> ## Documentation Index
> Fetch the complete documentation index at: https://apie.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Runtime intelligence

> Turn session telemetry into a readable story, action items, and guardrail recommendations.

You already have raw runtime events, guardrail decisions, approvals, and receipts. Runtime intelligence adds the product layer on top: it turns a session into a short summary, a grouped story timeline, follow-up action items, and guardrail recommendations you can review in the dashboard.

When it is ready, you can answer "what happened, why did it matter, and what should we change next?" without reading every event by hand.

<Note>
  Runtime intelligence is derived from telemetry. Raw events, guardrail decisions, approvals, receipts, declared capabilities, and boundary records remain the source of truth.
</Note>

## What appears

| Dashboard surface         | What it tells you                                                                                                     | Evidence behind it                                                                           |
| ------------------------- | --------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- |
| Session summary           | A plain-language title, outcome, primary actor, involved tools/resources/environments, risk level, and confidence     | Event ids from the session                                                                   |
| Story timeline            | A compressed timeline of meaningful steps, not one card per event unless the event matters on its own                 | Event ids, plus related guardrail decision, approval, and receipt ids when present           |
| Action items              | Concrete next steps such as reviewing an unknown tool, declaring a capability, requiring approval, or fixing metadata | Evidence event ids and a confidence label                                                    |
| Guardrail recommendations | Suggested monitor, warning, approval, or block policies for the observed behavior                                     | Evidence event ids, affected tool/action/resource/environment, and any matching template key |

Runtime intelligence can return no action items. For example, a harmless read-only session should produce a readable story without telling you to do unnecessary work.

## When it appears

Runtime intelligence is generated for sessions with events. It is usually queued when a session completes, when a run completes, when an error or failed action occurs, when an approval is requested or resolved, or when Apie observes a high-signal event such as:

* A guardrail decision that warns, blocks, or requires approval
* An unknown action or resource
* A production create, update, delete, or execute action
* Access to risky resources such as secrets, pipeline runs, deployment events, or database records

While generation is running, the dashboard can show **Story generation queued** or **Generating session story**. When the result validates, the story replaces the deterministic fallback view.

If new events arrive after a result was generated, the dashboard marks the story as **Newer events are available** and keeps the previous result visible until a newer result is ready. Workspace managers can regenerate a stale or failed story from the session replay page.

## How it relates to raw events

The raw event stream stays available for audit and debugging. Runtime intelligence reads a compact, redacted context built from those events and produces a validated view for the dashboard.

Each useful claim must point back to evidence:

| Field              | Why it matters                                                                                  |
| ------------------ | ----------------------------------------------------------------------------------------------- |
| `evidenceEventIds` | Lets you jump from a summary, action item, or recommendation back to the events that support it |
| `sourceBasis`      | Distinguishes declared, observed, inferred, unknown, and violated behavior                      |
| `confidence`       | Shows whether the interpretation is high confidence or should be treated cautiously             |
| `contextWarnings`  | Surfaces limits in the available context, such as compacted or incomplete evidence              |

The generated story may infer meaning from event labels, metadata, and guardrail context, but it should use "unknown" when the evidence is not strong enough. It does not overwrite event metadata or boundary records.

## How it relates to guardrails

Guardrails decide what happens at runtime. Runtime intelligence explains what happened after the fact and may recommend what to guard next.

| Guardrail concept           | Runtime intelligence behavior                                                                 |
| --------------------------- | --------------------------------------------------------------------------------------------- |
| Existing guardrail decision | Timeline cards can reference the decision that allowed, warned, blocked, or required approval |
| Approval request            | Timeline cards can link the approval that paused or resolved the action                       |
| Recommended guardrail       | The dashboard can suggest a mode such as Monitor, Warn, Require approval, or Block            |
| Declared capabilities       | Action items can suggest declaring expected tools or fixing missing action/resource metadata  |

A recommendation is not an active policy. Review it against your production intent, then enable the matching template or create the guardrail you want.

## Statuses

| Status        | Meaning                                                             |
| ------------- | ------------------------------------------------------------------- |
| `not_started` | Apie has deterministic session metadata, but no generated story yet |
| `queued`      | A generation job is waiting to run                                  |
| `processing`  | The story is being generated and validated                          |
| `ready`       | A validated story is available                                      |
| `stale`       | A previous story is visible, but newer events exist                 |
| `failed`      | Generation failed; deterministic session data is still available    |
| `disabled`    | Runtime intelligence is off for the workspace or environment        |

## Evidence and redaction

Runtime intelligence is designed for review, not certification. It should not claim that an agent is safe, compliant, certified, fully governed, or fully controlled.

Before model generation, Apie builds a compact context from canonical fields, redacted metadata summaries, evidence ids, guardrail references, approvals, receipts, declared tools, boundary state, and agent profile data. If sensitive content is still detected in the final model input, generation fails instead of sending that input.

## Next steps

<CardGroup cols={2}>
  <Card title="Walk through a generated story" icon="book-open" href="/recipes/runtime-intelligence-walkthrough">
    See how a release session turns into a summary, story timeline, action items, and guardrail recommendations.
  </Card>

  <Card title="Trace runs and sessions" icon="timeline" href="/observe/trace-runs-and-sessions">
    Capture the session and event data runtime intelligence uses.
  </Card>
</CardGroup>