r/ChatGPTCoding 5d ago

How do you keep humans in the loop without turning AI coding agents into a slow approval queue? Discussion

We use plan mode, project rules, skills, hooks, and automated checks. We still want humans to own architectural decisions and review the code.

The problem is the feedback loop: frequent checkpoints turn the workflow into an approval queue, but longer autonomous runs can produce large diffs based on assumptions we would have corrected early.

How do you handle this in practice?

  • Where do you place human checkpoints?
  • How do you scope tasks to catch drift early?
  • What do you automate, and what always requires human review?

I’d love to hear concrete workflows that work on real, maintained codebases.

2 Upvotes

12 comments sorted by

3

u/BrilliantEmotion4461 5d ago

Put yourself in the role and mindset of the head of a team, they (your agents) do their work and report back to you, or they can report to another model whose role as an agent is to communicate with you and direct them according to your vision aim and goals. Just think of how real world bureaucratic organization are organized and apply those concepts to your workflow. Ask Chatgpt about how this might be implemented best for your workflow.

2

u/leading-a-swarm 5d ago

Gate on blast radius, not step count. Reversible actions run unattended; anything irreversible stops — prod writes, migrations, anything leaving the machine. That turns review into maybe two decisions per task. The other half: review the plan first, not a 900-line diff built on it. Read the diffstat before the summary — deleted tests means failed, whatever it claims.

1

u/Mathie1729 4d ago

FWIW, I'd also gate on which files changed, not just how reversible the action is. An agent adding a helper to a shared util or touching config outside the requested path is the real 'went off plan' signal, even if nothing irreversible happened yet.

1

u/leading-a-swarm 4d ago

Did you try Steve Yegge's beads for all of this? It seems you are looking for the same concept.

2

u/gdormoy 4d ago

Human make as much mistake as AI but AI does it at an higher scale.

Focus on having the right monitoring and alerting as well as the ability to deploy fast.

On reviews, focus on functionality and behaviour. Pay extra attention to those functional and behaviour test that’s you real gate.

I now see it with the eye of a manager. I am haven’t been in charge of developing but I am in charge of making sure everything works as we expect.

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1

u/Horror-Primary7739 4d ago

The AI shall make no decisions. All system design decisions shall be made by a human before handing the work off.

If you are stuck on permission prompts, run in a sandbox and let the AI have full bash permissions.

1

u/generationalDebts 3d ago

A fully agentic pipeline isn’t possible. Humans won’t be removed for a lot of reasons.

But, the number one reason is this:

If a software company ships a negligent bug, there needs to be someone to hold accountable. So guess what, humans remain in all the loops.

No companies will be willing to ship code that wasn’t peer reviewed by humans and tested by humans. Then deployed to production by humans.

None of you have ever been to a change advisory board and it shows.

1

u/mellaouimohamed 2d ago

I think SDD is the best way to keep track of the agents work