Ramp's code generation by AI has rapidly increased from 30% to 50% in three months. This isn't just for prototypes but for the entire production stack, back-end and front-end, signaling a fundamental shift in software development that makes the entire company more productive.

Michael Bolin, a tech lead on OpenAI's Codex, says models now generate 80-90% of his code. He reserves manual coding for critical, low-level tasks like security sandboxing. For most work, including debugging and refactoring, he relies on the AI agent to maximize his throughput.

AI coding has advanced so rapidly that tools like Claude Code are now responsible for their own development. This signals a fundamental shift in the software engineering profession, requiring programmers to master a new, higher level of abstraction to remain effective.

The Head of Engineering for Atlas estimates that north of 75% of new code is initially written by the AI assistant Codex. This indicates a profound shift where the primary engineering workflow becomes prompting, guiding, and refining AI output, rather than manually writing code from scratch.

Agentic AI is most advanced in software engineering because code provides a constrained, text-based, and verifiable environment. AI agents can now operate for hours, understanding codebases and fixing errors. This iterative reasoning process is a direct preview of how AI will eventually perform long-running, complex investment research tasks.

The rise of powerful AI development tools has flipped the build-versus-buy equation for investment firms. One OCIO went from relying on 90% externally developed tools to building 90% of their software internally, creating highly customized solutions for their specific workflows at a fraction of the previous cost.

The primary impact of AI coding tools is enabling non-coders to perform complex development tasks. For example, a hedge fund analyst can now build sophisticated financial models simply by describing the goal, democratizing software creation for domain experts without coding skills.

AI acts as a massive force multiplier for software development. By using AI agents for coding and code review, with humans providing high-level direction and final approval, a two-person team can achieve the output of a much larger engineering organization.

Experienced engineers using tools like Claude Code are no longer writing significant amounts of code. Their primary role shifts to designing systems, defining tasks, and managing a team of AI agents that perform the actual implementation, fundamentally changing the software development workflow.