AI Coding Feels Like Using an Unreliable Compiler
The article discusses the mixed feelings developers have towards using large language models (LLMs) for coding. While LLMs can assist in generating code, they often feel unreliable, requiring extensive verification and review from developers. The effectiveness of AI coding tools is influenced not just by the models themselves, but also by the engineering that surrounds them.
- ▪Developers are confused about the reliability of LLMs in coding tasks.
- ▪LLMs are compared to unreliable compilers, as they often produce code that requires thorough inspection and correction.
- ▪The quality of AI coding tools is determined by both the underlying model and the engineering that supports it.
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AI Coding Feels Like Using an Unreliable Compiler Written by Federico Tomassetti Federico Tomassetti in Language Engineering, Reflections 19 May 2026 X LinkedIn Facebook Threads Email Reddit BlueSky jQuery(function($) { $(".elementor-grid-item:last-child").last().after($("#bluesky_share")); }); Table of contents #allcont table, #allcont img, #allcont h4 { margin: 20px 0px !important; } #allcont pre, #allcont .enlighter-default { margin-top: 20px !important; } #allcont iframe { padding-bottom: 20px; } AI Coding Feels Like Using an Unreliable Compiler Every developer I know is asking roughly the same questions about LLMs.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Strumenta.
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