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Private beta: AI SRE is currently in private beta and available to invited accounts only. To join the whitelist test, contact the Flashduty sales team to request access; features and the UI may change during the beta.

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Overview

Type /insight in the input box of any AI SRE session and AI SRE will look back at your last 30 days of sessions to produce a single-page operational insight report. The report uses a parchment-style HTML layout and renders directly in the session as a chat card, which you can preview and download. The report answers three questions: how much you did with AI SRE this month, what you were mainly working on, and which recurring “friction” patterns are most worth eliminating right now. Friction refers to patterns that repeatedly drain your time — for example, pasting the same database connection string across multiple sessions, an agent missing a runbook it should already know, or it repeatedly querying the wrong data source.
/insight is read-only. It only analyzes and presents; it will not automatically modify any knowledge, skill, or MCP configuration. Every suggestion is copyable text — whether to act on it is entirely up to you. See How to Act on Suggestions.
/insight is a built-in AI SRE skill: it automatically exports your past sessions, computes quantitative metrics, analyzes the session content section by section, and renders a consolidated report. The entire process is transparent to you — all you need to do is type /insight.

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How to Generate

1

Type /insight in a session

Type /insight in the input box of any AI SRE session and send it. No parameters are required.
2

AI SRE automatically determines the analysis scope

The scope depends on whether the current session is bound to a team (see the table below). AI SRE will state the analysis scope and time window (default: last 30 days) at the beginning of the report.
3

Wait for the report to render

AI SRE exports sessions, computes metrics, analyzes the content, and then renders the parchment-style report as a chat card, accompanied by a 2–3 sentence spoken summary. You can preview or download the full report from the card.

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Analysis Scope

/insight always uses the account as the security boundary — it only sees sessions readable by the current app_key and never crosses that boundary. Within that boundary, the specific scope depends on whether the session is bound to a team:
If your session is not bound to a team but you only want to see a specific team’s data, name that team (by name or ID) when you type /insight. AI SRE will ask you to confirm before narrowing the scope to that team.

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How the Report Is Produced

Understanding how the report is put together helps you see where the numbers come from:
AI SRE first lists the sessions within scope for the last 30 days (up to 200 by default) and exports their full records, then keeps only multi-turn sessions — sessions where you sent ≥ 2 messages. Single-turn sessions have no learnable friction and are excluded from friction analysis.
The report’s first layer (quantitative overview) — session count, your turn count, tool call count, average turns, daily activity, tool and skill distribution, model distribution, and outcome distribution — is computed deterministically across all sessions by program logic, not estimated by the model, so it is reliable and always present even when no friction is found.
AI SRE reads the session records in sections, distilling “session topics” and “friction findings” from each, then consolidates everything: topics are aggregated into a narrative overview, and findings are deduplicated, clustered, and ranked by importance into friction cards. The report contains only the distilled topics and findings — it does not copy your raw session content verbatim.

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Report Contents

The report is structured in three layers from top to bottom. Regardless of whether any friction is found, the first layer (quantitative overview) is always present.

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Layer 1: Quantitative Summary

Computed deterministically by program logic, not estimated by the model; the model only transcribes the numbers into the report. Includes:

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Layer 2: Narrative Overview

A 2–4 sentence second-person summary of what you were mainly working on this month — the most common domains, recurring entities (the same incident analyzed more than once, a cluster or host that kept appearing), and the overall shape of the month’s work. This layer is aggregated from the topics surfaced across your sessions.

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Layer 3: Friction Cards

Friction cards ranked from highest to lowest importance, up to approximately 8 cards. Each card includes:
  • A rank and a friction type label (one of five types; see the next section);
  • A frequency badge showing how many distinct sessions this friction consumed your time in (deduplicated evidence session count);
  • A one-line title and a second-person explanation;
  • Evidence: all real session IDs that match this friction (listed in full, not truncated);
  • A copyable recommendation: text you can paste directly;
  • Destination: which knowledge-base file this text should go into.
Every friction card must reference at least one real session ID as evidence — the report never fabricates sessions, facts, or runbook gaps. If no rankable friction is found, the third layer displays an empty-state message while the first and second layers are still shown — in that case, “the overview itself is the report.”

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Friction Types

/insight recognizes exactly five friction types, each corresponding to a clear, adjustable “dial.” Listed in default importance order:
repeated_context is ranked first because it is the most persistent — the same fact being provided repeatedly across multiple sessions means persisting it into the knowledge base once will benefit every future session. When its evidence count ties with other friction types, it still ranks higher.

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How to Act on Suggestions

The report is read-only: it surfaces problems and provides copyable fix text, but never automatically applies any changes. During the beta, all suggestions are copy-paste style — you confirm them, then manually apply them in the corresponding resource.
1

Read the report and pick what's worth doing

Friction cards are already ranked by importance. Start with the top-ranked cards that have high frequency badge numbers — those are the patterns consuming your time most repeatedly.
2

Copy the suggested text

Each card’s “Copyable suggestion” contains text you can paste directly, and the “Destination” line tells you which knowledge-base file it belongs in.
3

Manually apply it in the corresponding resource

Based on the friction type, paste and save in the appropriate resource: repeated context and hallucinated entities go into the knowledge base’s services.md or DUTY.md; a missing runbook means adding a new runbook to the knowledge base; a wrong data source gets pinned in observability.md / clusters.md; stale knowledge means updating the outdated file directly. These are all standard edits under Knowledges.
/insight will never perform any writes on your behalf — it does not invoke any sync or install actions, and does not modify knowledges, skills, or MCP. If you later want AI SRE to “add this runbook,” that is an independent natural-language instruction and is outside the scope of /insight.
/insight runs on demand, one report at a time — it does not “continuously watch” or generate reports on a schedule. The recommended approach is to run it again after accumulating a few more incident investigations, to see which frictions have been resolved and which new ones have emerged.

Console

Learn about session creation, team binding, and war rooms — these determine the analysis scope of /insight.

Manage Knowledge

Most suggestions from the report land in the knowledge base’s DUTY.md / services.md / runbooks. This page explains how to edit them.

Overview

Get a high-level understanding of AI SRE’s capabilities and how it works.