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[ARTICLE · art-14811] src=lwn.net pub= topic=large-language-models verified=true sentiment=· neutral

Arias: Human Proof for FOSS Contributions

Dillo web browser maintainer Rodrigo Arias Mallo proposed requiring new contributors to submit asciinema recordings of their programming sessions as proof of human authorship, aiming to filter out AI-generated patches. Mallo argued that large language models struggle to produce realistic recordings of human coding behavior due to insufficient training data on developer workflows and mistakes. The Dillo project has not yet implemented the requirement, but Mallo plans to test the approach further.

read1 min publishedMay 27, 2026
Rodrigo Arias Mallo, maintainer of the [Dillo](https://dillo-browser.org/) web browser, has written a
[blog post](https://dillo-browser.org/lab/human-proof/)

with a proposal on one way to ensure that a contribution is written by a human and not AI; he suggests asking new contributors to record

their programming session using asciinema. In the same way that LLMs generate patches, they can also generate the asciinema recordings themselves. Then, the contributors can lie to the reviewers pretending to have made the edits. Perhaps surprisingly, this is not a easy task for LLMs, at least from my observations. The corpus of recordings of developers making mistakes and thinking the whole process of editing a file is not as large as the corpus of FOSS programs and patches in which to train an LLM. During my very simple tests I haven't been able to generate an asciinema session that remotely resembles what I would expect from a human, and even less so from a human with a nice editor theme and editing an existing Dillo source file.

The Dillo project is not yet requiring asciinema recordings, but he said that he would like to test the theory further. LWN covered asciinema in January 2026.

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