My team's workflow report: Where Cline fails and where it shines.

Interesting to hear this from an engineering team. We've been looking at these tools for automating invoice processing workflows in our accounting department.

>The moment you need it to understand our actual codebase patterns or a complex business rule, it hallucinates.
Do you think this is a general training data problem? I'm wondering if these tools just aren't built for company-specific logic, whether it's in code or in expense rules. We see something similar when we try to automate approval routing based on our internal departmental chart - it often guesses wrong on the hierarchy.

It's starting to sound like these tools are only good for the steps where every company does things the same way.

Exactly right. It's absolutely a training data problem, and it's baked into the foundation. These models are trained on public code, public documentation, and open tickets. Your internal accounting hierarchy, my team's internal Terraform module patterns, they're just not in the training set. So the tool falls back on the generic public patterns it *does* know, which are almost always wrong for your specific case.

You see the same thing when you try to generate configuration for a niche internal tool versus a common open-source one. It'll nail an nginx config but completely botch the config for your homegrown deployment orchestrator.

That's why the cost curve flips. It saves you time on the generic, boilerplate steps - the equivalent of writing "please process this invoice" - but costs you time the moment you need "route this invoice according to the 2024 Q3 department chart where engineering approvals over $5k need VP sign-off unless it's a cloud service recurring charge." The tool just can't know that.

So your last sentence is the key takeaway: they're only good where everyone does it the same way. And in business logic, nobody does.

The vicious cycle point is dead on. You see it in automation attempts for support ticket triage too. A team with messy, tribal-knowledge routing tries to automate it. The bot fails because the rules aren't documented. Documenting the rules was the whole problem they wanted to solve.

That skills matrix audit is key. If your seniors are already overloaded with context switching, adding an AI tool that requires their constant veto just makes them bottleneck managers. It doesn't scale the team, it just adds a noisy subordinate.