The more we build onto our AI agent, the worse it gets

[Thirteenth]

We started with a pretty simple agent built around one workflow, and honestly it did its job well. Then over time it turned into something else entirely. New instructions got added, then more tools, then fallback rules, then edge case handling from three different teams, and now the thing technically covers way more ground but feels completely unreliable. It'll follow the wrong workflow, miss context that's sitting right there, or go through a whole chain of tool calls when a single sentence would've done it. The behavior has clearly shifted but pinning down exactly which change broke what is near impossible. Every modification seemed reasonable at the time. How are other teams actually keeping track of what's working in their agents once the instructions and capabilities start stacking up?

 

[Lovol]

Inconsistent behavior is almost always a sign the instruction set has outpaced the evaluation framework around it. Every team adds what feels like a small tweak, but the model's now juggling twenty competing priorities and latching onto whichever one feels most relevant in the moment. The answer isn't pruning instructions, it's building actual regression testing so you know what changed between versions. Run the same set of representative inputs before and after every modification and compare outputs systematically, not just spot-checking a few cases and calling it done.

 

[Egglex]

A lot of teams hit this exact wall at roughly the same point, when the agent stops doing one thing well and starts trying to satisfy everyone at once. That's when the evaluation layer becomes what actually determines whether you can scale the agent or just keep adding to the pile. You can do your agent optimization here https://eignex.com/ . The tooling there handles exactly this kind of complexity, tracking behavior across versions and pinpointing which changes are actually making a difference. Beats trying to eyeball outputs and reverse-engineer what went sideways.