The Bottleneck in AI Development: Humans (www.nibzard.com)

After months advising Verdent AI, the author argues the industry is moving from an “assistant era” (one human, one agent) into an “orchestration era” where humans become the bottleneck. Current tools speed individual coding tasks but still rely on single-threaded human supervision; the next phase will coordinate many AI agents in parallel, leveraging compute that already outstrips human capacity. That shift promises exponential productivity gains by allowing workflows that maintain perfect working memory, run multiple contexts simultaneously, scale compute dynamically, and execute complex verification loops without constant human intervention—but it exposes new challenges around observability, trust, and debugging. Verdent’s bet is to build the infrastructure for that orchestration: a plan-first architecture, multiple agents running in isolated Git worktrees with shared understanding, real-time task dashboards, DiffLens that explains why code changed, and verification reports that show which agents met acceptance criteria. The broader implications for ML teams are clear: models will commoditize, so interfaces and orchestration will be the real competitive edge; security must be embedded into workflows (sandboxing, formal checks) rather than patched afterward; and teams that embrace higher process complexity will outproduce those stuck in linear, human-scale patterns. It’s early and risky, but orchestration-first platforms could define Act Three of software development.