Project Proposal Writing Guide
Overview
Section titled “Overview”The capstone project proposal is the primary deliverable for the Week 8 (2026-04-21) presentation, which replaces the midterm exam. This guide provides writing guidelines and a template to ensure consistency and specificity across proposals.
Submission location: capstone/projects/[student-id]/proposal.md (via GitHub PR)
Deadline: 2026-04-20 23:59 (the day before Week 8 class)
Length: 4–6 pages (about 2,000–3,000 words)
Presentation time: 15 minutes talk + 5 minutes Q&A
Grading (Midterm Project, 20%)
Section titled “Grading (Midterm Project, 20%)”| Criterion | Points | Description |
|---|---|---|
| Clarity of problem definition | 4 | Why this problem, why an agentic approach |
| Specificity of system design | 6 | Agent roles, artifacts, pipeline structure |
| Application of course techniques | 4 | Explicit links to Weeks 1–7 content |
| Feasibility | 3 | Achievable within Weeks 13–16 |
| Presentation quality | 3 | Clear delivery, Q&A responsiveness |
Writing Principles
Section titled “Writing Principles”- Specific > general: “Use an LLM to improve code” ❌ → “Use GPT-5.1 Sonnet to analyze pytest failure logs and generate fix patches” ✓
- Numeric success criteria: “Works well” ❌ → “Test coverage ≥ 80%, average loop count ≤ 5” ✓
- Explicitly map course techniques: Name the technique and the week (e.g., “Week 5 Context Rot prevention”, “Week 6 CLAUDE.md tuning”)
- Be honest about risks: Don’t hide weak points — state them with mitigation strategies
- At least one diagram: Visualize the agent pipeline or data flow
Proposal Template
Section titled “Proposal Template”Copy this template to capstone/projects/[student-id]/proposal.md and fill it in.
---title: "[Project Title]"student_id: "2023xxxx"student_name: "Hong Gildong"submitted: "2026-04-20"---
# [Project Title]
**One-line summary**: (What problem does your agent system solve, in one sentence?)
**Student ID / Name**: 2023xxxx / Hong Gildong**GitHub Repository**: https://github.com/...
---
## 1. Problem Definition
### 1.1 Current State(Describe the current inefficiency — manual work, repetitive tasks)
### 1.2 Why an Agentic Approach?(Argue why a simple script or a single LLM call is not enough.Reference Week 1 HITL/HOTL and Week 4 loop paradigm.)
### 1.3 Target User / Usage Context(Who uses this system, when, and how?)
---
## 2. Proposed System Design
### 2.1 Agent Roster
| Agent | Role | Input Artifact | Output Artifact | Model ||-------|------|----------------|-----------------|-------|| Planner | Requirement parsing | user prompt | spec.md | Opus || Coder | Implementation | spec.md, code | diff, PR | Sonnet || QA | Verification | PR, tests | review.md | Sonnet |
### 2.2 Pipeline Architecture
(Show the pipeline as a diagram or ASCII art)User Input → Planner → Coder (Ralph Loop) → QA Gate → Human Approval → Deploy
### 2.3 MCP Tools / External Integrations
- GitHub MCP — PR creation/review- Filesystem MCP — local file edits- (add more)
### 2.4 State Tracking / Handoffs
(Describe the files/JSON structures used for agent-to-agent handoff — see Weeks 5/7)
---
## 3. Tech Stack
| Category | Choice | Rationale ||----------|--------|-----------|| LLM | Claude Opus 4.6 (Planner), Sonnet 4.6 (Coder) | Cost/quality balance (Week 5) || Framework | Claude Code + Custom Agents | .claude/agents/ directory || Language | Python 3.12 | Course standard || Testing | pytest | Easy CI integration || Deployment | GitHub Actions | Free and simple |
---
## 4. Course Technique Mapping
Name the techniques from each week you will **actually apply**. Not "I've heard of it" — "I am using it this way in this project."
| Week | Technique | How It Applies ||------|-----------|----------------|| Week 1 | HOTL governance | Human approval gate at deploy stage || Week 3 | MCP servers | Wrap GitHub API calls as an MCP server || Week 4 | Ralph Loop | Coder agent's test-fail-retry loop || Week 5 | Context Rot prevention | fix_plan.md + claude-progress.txt state files || Week 6 | CLAUDE.md tuning | Project-specific constraints (e.g., "never hardcode secrets") || Week 7 | Gated pipeline | 3-retry limit at QA failure, then human escalation |
---
## 5. Development Schedule
| Week | Milestone | Deliverable ||------|-----------|-------------|| Week 13 | Planner + Coder skeleton | design.md, initial code || Week 14 | Ralph Loop integration, QA agent | Working pipeline demo || Week 15 | System integration, E2E testing | report.md, links.md (slides URL) || Week 16 | Final presentation, demo | links.md (demo video URL), final submission |
---
## 6. Success Criteria
| Metric | Target | Measurement ||--------|--------|-------------|| Functional accuracy | ≥ 80% | Test case pass rate || Average loop count | ≤ 5 | Log analysis || Token cost per task | ≤ $0.50 | API billing logs || E2E response time | ≤ 2 min | Benchmark |
---
## 7. Risks and Mitigations
| Risk | Severity | Mitigation ||------|----------|-----------|| LLM hallucinates non-existent API calls | High | Enforce tests at QA gate (Week 7) || Token cost blow-up | Medium | Model tier routing (Haiku explore, Sonnet implement) || External API downtime | Low | Prepare mock fallback path |
---
## 8. References
- (Week links, papers, blog posts, etc.)Writing Tips
Section titled “Writing Tips”Common Mistakes (avoid these)
Section titled “Common Mistakes (avoid these)”-
X “A system that automatically generates code with AI” — too abstract
-
O “An agent that takes pytest failure logs as input and produces fix commits” — concrete I/O
-
X “Uses Claude”
-
O “Planner uses Opus 4.6 (
--effort high), Coder uses Sonnet 4.6 (--effort medium)” -
X “Will produce good results”
-
O “Test coverage ≥ 80%, converges in ≤ 1.5 fixes on average”
It Must Be an Agentic System
Section titled “It Must Be an Agentic System”Your project must have at least 3 of the following to qualify as a capstone:
- Agent iterates in a loop (Ralph Loop)
- Multi-stage pipeline (Planner → Coder → QA, etc.)
- Tool use (file system, shell, external APIs)
- Autonomous decisions (no human intervention at every step)
- State tracking files for context management
- Validation gates (tests, QA, human approval)
Presentation Structure (15 minutes)
Section titled “Presentation Structure (15 minutes)”| Time | Section |
|---|---|
| 2 min | Problem definition (§1) |
| 5 min | System design (§2) — diagram-centric |
| 3 min | Course technique mapping (§4) — why these weeks matter |
| 2 min | Schedule and success criteria (§5–6) |
| 3 min | Risks and mitigations (§7) |
Q. I haven’t picked a topic yet. A. See Week 13 project ideas. Five example topics are listed there.
Q. Can I extend an existing open-source tool (e.g., sdlc-toolkit)? A. Yes, but you must clearly describe what you added or changed. Pure reuse does not count.
Q. Can I use a local model (Ollama)? A. Yes. This connects with Weeks 10–11 on open-source model deployment.
Q. Should my GitHub repo be public or private? A. Public is recommended (easier for peer evaluation). If private, invite the instructor and TA as collaborators.