Servers and Homelabs:
What happens when you ask a 2026 coding agent like Claude Code to build a chess engine from scratch (with no plan, no architecture document, no step-by-step guidance) in a language that was never designed for this purpose? Building a chess engine is a non-trivial software engineering challenge: it involves board representation, move generation with dozens of special rules (castling, en passant, promotion), recursive tree search with pruning, evaluation heuristics, as well as a way to assess engine correctness and performance, including Elo rating. Doing it from scratch, with minimal human guidance, is a serious test of what coding agents can do today. Doing it in LaTeX’s macro language, which has no arrays, no functions with return values, no convenient local variables or stack frames, and no built-in support for complex data structures or algorithms? More than that, as far as I can tell, it has never been done before (I could not find any existing TeX chess engine on CTAN, GitHub, or TeX.SE). Yet, the coding agent built a functional chess engine in pure TeX that runs on pdflatex and reaches around 1280 Elo (the level of a casual tournament player). This post dives deep into how this engine, called TeXCCChess, works, the TeX-specific challenges encountered during development. You can play against it in Overleaf (see demo https://youtu.be/ngHMozcyfeY) or your local TeX installation https://youtu.be/Tg4r_bu0ANY, while the source code is available on GitHub https://github.com/acherm/agentic-chessengine-latex-TeXCCChess/，详情可参考新收录的资料
。关于这个话题，新收录的资料提供了深入分析
J. M. W. Turner
Data Rights datarights.ngo🇳🇱。新收录的资料是该领域的重要参考