GitLab says Git is being reengineered for "machine scale." Was the idea of "Git for AI agents" ahead of its time?

I was reading GitLab's recent statements around agentic software engineering, and one quote really stood out: *"Git itself is being reengineered for machine scale."* ([Business Insider](https://www.businessinsider.com/gitlab-layoffs-memo-2026-5?utm_source=chatgpt.com)) According to GitLab, future software development will involve AI agents that: * plan, * code, * review, * deploy, * and repair software, with humans providing oversight and architectural judgment. ([Business Insider](https://www.businessinsider.com/gitlab-layoffs-memo-2026-5?utm_source=chatgpt.com)) That got me thinking. There has been projects for some time arguing that AI agents shouldn't simply be treated as **better autocomplete systems**. Instead, they argued that agents should become **first-class participants in software development**: * with their own identities, * their own branches, * their own merge requests, * their own audit trails, * and infrastructure designed for machine-rate collaboration. One example is **GitLawb**, which has described itself as a kind of "Git for agents." At the time, a lot of people dismissed these ideas as unnecessary or overly ambitious. But now GitLab—a multi-billion-dollar DevSecOps company—is talking about: * agent-specific APIs, * machine-scale Git infrastructure, * orchestration layers coordinating agents, * and agents acting as first-class users of development platforms. ([Business Insider](https://www.businessinsider.com/gitlab-layoffs-memo-2026-5?utm_source=chatgpt.com)) It does raise an interesting question: Was the underlying thesis correct all along? We've seen similar patterns before: * Containers existed before Kubernetes became the standard. * Electric vehicle startups pushed ideas that incumbents later adopted. * Cloud-native companies advocated architectures that the rest of the industry eventually embraced. The original innovators don't always dominate the market. But when major incumbents begin rebuilding around similar assumptions, it often suggests that the **problem itself is real**. So I'm curious what this community thinks: **Do AI agents require an entirely new layer of collaboration infrastructure?** Or will existing platforms simply evolve enough to absorb these workflows? Because if GitLab is right, software development may be transitioning from:humans using AI tools to humans managing teams of AI developers. And if that's the case, version control itself may have to evolve.