AI Coding will Prevent Expertise | Lars Faye

AI Coding will Prevent Expertise<br>The need for ongoing friction in long-term skill formation.

"We see a future where intelligence is a utility like electricity or water and people buy it from us on a meter and use it for whatever they want to use it for" - Sam Altman of OpenAI

In my previous article, code]:outline-0 [&>code]:border-dashed hover:[&>code]:border-primary hover:[&>code]:text-primary focus-visible:[&>code]:border-primary focus-visible:[&>code]:text-primary transition-colors [&>code]:transition-colors">Agentic Coding is a Trap, I discussed the "skilled orchestrator paradox", where the skills required to manage AI agents for coding are the same ones that can be diminished through the continued use of said AI agents. Expertise was largely the differentiator; the more experienced a developer is, the less likely it is that they might experience skill atrophy, as the knowledge has had a chance to ossify after years of experience.<br>If you look around right now, you'll find the vast majority of those that are seeing the most benefits from these models are those that have had years, if not decades, of experience in the field (which predates AI tooling, of course). And any industry veteran will tell you the same: the bedrock of this knowledge comes from doing the work.<br>Developers who've entered the field around the time of LLMs are placed in a position where they don't have the benefit of longevity, but they are being guided (and sometimes mandated) to accelerate their efforts using coding assistants that require a history of expertise to wield effectively and responsibly.<br>It's an awkward place to be for that demographic, as it creates a scenario where a novice needs expert-level skills to leverage the tools and keep pace in the industry.<br>The "Expert Novice"<br>We're currently sending very mixed signals to people across the industry. We're hammering in that if you're not using AI tools, you will be "left behind" by your peers who are using them. code]:outline-0 [&>code]:border-dashed hover:[&>code]:border-primary hover:[&>code]:text-primary focus-visible:[&>code]:border-primary focus-visible:[&>code]:text-primary transition-colors [&>code]:transition-colors">"AI won't replace you, someone using AI will" has been on repeat since 2023.<br>And in the same breath, it's also said that the way to get the best results from these models is to apply higher-order thinking; "vibe coding" is a dead end; you need to "move up the stack" and create robust specs, architect with good design patterns, and always review the outputs diligently so you never ship something you don't understand.<br>The skills to do so, however, are a function of someone who has experienced the friction and challenges over time that culminate in code]:outline-0 [&>code]:border-dashed hover:[&>code]:border-primary hover:[&>code]:text-primary focus-visible:[&>code]:border-primary focus-visible:[&>code]:text-primary transition-colors [&>code]:transition-colors">"good taste".<br>This leads to another situational paradox: If these tools demand expertise, yet the tools can actively circumvent the friction that cultivates expertise, then what is the path for one to become an expert so they can effectively use these tools?<br>Confidence without Comprehension<br>One hope is that these models will end up accelerating learning as they are used for code generation. Junior developers can work with the same gravitas and confidence as industry veterans with their "personal AI tutor". Knowing syntax is increasingly less important, and any knowledge or ambiguity gaps are filled by the AI tool. The deeper mechanics of the code stay abstracted away, since the developer sits higher in the stack.<br>code]:outline-0 [&>code]:border-dashed hover:[&>code]:border-primary hover:[&>code]:text-primary focus-visible:[&>code]:border-primary focus-visible:[&>code]:text-primary transition-colors [&>code]:transition-colors">JetBrains, a major player in developer tools, code]:outline-0 [&>code]:border-dashed hover:[&>code]:border-primary hover:[&>code]:text-primary focus-visible:[&>code]:border-primary focus-visible:[&>code]:text-primary transition-colors [&>code]:transition-colors">recently completed a study of junior and novice developers by painstakingly analyzing their individual behavior in live coding sessions, and testing their ability to learn coding with AI tooling in varying degrees of assistance. Their main takeaway was stark and counterintuitive:<br>"Participants thought it was like having a personal tutor. From the data in our study ... we observed that they did not, in fact, use GenAI tools like a personal tutor. In fact, it was quite the opposite."

The participants that leaned into heavier AI assistance:<br>ul]:my-0">"Often skipped crucial planning stages, finding that because they hadn’t reasoned themselves into this position, Copilot had."<br>ul]:my-0">"Finished with an 'illusion of competence' rather than true understanding."<br>Counter to that,...