideating strategy, and learning new topics. This hands-on experience will not only lighten your workload but also fulfill your reskilling goals. By integrating AI into your current processes as part of your reskilling, you can manage your workload more efficiently and achieve your learning objectives simultaneously.

The AI Era is inevitable. Here's how to navigate resistance. Be Transparent: AI can feel like a black box, causing discomfort. Create transparency by explaining AI-driven decisions, involving teams, and fostering trust. Fear of Losing Control: AI disrupts familiar patterns, leading to fear. Embrace adaptability and focus on how AI can enhance, not replace, your work. Experiment and Learn: Run small AI experiments to understand its potential. Learn from failures and successes, and iterate to see benefits sooner. Engage Beneficiaries: Show others how AI improves processes, saves time, and enhances outcomes to gain buy-in. Foster transparency, embrace adaptability, experiment, and engage beneficiaries to enter the AI era together.

The skills of the future are clarity of thought and speech on the user side. And on those who are building solutions, they must be great lateral and outside the box thinkers. The best solutions and approaches haven't been created yet.

To that end, stick to the main APIs as much as possible when learning. Avoid the frameworks which try to abstract everything. This is a ground floor opportunity to learn something new!

Today, AI is in a constant state of flux. The frameworks are changing too rapidly to rely on for enterprise work. Avoid overreliance on abstractions and focus on becoming adept at using the core APIs from the major model providers. Build your own lightweight abstractions, while we wait for more industry standard approaches to rise from all the various techniques people are experimenting with.