AI + ML
The boom is piling up technical debt, warns Lightrun's Moshe Sambol
INTERVIEW Enthusiasm among managers to adopt AI tools has outpaced developers' ability to learn those tools and use them effectively.Moshe Sambol, VP of customer solutions at software observability outfit Lightrun, told The Register in an interview that he speaks with a lot of companies. Some of the developers in those organizations, he said, are very comfortable with AI tools."But the reality is that a lot of developers are much earlier in the curve," he said. "The expectations of businesses are getting ahead of where the developers are in terms of their mental model and in terms of the training that they're providing, the enablement they're providing to make their teams comfortable with the tools, and the rate at which these tools are evolving."
Sambol said the degree of AI tool adoption varies.
"I absolutely have customers who've told their developers, 'You don't write code anymore. You review code. No one should write a line of code unless for some reason you failed after three attempts getting GenAI to do it,'" he said. "I have customers like that. I don't know if I should name them, but absolutely."And he said on the other side of the spectrum, there are organizations like banks that are just starting to roll AI tools out due to compliance obligations and traditional industry caution."It's an exciting time to be adopting these tools and learning these tools, but it puts a lot of pressure on the developer," he said. "It puts this expectation of being more productive."Not everyone manages that, and Sambol said he has a lot of sympathy for developers who have been directed to use AI tools without training and organizational guidance. Generative AI models will produce a lot of code quickly, he said, and because the code seems correct initially, it often gets pushed forward."If it's not creating bugs en masse today, it's just pain waiting to happen," he said. "The number one question I think we have to be asking developers is, 'Can you explain that code? Have you validated that the code actually fits in the context of the broader system?'"Sambol said the answer isn't necessarily yes or no because developers have different levels of experience and often work on large projects where they focus only on a specific part of the code base. It's common in enterprises, he said, that no one person will understand the entire system end-to-end, which is why problem resolution often requires a group of people.The issue he sees is that generative AI systems don't help bridge the missing knowledge gap. They don't provide the context to understand all the components involved.Sambol went on to describe an incident in which a developer was using an AI assistant to build an Ansible automated workflow. "The generative AI was creating the Ansible template for him, which seems like a perfect match – it's drudge work," he explained. "And it's much better at getting the syntax exactly right."
