In the fast-evolving world of software development, artificial intelligence tools promised to revolutionize coding, automating mundane tasks and boosting efficiency. But for many developers, the reality has been a double-edged sword. Thomas Orus, a seasoned programmer, shared a candid account in his blog post titled “I Tried Coding with AI: I Became Lazy and Stupid,” detailing how relying on AI assistants like GitHub Copilot led him to skip deep problem-solving, resulting in shallower understanding and increased errors. Orus described generating code snippets without fully grasping their mechanics, fostering a dependency that dulled his critical thinking—a sentiment echoing across the industry.

This personal revelation isn’t isolated. Recent studies and developer forums reveal a growing concern that AI coding tools, while seductive in their speed, might be eroding core skills. Developers report feeling “lazier” as AI handles boilerplate code, but this convenience comes at a cost: reduced learning and innovation.

The Productivity Paradox

A landmark randomized controlled trial by METR, published in July 2025 and highlighted in Reuters, found that experienced open-source developers using early-2025 AI tools took 19% longer to complete tasks in familiar codebases. Contrary to hype, AI introduced friction—developers spent extra time verifying and debugging AI-generated code, leading to net slowdowns. The study noted a “perception gap,” where participants felt more productive, yet metrics showed otherwise, underscoring how overreliance can mask inefficiencies.

Echoing this, an article in InfoWorld from just days ago questions whether AI is “making our code stupid,” pointing to bloated, insecure outputs that demand rigorous human review. Developers interviewed expressed frustration over AI’s tendency to produce superficial solutions, potentially atrophying their ability to architect robust systems.

Eroding Skills and Rising Frustrations

On social platforms like X, sentiments from developers in 2025 paint a vivid picture of this shift. Posts from industry figures highlight a divide: some praise AI for supercharging tasks like debugging (with claimed 30% speedups), while others warn of diminished learning curves, especially for juniors. One thread emphasized that AI automates routine work, shrinking entry-level roles and forcing a pivot to skills like prompt engineering and system oversight—yet this often leaves coders feeling intellectually stagnant.

A study reported in The Indian Express last week revealed developers’ growing reliance on AI, coupled with declining confidence due to hidden bugs and errors. As one X user noted in a widely viewed post, AI might amplify outputs for side projects, but it risks turning programmers into mere overseers, not creators.

The Human Element Persists

Not all views are pessimistic. In a forward-looking piece from Brainhub.eu in May 2025, experts argue that AI’s impact demands upskilling in areas like architecture and integration, preserving jobs for those who adapt. Yet mandates to use AI, as critiqued in LeadDev‘s April 2025 article, are pushing teams to frustration, with coders cleaning up AI-induced messes in codebases.

This tension points to a broader detriment: AI’s allure can foster “stupidity” by shortcutting the mental rigor that builds expertise. An AS USA report last week synthesized evidence showing AI reducing creativity and speed in some workers, urging a balanced approach.

Toward a Smarter Integration

Industry insiders are calling for guardrails. Orus, in his reflection, advocates using AI as a tool, not a crutch—prompting manually first, then refining with AI to maintain sharpness. METR’s findings, echoed in Business Insider, suggest training programs to mitigate slowdowns, emphasizing verification protocols.

As 2025 unfolds, the debate intensifies. X discussions reveal optimism among some, with posts touting AI’s role in democratizing coding to non-engineers, potentially increasing demand for skilled overseers. However, the risk of laziness persists if developers don’t reclaim agency.

Ultimately, AI isn’t rendering coders obsolete but reshaping their craft. By blending human insight with machine efficiency, the industry could emerge stronger—provided it addresses these cognitive pitfalls head-on. As one X post wisely put it, shifting to higher-level thinking is key, turning potential stupidity into strategic savvy.