We are entering the era of the infinite codebase. With agents, the code repository is no longer a fixed artifact maintained by hand. It’s becoming a living system, where code is constantly being generated, forked, and rewritten on demand. The data reflects this. In just a few years, the volume of code and software projects flowing through GitHub has grown exponentially. All this code has strained developer workflows, creating a crisis of legibility. When an agent produces thousands of lines in seconds, it creates a black box. Developers inherit mountains of “ghost code” they can’t fully explain, maintain, or debug. The problem balloons as teams of humans and agents, each with different working styles and objectives, pile changes into the same project. Existing dev tools weren’t designed for this level of throughput. Historically, Git, the standard for storing and versioning code, captured what was written – the the code itself, tracking diffs between contributors. But it did not capture why – the spec and prompts that initiated the work, the paths accepted and discarded by the developer and agents, the trail of decisions that collectively tell the story of how a piece of software got built. Now that code itself is cheap and abundant, the why – the full reasoning process behind the code – is a more valuable data asset than code itself. With it, agents can stop repeating mistakes and deliver higher accuracy, which saves time and token spend. Humans can more easily audit what was written and why. Handoffs between agent and human collaborators are more seamless. This insight led former GitHub CEO Thomas Dohmke to launch Entire, a new development platform and system of record for software in the era of agents. Entire’s CLI hooks into agent workflows and captures the full coding session – all the developer prompts, agent transcripts, and tool calls. It then indexes and versions that data into a searchable, legible record that sits alongside the code. Every commit now traces back to the exact conversation, the entire history, that created it for humans and agents to read. It’s one of the AI-native products I’m most excited about right now. It’s seamless and easy to use – a beautiful blueprint for how humans and AI will collaborate at scale, letting us work at a higher level of abstraction without losing control. I sat down with Thomas to talk about how software development is changing, his strategy to own the agentic record, and what happens once we open the black box… when we capture the soul of software. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thetimes.blog
