DAILY ENGLISH LAB AGENT
Epic: Lesson Generation Pipeline Architecture
We are grooming the backlog for the AI Engineer Daily English Lab Agent. The PM wrote a massive epic for the lesson generation pipeline, but it lacks clear user stories and acceptance criteria. We need to break it down into manageable sprint tasks and define exact conditions of satisfaction for the Claude Code CLI integration.
我们正在为 AI 工程师每日英语实验室 Agent 进行需求梳理 (Backlog Grooming)。产品经理为课程生成 Pipeline 写了一个庞大的 Epic，但缺乏清晰的用户故事和验收标准。我们需要将其拆分为可管理的 Sprint 任务，并为 Claude Code CLI 集成定义准确的完成条件。
A large body of work that can be broken down into specific tasks or user stories.
"We need to slice this epic into smaller, deliverable user stories for the upcoming sprint."
An informal explanation of a software feature written from the perspective of the end user.
"The current user story is too vague; it doesn't explain why the user needs the MCP server integration."
Conditions that a software product must satisfy to be accepted by a user or stakeholder.
"Let's update the acceptance criteria to explicitly include handling Claude API rate limits."
The process of refining, estimating, and prioritizing items in the product backlog.
"During backlog grooming, we noticed several user stories were missing technical prerequisites."
Uncontrolled continuous growth in a project's scope after it begins.
"Adding the multi-agent orchestration right now will introduce massive scope creep."
A shared, comprehensive checklist of what it means for work to be complete.
"Our Definition of Done requires a minimum of 80% test coverage and a passed security scan."
A problem or situation that occurs only at an extreme operating parameter.
"The PM missed an edge case in the user story where the LLM context window is completely maxed out."
"This story is too broad. We need to slice it down."
这个故事太宽泛了。我们需要把它拆解。 · Use during grooming to push back on unestimated, massive tasks
"What's the actual business value we are trying to deliver here?"
我们在这里试图交付的实际商业价值是什么？ · Use when a feature request seems purely technical or unnecessary
"Let's nail down the acceptance criteria before we start coding."
在开始编码前，让我们先把验收标准敲定。 · Use to enforce clarity and prevent engineering rework
"I'll spike this ticket to investigate the Claude Code CLI integration."
我将针对这个任务做一个探路(Spike)，以调查 Claude Code CLI 的集成。 · Use when a story lacks technical clarity and needs a time-boxed research task
"This feels like scope creep. Let's push it to the next iteration."
这感觉像是范围蔓延。我们把它推迟到下一个迭代吧。 · Use to defend the current sprint goal and defer new requests
To ensure the AI Engineer Daily English Lab Agent meets user needs, we utilize structured user stories. A well-crafted user story captures the *who*, *what*, and *why* of a requirement. However, stories alone are insufficient for engineering execution; they must be paired with precise acceptance criteria.
When defining the MCP server integration, the epic initially suffered from severe scope creep. By engaging in rigorous backlog grooming, we sliced the epic into discrete, actionable stories. Furthermore, adhering to our rigorous Definition of Done ensures that edge cases—such as LLM context window limits and Claude API rate limit timeouts—are proactively addressed in the testing phase, rather than discovered during production rollouts.
Comprehension Check
1. What must be paired with user stories to ensure proper engineering execution?
2. How did the team resolve the scope creep regarding the MCP server integration?
3. Which of the following is considered an "edge case" mentioned in the text?
The PM wrote a new user story: "As a user, I want the system to generate lessons." Write a Jira comment pushing back on this requirement.
- 1.State that the story is too broad and needs to be sliced.
- 2.Ask for clear acceptance criteria (e.g., prompt templates or context limits).
- 3.Mention the risk of scope creep if it remains undefined.
- 4.Keep it under 80 words.
3 Words from Previous Lessons
上下文窗口
Token limit for an LLM prompt.
级联故障
One failure triggering a chain reaction.
子进程
A process spawned by the main script.
2 Expressions from Previous Lessons
"We are blowing past the context limit with these logs."
"We need to fail fast to prevent resource exhaustion."
When designing an LLM orchestration agent, why might a standard Agile "User Story" (e.g., "As a user, I want...") be insufficient for defining technical requirements? How do you adapt product requirements for AI-native, non-deterministic features?
Answer in English. Use technical vocabulary from this lesson. No word limit.