I want to thank Irene Lyakovetsky for interviewing me recently for the SaugaTalks podcast. We covered many topics related to AI, digital transformation, and lifelong learning, as well as technical topics such as testing large language models, AI governance, and experimenting with code generators.

Segments of the interview are available in the playlist on the SaugaTalks podcast, Digital Transformation and Business Problems AI Can Solve. I have also embedded my favorite shorts at the end of this post.

Three takeaways for Digital Trailblazers

Below are three takeaways for digital transformation leaders on topics I covered in the interview.

1. GenAI code generator limitations

I’m in the process of moving this blog to a new platform. It’s a behemoth job because of the 600+ posts here that needed an updated information architecture and lots of HTML data cleansing. I used Zapier to help automate most of the migration, but I needed some Javascript to parse, correct, and modify some of the posts.

I used ChatGPT to create several content-cleansing scripts. Unfortunately, Zapier didn’t accept scripts using DOMParser, so the scripts all used simple and often imperfect RegEX patterns to find and fix the content.

ChatGPT generated the code, but I had to read it, understand it, test it, and provide feedback to ChatGPT to fix its logic. Like a lower-level developer, ChatGPT made assumptions, and its code reflected ideal situations. Other code generators may be able to test their code and automate fixes, but I couldn’t do this with ChatGPT.

Bottom line: I saved a ton of time using ChatGPT to generate code I can no longer write. Even as a developer, writing RegEX was painful and rarely worked without many trials and errors. But, code-generating still required my prompts, evaluations, and testing – all skills developers will need and enhance even as Gen AI tools improve their code-generating skills.

2. Why Digital Trailblazers are key to AI

I have several posts explaining why organizations need more Digital Trailblazers, which I summarize in the second featured video.

With GenAI, organizations should double down on developing more employees from hands-on roles to Digital Trailblazers. The challenge for all companies is to leverage AI beyond product drivers and energize digital transformation. This won’t happen on its own by deploying tools and enabling employees to tinker. DigitalTrailblazers should be looking to update products/services with genAI capabilities, improve user experiences, and fully re-engineer business processes to leverage AI and ML capabilities.

Some other key posts for Digital Trailblazers:

• 10 Questions on Leading Gen AI and Driving Digital Transformation
• Top Leadership Attributes of Really Successful Digital Trailblazers
• How to Drive Lifelong Learning: Practical Ways for Digital Trailblazers

3. What innovation to expect with GenAI

Currently, GenAI is largely a point solution (like ChatGPT) or embedded in workflow applications, as  Appian, Atlassian, Microsoft 365, Pega, Quickbase, Salesforce, SAP, and other enterprise SaaS platforms have done.

We have yet to see GenAI fully integrated with other devices such as AR/VR + GenAI, voice + genAI, and cars + genAI. Once we do, we’ll see a new wave of consumer and industrial experiences, think retail + genAI, safety sensors + genAI, and immersive higher ed experiences.

Organizations need to dedicate more time to blue sky planning, and guess who will lead them? StarCIO Digital Trailblazers! Please contact me for help!

The Interview on SaugaTalks

Below are the three shorts I referenced in today’s post. Please visit the playlist on SaugaTalks for many more shorts to watch!

Here is the full interview