New junior developers are reliant on Copilot, Claude, and other AI tools, meaning foundational coding knowledge is now missing, creating problems down the road
100k+ views 70+ votes 50+ votes — Something's been bugging me about how new devs and I need to talk about it. Bluesky: @mariotoday . Mastodon: @rabc@hachyderm.io , @dwallach@discuss.systems , and @sinbad@mastodon.gamedev.place X: @deedydas , @nickadobos , @deedydas , @gergelyorosz , @deedydas , @namanyayg , and @elonmusk Forums: Hacker News , r/ChatGPTCoding , r/theprimeagen , r/programming , and Slashdot Bluesky: @mariotoday : “We're trading deep understanding for quick fixes, and while it feels great in the moment, we're going to pay for this later” [embedded post] Mastodon: Ricardo Carvalho / @rabc@hachyderm.io : lol we are in a world where people are being fired for “low performance” without knowing what that means exactly and you think they will loose precious time having brainiac discussions instead of shipping features? — https://nmn.gl/... [image] Dan Wallach / @dwallach@discuss.systems : I feel anxious for stepping away from teaching just as AI assistants have swept through the education system. This piece, linked below, is a thoughtful look at what we're giving up, for junior developers who rely on AI rather than having to actually think through the problem and understand the solution. … @sinbad@mastodon.gamedev.place : What's amusing to me here is it's a dev comparing the “old approach” of learning via StackOverflow to learning via LLMs. My generation of programmers disrespected SO as dumbing down learning because so many devs were just copy/pasting the top answer instead of understanding it - it was faster so of course they did. … X: Deedy / @deedydas : @forevermylapore I think about it a lot, and I think yes understanding still matters. AI is a leaky abstraction on code. In other words, it fails to truly hide the underlying complexity. Python is just a layer on abstraction on C++ where you require no memory management. But it's deterministic Nick Dobos / @nickadobos : @deedydas @elonmusk Right because the maps are never outdated, the docs are never wrong... Documentation & stackoverflow has a higher hallucination / error rate than LLms Deedy / @deedydas : New junior developers can't actually code. Fantastic blog where the author argues that AI is preventing devs from understanding anything Unlike the internet which only replaced fact lookups but adds explanations, AI replaces all reasoning. [image] Gergely Orosz / @gergelyorosz : “New juniors can't actually code.” Story as old as the tale of programming. It takes time for new developers to understand how everything works and become competent. Here's an early-career developer confessing in 2013 they rely too much on this site called... Google. [image] Deedy / @deedydas : @elonmusk If Google Maps hallucinated every 5 attempts, it might be pretty important to remember how to get to places! Neo / @namanyayg : look mom I'm rank #1 on Hacker News again! [image] Elon Musk / @elonmusk : @deedydas People also don't know how to get places in cities without digital maps & GPS Forums: Hacker News : New Junior Developers Can't Actually Code r/ChatGPTCoding : New Junior Developers Can't Actually Code r/theprimeagen : AI is Killing How Developers Learn. Here's How to Fix It r/programming : AI is Killing How Developers Learn. Here's How to Fix It Msmash / Slashdot : 'New Junior Developers Can't Actually Code'
Context & Ripple Effects
The concern extends a broader debate over whether generative AI bypasses the practice that builds durable expertise. Related coverage argues that the greater educational risk is short-circuiting the learning processes needed to use these systems well, rather than simply enabling cheating.
It also qualifies the assumption that AI-assisted coding automatically improves output: a later METR study of experienced open-source developers found slower task completion despite participants’ expectations of speed gains. The issue is therefore not only junior-developer readiness, but whether tool fluency is being mistaken for engineering capability.
First-order effects
- Junior developers who accept AI-generated code without being able to explain or debug it can struggle when outputs are wrong, incomplete, or poorly matched to a codebase.
- Teams employing them face a more immediate review and mentoring burden, because foundational gaps surface in diagnosis, maintenance, and design work rather than only in initial code production.
Second-order effects
- Hiring and training programs may put greater weight on code review, debugging, and reasoning exercises to distinguish assisted output from underlying competence.
- AI coding-tool vendors face pressure to support learning and verification workflows, not just faster code generation, as teams try to reduce reliance on unexamined suggestions.
Third-order effects
- If reliance consistently displaces early-career practice, the software industry’s junior-to-senior development pipeline could become more dependent on scarce experienced reviewers and mentors.
- The pattern points to a growing form of generative technical debt: faster apparent delivery now can shift costs into maintainability, incident response, and skill rebuilding later.
The trend: Generative AI is moving from a productivity add-on to a workplace learning intermediary, forcing organizations to balance speed against the preservation of human judgment.