Adam Analytics And Recommendations

Adam turns model, tool, endpoint, and conversation telemetry into operational insight. The product should help teams understand what agents are doing, where risk appears, and which patterns deserve attention.

Signals Adam Uses

Adam can use telemetry from:

model requests and provider responses,
token usage and provider latency,
tool attempts and failures,
endpoint query patterns,
policy warnings or blocks,
PII and secret detection,
workflow execution,
and migration or infrastructure events surfaced through Eve.

Recommendation Categories

Category	Examples
Performance	Slow queries, hot keys, high fanout, large responses, N+1 patterns.
Cost	Expensive model routes, repeated tool calls, oversized prompts, inefficient workflows.
Security	PII exposure, secrets in prompts or results, unauthorized tool attempts.
Reliability	Error-rate changes, endpoint health degradation, tool timeouts.
Operations	Migration readiness, rollback warnings, capacity pressure, missing observability.

How Recommendations Should Be Presented

Useful recommendations include:

a clear finding,
severity,
confidence,
evidence,
affected endpoint or tool,
estimated impact when available,
and a specific next action.

Avoid recommendations that only restate metrics. For example, "p99 latency is high" is less useful than "Redis key pattern cart:* is responsible for most p99 latency because 18 percent of traffic hits one hot key family."

Analytics Rollout

Roll out analytics in stages:

Enable basic request and tool metrics.
Confirm attribution by organization, user, endpoint, model, and tool.
Add bounded sampling for deeper request analysis.
Tune severity thresholds for the customer's workload.
Enable recommendations once the signal quality is acceptable.
Review recommendations with operators before automatic workflow actions.

Customer Success Questions

When onboarding a customer, ask:

Which endpoints or tools are most critical?
Which model providers and tools should have cost tracking?
Which data types are sensitive?
Which operations require approval?
What latency and error-rate thresholds matter?
Which recommendations should page someone versus become backlog items?