AI dev speed challenges controls

Software teams used to worry about one developer pushing one risky change. Now one person can ask an artificial intelligence coding agent to touch multiple files, run commands, and keep editing until the task looks done. (code.visualstudio.com) That shift changes what “review” means. Microsoft’s Visual Studio Code 1.115, released on April 8, 2026, previews a separate VS Code Agents app that can run agent sessions across multiple repositories in parallel, each in its own worktree. (code.visualstudio.com) A worktree is basically a second checkout of the same repository, like opening several copies of the same document on different desks so different helpers can mark them up at once. VS Code says the new app lets developers switch between those parallel sessions, inspect diffs inline, leave feedback, and create pull requests without leaving the app. (code.visualstudio.com) The promise is speed. InfoWorld reported on April 9 that developers using artificial intelligence coding assistants often describe productivity gains in the 15% to 55% range, which is why these tools are spreading so fast inside engineering teams. (infoworld.com) The catch is that faster typing is not the same thing as safer changes. The same InfoWorld piece says artificial intelligence generated code can pile up technical debt, hide bugs that ordinary code review misses, and open security holes if teams skip practices like pair programming and automated tests. (infoworld.com) Technical debt is borrowed time in code form. It is what happens when a team ships a shortcut today and leaves tomorrow’s engineers a mess of brittle logic, missing tests, and confusing dependencies to clean up later. (deloitte.com) That is why older agile habits are back in the spotlight. InfoWorld argues that test-driven development, behavior-driven development, acceptance test-driven development, pair programming, and continuous integration now work less like process theater and more like guardrails for machine-generated changes. (infoworld.com) The tools are also getting more autonomous, not less. GitHub’s April 8 release notes say Visual Studio Code now includes an Autopilot preview where agents can approve their own actions, retry after errors, and continue until a task completes without manual approval. (github.blog) Once software starts changing itself in loops, change-control gets harder to prove. Deloitte wrote in 2024 that organizations integrating generative artificial intelligence into the software development life cycle are already prioritizing stronger testing and validation, and nearly half are increasing cross-functional collaboration to manage those outputs. (deloitte.com) The practical problem is evidence. If one developer launches several agents, each agent edits files, runs tools, and maybe calls outside services through Model Context Protocol servers, an auditor or team lead has to reconstruct who approved what, which tests ran, and which change actually reached production. (code.visualstudio.com, github.blog) So the story is not that artificial intelligence writes code now. The story is that code generation is becoming a multi-agent workflow inside the repository itself, and the teams that keep their tests, reviews, and approval trails intact will be the ones that can move fast without losing control. (code.visualstudio.com, infoworld.com)