Direct answer: In Week 19, don't integrate more technology. Your job is to compress the business, frontline, and engineering evidence gathered over the first 18 weeks into a Capstone M0 contract that can be approved, approved with conditions, rejected, or revoked. The contract centers on "which business decision Week 24 will support, which frontline step it will change, and which risks must never happen" — not "I want to build a RAG + MCP project."
What M0 freezes, and what it doesn't
Title "What M0 freezes, and what it doesn't"
What M0 freezes is the problem and risk boundary that the next phase must jointly adhere to:
业务决定 ↕ 核对一线任务、异常与人工兜底 ↕ 约束数据、权限、安全、成本与参与者保护 → 第 20–24 周需要补齐的证据 → 继续 / 缩小 / 停止的条件
It does not freeze the technical implementation. If Week 20 reveals that the data boundary doesn't hold, you can narrow the scope or stop; you cannot rewrite the problem just to preserve an architecture you've already drawn.
First, attach an evidence label to every important statement:
| Label | Meaning | How to write it |
|---|---|---|
| Fact | Has a traceable source, applicable scope, and date | "In 12 anonymized replays, 7 showed a manual lookup step" |
| Inference | Derived from multiple facts, but other explanations may still exist | "Manual lookup is likely the main waiting point" |
| Assumption | A value or behavioral mechanism yet to be verified | "Reducing lookup time may lower average handling time" |
| Unknown | Currently insufficient evidence | "Real task frequency and annual financial value are unknown" |
Statements like "everyone needs this," "it will definitely improve efficiency," or "customers will use it" should be downgraded to assumption or unknown if they have no source.
Look at the finished product first: Beichen Capstone M0
Title "Look at the finished product first: Beichen Capstone M0"
The following company, process, roles, numbers, and approvals are all fixed synthetic course examples.
The decision Week 24 will support
Title "The decision Week 24 will support"
Whether it's worth continuing a restricted "customer service policy confirmation" pilot: ordinary customer service agents review current, authorized policy sources before replying to customers; they escalate when encountering conflicts, outdated content, or no answer; and only after the agent confirms each time can the system create a supervisor review ticket.
This is not a company-wide launch approval, nor "letting AI handle customer service automatically."
Scope and non-goals
| Item | M0 scope |
|---|---|
| Primary role | Ordinary customer service agents in Business Unit A |
| One task | Confirm policy sources before replying |
| One exception | Escalate to the policy owner or supervisor when sources conflict |
| Single write effect | Create a supervisor review ticket after per-instance approval |
| Data boundary | Business Units A/B isolated; ordinary and supervisor roles isolated |
| Non-goals | Auto-replies, bulk writes, autonomous approvals, cross-department rollout, real production deployment |
Knowns, assumptions, and unknowns
Title "Knowns, assumptions, and unknowns"
| Statement | Label | Source or next step |
|---|---|---|
| Lookup and escalation breakpoints exist in fixed replays | Fact (within teaching samples) | Weeks 2–4 synthetic walkthrough records |
| Retrieval and citation can reduce some lookup steps | Assumption | Observe in Weeks 21 and 24 |
| Permission leaks, wrong policies, and unapproved writes are unacceptable | Hard constraint | M0 risk readback |
| Real adoption, task frequency, time saved, and financial value | Unknown | Can only be verified through an authorized pilot |
M0 decision
decision_id: northstar-m0-v1decision: course_simulation_approved_with_conditionsscope: one_role_one_task_one_exception_one_approved_effectconditions: - M1_negative_access_matrix_passes - no_missing_acl_document_enters_candidates - all_external_effects_require_fresh_approvalreopen_if: - role_or_data_scope_changes - frontline_workload_increases_beyond_agreed_boundary - a_forbidden_effect_or_access_leak_occursdoes_not_authorize: - real_customer_data - production_deployment - autonomous_actions
This example passes because value is still labeled as an assumption, real adoption is still unknown, and the course's simulated approval has not been written as organizational authorization.
Step 1: Build evidence lineage, don't copy old documents
Title "Step 1: Build evidence lineage, don't copy old documents"
Create a table for the key artifacts from the first 18 weeks:
| Evidence | Version / date | What it originally supported | Does the current scope still match? | Decision | Limitations or conflicts |
|---|---|---|---|---|---|
| Discovery Brief | v3 / date | Problem and relevant roles | Partial | Revise | New write-operation risk added |
| RAG eval report | v1 / date | Failure classification on a fixed corpus | Yes | Reuse structure | Cannot represent the Capstone's new corpus |
| MCP effect audit | v1 / date | Approval and reconciliation for a single tool | Yes | Reuse controls | Must re-verify integration in Week 22 |
Each item can only have one primary decision:
- Reuse: scope and version still apply;
- Revise: the core can be kept, but roles, data, or risks have changed;
- Retire: conflicts with the new problem or is no longer valid;
- Incomplete: not enough evidence yet.
More old files doesn't mean stronger evidence. If evidence can't answer the current decision, don't force a citation just to make your portfolio feel complete.
Step 2: From the boss's goal to the frontline task
Title "Step 2: From the boss's goal to the frontline task"
Use these five questions to connect the two levels of conversation:
- What decision does the boss ultimately need to make, rather than what features do they hope to see?
- Which task of which frontline role affects this decision?
- What are the normal path, exception path, and human fallback respectively?
- Which step does the system change, and whose judgment must be preserved?
- Which observable outcome would support continuing, and which protective metric or hard risk would require stopping?
One-page problem and risk contract template
Title "One-page problem and risk contract template"
# Capstone M0 问题与风险合同 v1 ## 决定第 24 周,谁要根据哪些证据决定继续、缩小还是停止什么? ## 当前一线任务- 主要角色:- 触发条件:- 正常步骤:- 一个关键异常:- 当前人工兜底与责任人:- 一线明确不愿失去的判断权: ## 范围- 一个任务:- 一个异常:- 一个允许的写效果(若有):- 数据和角色边界:- 非目标: ## 指标与证据状态| 指标或主张 | 基线 | 类型:事实/推断/假设/未知 | 来源 | 第几周验证 || --- | --- | --- | --- | --- | ## 硬风险与停止条件| 风险 | 不可接受结果 | 检测证据 | 负责人 | 触发后的动作 || --- | --- | --- | --- | --- | ## 批准、异议与重开条件分别记录业务、一线、数据/安全和工程角色的结论;不要用一个统一签字代替不同责任。
Step 3: Write metrics as value mechanisms, not promises
Title "Step 3: Write metrics as value mechanisms, not promises"
Every candidate metric answers six things:
- Which decision the metric supports;
- Which roles and tasks it applies to;
- What the numerator, denominator, time window, and source are;
- Whether the current baseline is a fact, simulated, or genuinely unknown;
- What alternative explanations might affect it;
- Which protective metric prevents "optimizing the number while harming the frontline."
For example, "average handling time decreased" cannot stand alone. A more complete mechanism is:
当前查找步骤与等待时间(待真实测量) → 有依据的政策候选减少部分查找 → 一线仍确认或升级 → 观察任务时长与返工同时保护:权限泄漏 = 硬停止;错误政策不得被更快地送达
Without authorized traffic, the baseline remains unknown. Course replays can only validate the calculation method or expose process gaps.
Step 4: Conduct a four-party readback and produce a decision record
Title "Step 4: Conduct a four-party readback and produce a decision record"
Have four responsibility perspectives read back the same M0:
| Perspective | Must confirm | Cannot confirm on behalf of others |
|---|---|---|
| Business owner | The decision to make, value mechanism, budget risk, stop conditions | Actual frontline burden and data authorization |
| Frontline role | Current tasks, exceptions, human fallback, preserved judgment | Organizational budget and security exceptions |
| Data/security owner | Data scope, permissions, retention, hard risks | Business value and frontline usability |
| Engineering owner | Feasible boundaries, controls pending verification, rollback and ops gaps | Customer acceptance and business priorities |
When real roles are unreachable, role-playing is allowed, but every item must be marked as simulated. Recording dissenting opinions matters more than pursuing a table where "everything passes."
Five-day schedule
| Learning Day | Suggested Time | Action for the Day | Required Outcome Before Leaving |
|---|---|---|---|
| Day 1 | 1–2 hours | Inventory upstream versions, capabilities, and limitations | Evidence lineage and a first draft of reuse/revise/retire decisions |
| Day 2 | 2 hours | Fix one decision, one role, one task, and one exception | A one-page contract of questions and risks |
| Day 3 | 1–2 hours | Write the value mechanism, baseline state, guard metrics, and unknowns | Metric cards and stop conditions |
| Day 4 | 2 hours | Map the evidence gaps for weeks 20–24 | Every risk has a validation week and an owner |
| Day 5 | 2 hours | Complete the four-party read-back and the M0 record | Approve, approve with conditions, object, or stop decision |
This Week's Acceptance
Title "This Week's Acceptance"
- The contract centers on business decisions and frontline tasks, not technical names;
- the normal path, one key exception, the human fallback, and the responsible person are clear;
- every major claim carries a fact, inference, assumption, or unknown label;
- data, permissions, security, cost, and participant protection enter the hard constraints;
- the judgment authority retained by the frontline and any new burden are explicitly recorded;
- every piece of legacy evidence is judged as reuse, revise, retire, or incomplete;
- M0 explicitly lists the evidence not yet completed for weeks 20–24;
- business, frontline, data/security, and engineering opinions are recorded separately;
- the decision includes scope of application, conditions, objections, review date, and reopening conditions;
- without real authorization, write only "course-simulated approval";
- M0 does not authorize real data, production deployment, or autonomous write operations.
Common Failures and Fixes
Title "Common Failures and Fixes"
| Failure | Diagnostic Signal | Fix Action |
|---|---|---|
| The goal is "complete RAG + MCP" | Nobody knows what decision must be made in week 24 | Rewrite it as a role, a task, and a continue/stop decision |
| The boss's wish becomes a requirement directly | No evidence for the frontline process or exceptions | Go back to the task walkthrough and mark contradictions and unknowns |
| Frontline complaints become features directly | No frequency, alternatives, or responsibility boundary | Add evidence or narrow it into a hypothesis to be validated |
| All old files are reused directly | Versions, roles, or scopes conflict with each other | Make a reuse/revise/retire judgment item by item |
| Filling in unknown numbers for a sense of completeness | Metrics have no source or denominator | Restore "unknown" and designate an authorized path to obtain evidence |
| Simulated approval is written as customer approval | No real empowered role | Correct the label and withdraw extrapolated conclusions |
Independent Migration: Supply Chain Exception M0
Title "Independent Migration: Supply Chain Exception M0"
Replace the Beichen customer service case with "supply chain exception confirmation," but keep only:
- one decision the boss must make, e.g., whether to continue a restricted exception-handling pilot;
- one frontline role, e.g., procurement operations;
- one task, e.g., verifying the basis for an exception and forming a recommendation;
- one exception, e.g., conflicting supplier status;
- one approval-per-step effect, e.g., submitting an expedited review request;
- one hard stop condition, e.g., cross-supplier data leakage or duplicate procurement effects.
Write M0 first, then judge whether RAG, MCP, or multi-tenancy is really needed. Technology is not the default answer.
Explaining the Same Evidence to Three Audiences
Title "Explaining the Same Evidence to Three Audiences"
- Boss version: What decision must be made in week 24, how value could be generated, and what the current facts, assumptions, unknowns, and stop signals are.
- Frontline version: Which step changes, which judgments are retained, who takes over when an exception occurs, and how to refuse, exit, or roll back.
- Engineering version: Which versions are reused, what is retired, what the hard boundaries are, and in which week each remaining risk is validated.
Next Steps
Only proceed to Week 20: Connecting Capstone Data and Access Boundaries once M0 has received the corresponding authorization or is explicitly marked as course-simulated approval. If the role, data scope, or risk changes, version it first and re-read M0.
Sources and Fact Boundaries
Title "Sources and Fact Boundaries"
- GOV.UK Service Manual — Understand users and their needs: A reference for starting research from user tasks and actual needs rather than preset solutions.
- NIST AI RMF Playbook: A reference framework for governing, mapping, measuring, and managing AI risks.
- Palantir — Forward Deployed Software Engineer: A reference for customer collaboration, problem decomposition, and end-to-end delivery responsibilities; the job page may change.
Verification date: 2026-08-25. M0, evidence labels, week numbers, and acceptance gates are the teaching structure of this course, not an industry-wide standard. The Beichen case, replays, metrics, and decisions are all synthetic material; without real organizational authorization, they must not be extrapolated into customer needs, adoption, financial value, or production approval.