Recently, I wrote about how working on mature Salesforce orgs is like archaeology – we have to dig up the logic behind old processes before building new ones. The upcoming Spring ’26 release confirms that this approach is becoming the new standard. Innovations like Agentic Flow and the Zero Copy extension prove that Salesforce is betting everything on autonomy.
However, from an analyst’s perspective, the most critical element will be Agent Health.
What will Agent Health be? It’s a diagnostic panel that will show us how autonomous agents are performing. These won’t be just standard technical error logs, but a deep insight into whether an agent understands our instructions and can navigate the data and processes we’ve provided.
For us analysts, Agent Health will become a tool for verifying the quality of our work. If the results are poor, it usually won’t be a failure of the technology itself, but rather a lack of precision in preparing the system’s logical foundation.
3 signals in Agent Health to watch out for:
- High escalation rate at a repeatable point – This will show exactly where our “archaeology” was incomplete and where a business exception was missed in our instructions.
- Low Grounding Score – A sign that the agent is getting lost in the data. This is often the result of “org pollution” (e.g., redundant, undocumented fields). If the agent isn’t sure which information is current, it will start generating inconsistent responses.
- Decision loops and step limit exceeded – This indicates that the instructions in the User Stories are too vague or conflict with existing system logic. This is the exact moment where new automation “clashes” with unexamined legacy architecture.
Conclusion
In Spring ’26, the role of the analyst will shift even further toward designing robust logic and ensuring data quality. Agent Health will allow us to reliably evaluate the testing phase, helping us verify that autonomous agents are operating according to the intended logic before we release them to all users.
