[ativzzz]

First, don't do what people on the cutting edge are doing. They are AI hobbyists and their methods becomes obsolete within weeks. Many of the tricks they use become first class objects of frontier models/tooling or are unnecessary 2 model versions later.

What you can do is empower your agent to solve more complex problems fully on its own. See if you can write a plan (claude is great at writing plans) that encapsulates all the work needed for a feature. Go back and forth with the AI on the plan. Spend some time thinking about it. Including tests, how the AI can automatically validate that things work, etc. Put it on auto-accept and tab away. Once it finishes, review the code, do your normal QA, follow ups, etc

While it's working, go work on another feature in the same vein. Git worktrees are a simple way to work on the same codebase in parallel (though you likely work on an app that isn't set up for multiple instances of it running in parallel, have fun with that). Containers are another way to run these in parallel. Vibe code yourself a local tool to manage these. This is somewhat built into the claude/codex desktop apps, but you likely need to customize it for your environment

Basically you do the architecture, code review & QA and let the model do as much of the code as possible, and try to do it in parallel. I still do manual coding when I need to explore what a solution might look like, but AI is much faster at experimenting with larger solutions, and if you don't like what it did, it's a `git checkout .` away from a clean slate

How much time you spend on validating is a tradeoff of speed vs correctness needs for your business.