# Agentic Very Much! Adoption of Coding Agent in New GitHub Projects

arXiv: https://arxiv.org/abs/2606.07448 · HTML: https://mlsanity.com/paper/2606.07448/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- Builds on 3 of its 3 references that are in the map.
- First posted on arXiv 5 Jun 2026.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Builds on (most cited first, 3 of 3)

- [Agentic Much? Adoption of Coding Agents on GitHub](https://mlsanity.com/paper/2601.18341/) (2026)
- [Sampling Projects in GitHub for MSR Studies](https://mlsanity.com/paper/2103.04682/) (2021)
- [Promises, Perils, and (Timely) Heuristics for Mining Coding Agent Activity](https://mlsanity.com/paper/2601.18345/) (2026)

## Abstract (arXiv)

In previous work, we investigated the adoption of coding agents in GitHub projects, finding that it was very significant. This study follows this line of work, but analyses new projects, that were created after the previous study. In this new sample, we find that the adoption of coding agents is more than twice as high. We also find that the adoption is significantly more intensive, as the proportion of AI-assisted commits is sensibly higher, despite strong signs that we do not detect all of it.