In the Professional Scrum Developer (PSD) track, we learn a fundamental truth: You wouldn't ship code without code review, unit tests, integration tests, documentation etc. A rigorous Definition of Done (DoD) is the only thing standing between a high-quality Increment and a buggy, undeliverable mess.
But as Scrum Teams in 2026 begin integrating Autonomous AI Agents (like Devin, Cursor, or custom LLM wrappers) into their workflows, they are discovering a dangerous gap in their DoD.
The problem?
Traditional software is deterministic.
If you run a unit test on a payment calculator 100 times, you get the same result 100 times.
AI, however, is probabilistic.
Run the same prompt through an LLM 100 times, and you might get 95 correct answers and 5 "hallucinations."
If your Definition of Done relies solely on "Pass/Fail" binary checks, you aren't testing your AI agents, you're gambling with them. To maintain transparency and quality, Product Owners and Developers must evolve their DoD to account for "drift," "bias," and "hallucination."
Here is a 4-point governance framework to modernize your Definition of Done for the Agentic Era.
This article is adapted from the AI Agile Leadership Toolkit. For more deep dives into Agentic AI governance, visit the original post:
Definition of Done for AI Agents
1. The "Golden Set" Accuracy Check
In traditional Scrum, we ask: "Does the feature meet the Acceptance Criteria?"
For an AI agent, we must ask: "Does the agent meet the Semantic Similarity Threshold?"
You cannot manually test an AI agent before every release. Instead, you need a Golden Dataset, a curated list of 50–100 distinct inputs (questions) with verified, "perfect" human-written outputs (answers).
Update your DoD:
Criterion: The agent must be tested against the Golden Dataset in the CI/CD pipeline.
Threshold: It must achieve a semantic similarity score (using metrics like ROUGE or Cosine Similarity) of >90% against the verified answers.
2. The PII Redaction Guardrail
AI agents are often targets for "prompt injection" attacks designed to leak training data. If a user asks your support bot for "previous transaction logs," will it comply?
Security is no longer just a non-functional requirement; it is a core quality standard.
Update your DoD:
Criterion: Input/Output guardrails (such as Microsoft Presidio or custom regex filters) are active and verified.
Test: Attempt to feed the agent fake Personally Identifiable Information (PII) like a credit card number. The system must redact it to [REDACTED] before processing or logging.
3. The "Infinite Loop" Circuit Breaker
Unlike a human developer, an autonomous agent doesn't get tired. If it gets stuck in a logic loop, trying to fix a bug, failing, and trying again, it can burn through thousands of dollars in API tokens in minutes.
Update your DoD:
Criterion: A "Circuit Breaker" is configured at the infrastructure level.
Limit: Hard caps are set (e.g., "Max 5 steps per task" or "Max $2.00 spend per execution") to prevent runaway agent costs.
4. The Human Fallback Protocol
Trust is fragile. If an agent encounters a query it cannot answer with high confidence, it must not "guess." It must know when to quit.
Update your DoD:
Criterion: A Fallback Logic test is passed.
Test: When the agent's confidence score drops below a set threshold (e.g., 70%), it must gracefully route the user to a human support ticket or provide a safe, pre-canned response.
From "Bug Hunting" to "Drift Detection"
In the past, Quality Assurance was about finding bugs. In the AI era, it is about detecting Drift. An agent that is "Done" today might not be "Done" next Sprint if the underlying model changes or user behavior shifts.
By embedding these checks into your Definition of Done, you move your team from "hoping it works" to empirically proving it delivers value.
Join the Conversation in India - Are you leading an Agile team through the transition to AI?
These topics will be center stage at Agile Leadership Day India 2026 on February 28, 2026, in Noida. Join India’s top Agile minds as we explore "The New Agile", orchestrating ecosystems of human creativity and agentic speed.
Visit the website - ALDI 2026