Skip to content
Notifications
Clear all

Beginner question: Where do I find logs of the assistant's internal reasoning?

1 Posts
1 Users
0 Reactions
3 Views
(@averyd)
Estimable Member
Joined: 1 week ago
Posts: 120
Topic starter   [#13609]

I’ve noticed a common point of confusion among newcomers when troubleshooting assistant-generated code or recommendations: the desire to see the “internal reasoning” or a “chain of thought” log. This comes up especially when an assistant’s suggestion fails silently or produces an unexpected result.

The short answer is: **you generally don’t have access to that log.** Assistants typically provide only their final output, not the intermediary reasoning steps. This is a fundamental characteristic of the current generation of AI assistants—they are optimized to deliver a conclusion, not a transparent audit trail of how they arrived at it.

This leads to a reproducible failure case:
* **User Prompt:** “Show me the step-by-step reasoning you just used to arrive at your AWS cost-optimization suggestion.”
* **Assistant Output:** Often, the assistant will happily *generate a plausible-sounding* step-by-step breakdown. However, this is not a true log; it’s a newly generated text describing a *possible* reasoning path. It may omit key missteps or be a complete fabrication.
* **Correct Reality:** There is no system-provided, verifiable log of the model’s internal process. The only “ground truth” is the final text output itself.

This creates a real problem for debugging. For example, if an assistant recommends switching an EC2 instance family and purchasing Reserved Instances based on a flawed calculation, you cannot inspect its “thought process” to find the arithmetic error. You’re left reverse-engineering the error from the flawed output.

The proper approach is to treat the assistant as a black-box advisor and apply standard validation practices:
- Ask for citations or sources for factual claims (e.g., API names, pricing formulas).
- Request the assistant to “show its work” in the output itself, like providing the calculated numbers.
- Independently verify critical recommendations against official documentation or your own billing data.

It’s a limitation worth being acutely aware of, especially in FinOps where cost decisions require precision.

—A


Every dollar counts.


   
Quote