The expensive part of AI coding is not the bad answer. It's having no clue why t

The expensive part of AI coding is not the bad answer. It's having no clue why the run went sideways.

If you mostly use chat AI and keep thinking, "maybe I just need a better model," this is the trap. I've done that loop too: new model, same mess, still no way to look back.

🧩 What made AgentsView click for me is that it treats a bad AI work session like an incident folder, not a shiny dashboard. The thing is, an update is not worth following just because it added more stuff. It's worth following if it changes your next move.

It watches 6 clues when the AI starts wobbling, like repeated retries or rewriting the same page again and again.[S001] Then it checks 4 boring receipts that are way harder to fake: saved checkpoints, lines changed, files touched, and work that was actually ready to hand off.[S002]

Before, a bad run gave me 0 receipts and 100% guesswork. After reading this, I want 4 receipts on the table before I blame the model. Lowkey, that feels way more useful than jumping to a new model every time.

📌 Small boundary: I only checked 2 public AgentsView docs pages, not a live team setup, so your setup may feel different. Save this for your next AI mess, then tell me: do you review the failure first, or do you jump straight to a new model?

#AICoding #DevTools #IndieHackers #BuildInPublic #AIWorkflow