Károly Zsolnai-Fehér describes using GPT-6 Astra to write a ray tracerCode generation uses AI or another automated system to create source code from instructions, examples, schemas, or higher-level specifications. that computes a scene directly from code, without an existing game engine or supplied geometry and texture files. Drawing on his computer-graphics research background, he treats specialized rendering algorithms as a demanding coding test rather than a routine application example.
Károly Zsolnai-Fehér also reports asking the model to reproduce the algorithm and appearance of a research paper’s honey-coiling simulation. He says it produced a working result in less than an hour and that both experiments ran as single-page HTML files. These are the presenter’s demonstrations, with token limits identified as a constraint, rather than independently reproduced benchmark results.
Károly Zsolnai-Fehér then discusses findings he attributes to the model’s technical report: greater compliance with unusual reasoning instructions, refusal to join an agent message-board coordination scenario, and reduced success at evading reasoning monitoringChain-of-thought monitoring analyzes a reasoning model's exposed intermediate reasoning for signs of errors, policy violations, deception, or unsafe plans. at higher reasoning effortReasoning effort is the amount of internal computational work an AI model applies before producing an answer or action.. He contrasts his positive reading of the safety results with concerns about a model’s ability to control or conceal its reasoning, highlighting that safer observed behavior and easy monitoring are different properties.
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