Agent QA, Audits & Run Logs: How to Keep Your AI “Digital Employee” On Task

Small businesses are moving fast with AI agents. The risk isn’t the tech—it’s drift: gaps between intent and what the agent does. Fix it by treating the agent like a new hire: set run logs, QA, and audits. This guide gives you clear templates and thresholds.

Agent QA, Audits & Run Logs: How to Keep Your AI “Digital Employee” On Task

The Core Idea

If it isn’t logged, it can’t be trusted—or improved. Put lightweight guardrails in place:

  • Run Log (every execution)
  • Weekly Audit (spot checks + metrics)
  • RAG Thresholds (red/amber/green triggers)
  • Rollback Plan (pre-approved “off switch”)
  • Change Control (one-page record of updates)

1) The Run Log (Copy/Paste Template)

Track the minimum that lets you diagnose issues fast.

Fields:

  • timestamp
  • who/what triggered (user, schedule, webhook)
  • task_name (e.g., “FAQ reply”, “Lead enrichment”)
  • inputs_ref (link or ID to source data)
  • tools_used (email, sheets, CRM, browser)
  • output_ref (file/record link)
  • result (success | partial | fail)
  • confidence_note (short text; model self-rating)
  • human_review (yes/no + reviewer)
  • exceptions (timeouts, blocked domains, API errors)
  • PII_touched (yes/no)
  • SLA_seconds

CSV starter:

timestamp,trigger,task_name,inputs_ref,tools_used,output_ref,result,confidence_note,human_review,exceptions,PII_touched,SLA_seconds
2025-10-14T09:15:12Z,schedule,FAQ reply,faq_v4.md;ticket#1832,email;sheets,reply_1832.eml,success,"Matched policy; cited section 3.2",no,,no,42

2) RAG Thresholds (Flag Problems Before Users Do)

Define what “good” looks like, then color-code it.

Quality (manual spot-check rate weekly):

  • Green: ≥ 95% accurate; 0 critical errors
  • Amber: 90–94% accurate; ≤ 1 minor error
  • Red: < 90% or any critical error (wrong price, PII leak, policy breach)

Latency (SLA to first draft):

  • Green: ≤ 60s
  • Amber: 61–120s
  • Red: > 120s or timeouts

Escalations/Exceptions per 100 runs:

  • Green: ≤ 2
  • Amber: 3–5
  • Red: > 5

PII/Restricted Data touches (where applicable):

  • Green: 0 without human approval
  • Red: Any unauthorized touch

3) Weekly Audit Flow (30–45 minutes)

  1. Pull last week’s run log. Filter by task.
  2. Randomly sample 10–20 runs (or 5% if volume is huge).
  3. Score against your checklist (see below).
  4. Compute hit rates: accuracy, SLA, exceptions.
  5. Tag root causes (input, tool, prompt, policy).
  6. Create 2–3 small fixes (not five big ones).
  7. Decide status: Green (continue), Amber (tighten), Red (rollback).

Audit checklist (yes/no):

  • Cites or links source where policy requires it
  • Uses approved style & disclaimers
  • No hallucinated data/claims
  • Followed tool scope and rate card
  • Respected privacy/PII rules
  • Output landed in the right system/location

4) Rollback Plan (Pre-Write It)

When you hit Red, you don’t want a debate; you want a switch.

Rollback steps:

  1. Disable auto-runs; set the agent to “draft-only.”
  2. Route tasks to a fallback template or human queue.
  3. Announce internally (one-liner: “Agent paused for QA—ETA after fixes.”)
  4. Patch (prompt, tool permissions, input filters).
  5. Re-enable with a 10-run pilot before full return.

5) Change Control (One Page, Always)

Keep a living record so you can answer “what changed?”

Fields:

  • date
  • change_owner
  • what_changed (prompt, tool, dataset, policy)
  • why (metric or incident)
  • risk (low/med/high)
  • test_result (pilot stats)
  • next_review_date

6) Human-in-the-Loop (HITL) Where It Matters

Don’t review everything—review what carries risk:

  • Customer-facing emails & quotes
  • Policy and legal language
  • Any action that moves money, inventory, or access

HITL pattern: agent drafts → human approves → agent sends/logs.

7) Metrics That Actually Move the Needle

  • Time-to-first-draft (seconds)
  • Edit rate (human edits per draft)
  • Accuracy (audit pass %)
  • Exception rate (% runs with errors)
  • Business outcome (bookings, replies, closed tickets)

Track weekly; if a metric stalls for 2–3 weeks, change something structural (inputs, policy card, or tool scope).

8) The Policy/Style Card (Pin This Next to the Agent)

  • Voice: short, direct, no fluff; 6th–8th grade readability
  • Non-negotiables: don’t guess; cite sources; never promise delivery dates
  • PII rules: never store full card numbers; mask SSN; link to privacy notice
  • Escalate when: missing data, legal/price question, unhappy sentiment
  • Sign-offs: team name, support hours, contact path

9) Starter Pack (Copy & Go)

  • Run Log (CSV sheet)
  • Weekly Audit Checklist (10 yes/no items)
  • RAG Thresholds (four lines)
  • Rollback SOP (5 steps)
  • Change Control Doc (1 pager)
    Bundle those into a single shared folder and make it part of onboarding for every new agent.

Bottom Line

AI agents don’t fail suddenly; they drift. A lightweight QA loop—run logs + weekly audits + clear thresholds + rollback—keeps your “digital employee” sharp, safe, and profitable.

Ready to put this QA loop to work? Contact BoostMyAI to get started today.