AI coding agents are rapidly reshaping how software is built, reviewed, and maintained.

As large language model capabilities continue to increase, the bottleneck and software development

is shifting away from cogeneration toward planning, review, deployment, and coordination.

This shift is driving a new class of agentic systems that operate inside constrained environments,

reason over long time horizons, and integrate across tools like IDs, version control systems, and issue trackers.

OpenAI is at the forefront of AI research and product development. In 2025, the company released Codex,

which is an agentic coding system designed to work safely inside sandboxed environments while

collaborating across the modern software development stack. Tibo Sotio is the Codex engineering

lead, and Ed Bays is the Codex product designer. In this episode,

they joined Kevin Ball to discuss how Codex is built, the co-evolution of models and harnesses,

multi-agent futures, Codex's open source CLI, model specialization, latency and performance considerations,

and much more.

Kevin Ball, or K. Ball, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies,

founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through

latent space.

Check out the show notes to follow KBall on Twitter or LinkedIn or visit his website,

kball.l.lc.

Hey guys. Hey, guys, welcome to the show.

Hey.

Hey, thanks for having us.

Yeah, I'm excited about this one.

You guys are doing some really interesting stuff and I want to dig in.

...