"AI coding tools have caused as many problems as they have solved, according to industry experts. The easy-to-use and accessible nature of AI coding tools has enabled a flood of bad code that threatens to overwhelm projects. Building new features is easier than ever, but maintaining them is just as hard and threatens to further fragment software ecosystems. The result is a more complicated story than simple software abundance."
""For people who are junior to the VLC codebase, the quality of the merge requests we see is abysmal," Jean-Baptiste Kempf, the CEO of the VideoLan Organization that oversees VLC, said in a recent interview. Kempf is still optimistic about AI coding tools overall but says they're best "for experienced developers." There have been similar problems at Blender, a 3D modeling tool that has been maintained as open source since 2002. Blender Foundation CEO Franceso Siddi said LLM-assisted contributions typically "wasted reviewers' time and affected their motivation.""
AI coding tools have increased the ease of building new features while also lowering barriers to contribution, producing a higher volume of lower-quality submissions. Open-source projects report declines in average submission quality, with junior contributors producing problematic merge requests that burden reviewers. The accessibility of LLM-assisted coding has enabled a flood of bad code that risks overwhelming projects and fragmenting ecosystems. While some leaders remain optimistic and see AI as useful for experienced developers, maintenance and reviewer workload have worsened, negatively affecting motivation and threatening long-term project sustainability.
Read at TechCrunch
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