Topic: Appendix A. Bridges to the First Volume
Difficulty level: Medium
Estimated study time: 3–5 hours (including reviewing the relevant parts of the first volume)
Prerequisites: Familiarity with the basics of SDD (Specification-Driven Development) from the first volume
Understanding of the artifact structure: mission.md, tech-stack.md, roadmap.md
Basic experience with the requirements.md, plan.md, validation.md formats
An understanding of the AgentClinic study project and its domain model
Learning objectives: Accurately identify which chapters of the first volume are mandatory prerequisites for reading the second volume, and assess your own knowledge gaps.
Explain the differences between SDD dialects (author's, Spec Kit, Kiro) and perform a mental transfer of artifacts between them.
Map the AgentClinic study components from the first volume to production scenarios of the second volume using the domain map.
Describe what new layers and concepts the second volume adds on top of the foundation of the first volume.
Build a personal minimum reading path for the second volume based on the bridges table and your own level of preparation.
Overview: Appendix A serves as the central navigation hub between the first (theoretical-educational) and second (applied, production-oriented) volumes of the course. It brings together all the "bridges": the list of mandatory knowledge from the first volume without which the second volume cannot be read; the correspondence between SDD dialects (Spec Kit, Kiro, author's); a domain map connecting the AgentClinic study code with specific production scenarios; as well as an overview of the new layers that the second volume builds on top of the base process. Without mastering this appendix, the reader risks encountering an accumulation of unfamiliar terms in subsequent chapters.
Key concepts: Bridges: Connecting tables and explanations that turn the abstract production scenario of the second volume into a direct continuation of the study project of the first volume. Bridges ensure continuity of artifacts, terminology, and examples.
Minimum prerequisites: A set of concepts and skills from the first volume without which meaningful reading of the second volume is impossible. Includes: the project constitution structure, the feature specification format, merge gate criteria (EARS, Given/When/Then), replanning, legacy support, agent replaceability, team review, Qwen Code hooks, SDD anti-patterns, and the practical assessment.
SDD dialects: Three variants of specification formatting: the textbook's author's dialect (requirements.md, plan.md, validation.md), GitHub Spec Kit, and AWS Kiro. The second volume uses the author's dialect, but the ideas of the chapters transfer between dialects without loss of meaning through mental renaming of artifacts.
AgentClinic domain map: A correspondence table between the study code of the first volume (Hono routes, SQLite migrations, feedback forms) and the derived production scenarios of the second volume (node_not_ready, appointment_latency, high_memory_usage, rate_limit_breach, etc.). Allows quick context recall when reading any chapter.
Production layers of the second volume: New conceptual layers added by the second volume on top of the foundation of the first volume: the AgentClinic-production laboratory framework, recovery of specifications from legacy, controlled defects, production constitution, adversarial validation (LLM duel), mutation testing of specifications, shadow specifications, Specification CI, file arbitration, tiered budgets, anti-Goodhart metrics, production API integration, production anti-patterns.
Main case of the assessment path: For the assessment path, it is recommended to use high_memory_usage (peak SQLite reads after deploy) as the main case. The other production entities help understand the local runnable examples and do not require a separate evidence package.
Practice exercises: Name: Self-audit of prerequisites
Problem: Using the table "Minimum without which the second volume cannot be read," create a personal checklist. For each row, mark: (a) I know it confidently, (b) I vaguely remember, (c) I am not familiar with it. Calculate the proportion of items in each category.
Solution: 1. Open the prerequisites table from Appendix A. 2. Create three columns: "Confident," "Vague," "Not familiar." 3. For each of the 10+ items, determine your level. 4. If the proportion of "Not familiar" exceeds 30% — return to the relevant parts of the first volume (links are in the right column). 5. For "Vague" items — re-read the brief summaries of the relevant chapters.
Complexity: beginner
Name: Mental transfer of artifacts between SDD dialects
Problem: Given: a team works in GitHub Spec Kit. In the second volume, there is a chapter describing work with requirements.md and validation.md. Write a mental renaming map of artifacts for the transition from the author's dialect to Spec Kit.
Solution: Artifact correspondence: requirements.md → /speckit.specify; plan.md → /speckit.plan + /speckit.tasks; validation.md → /speckit.analyze + checklists. Algorithm: when reading a chapter of the second volume, mentally substitute Spec Kit commands for the author's file names. The ideas of the chapters are not tied rigidly to the format and transfer without loss of meaning.
Complexity: intermediate
Name: Mapping production symptoms to study code
Problem: While reading the second part of the course, you encounter the production symptom rate_limit_breach. Using the AgentClinic domain map, determine: (1) which study component of the first volume is the source of this scenario, (2) which part of the domain it affects, (3) why this symptom occurs specifically in the context of the feedback form.
Solution: 1. According to the domain map: rate_limit_breach → "Feedback form (part 12)." 2. Affects the AgentClinic feedback/reviews domain. 3. The feedback form accepts POST requests; during streaming of identical requests, the rate limiter triggers, which simulates a real attack or load testing. This shows how a study component transitions into a production scenario of protection against abuse.
Complexity: intermediate
Name: Building a personal minimum path
Problem: Based on the table "What the second volume added on top" and the results of the self-audit from exercise 1, build a reading order for the chapters of the second volume. Start with Part 0 (laboratory framework), then distribute the remaining parts by priority, considering your gaps.
Solution: 1. Be sure to start with Part 0 — it transitions AgentClinic to the production model and fixes the minimum path. 2. If you have gaps in understanding legacy support — start with Part 1 (recovery of specifications). 3. If you have gaps in validation — prioritize Part 4 (LLM duel) and Part 5 (mutation testing). 4. If you are interested in CI/CD integration — Parts 7 and 11. 5. Finish with Part 13 (production assessment). Path format: a list of parts with labels "mandatory," "recommended," "optional."
Complexity: advanced
Case studies: Name: Migrating a team from Spec Kit to the second volume's author's dialect
Scenario: A development team is already using GitHub Spec Kit in their daily work and decided to take the applied volume of the course to improve production processes. The second volume is written in the author's SDD dialect.
Challenge: The risk of misunderstanding and confusion with artifacts: the team is used to the commands /speckit.specify, /speckit.plan, and /speckit.analyze, while the course uses requirements.md, plan.md, and validation.md. Without proper mental transfer, the educational material may seem inapplicable to real workflows.
Solution: Using Appendix A to build a mental artifact correspondence map. The team created a cheat sheet: requirements.md → /speckit.specify; plan.md → /speckit.plan + /speckit.tasks; validation.md → /speckit.analyze + checklists. While reading each chapter of the second part, the team kept parallel notes on how the concept is expressed in their real Spec Kit process.
Result: The team successfully completed all 13 parts of the applied volume without loss of understanding. Moreover, they discovered that some ideas (for example, adversarial validation and shadow specifications) integrate organically into their Spec Kit process as additional steps after /speckit.analyze.
Lessons learned: SDD dialects are interchangeable — ideas matter more than file format.
Creating the artifact correspondence map in advance saves time when reading the course.
The practical concepts of the second volume (duel, mutation testing, Specification CI) are applicable in any dialect.
Related concepts: SDD dialects
Mental transfer of artifacts
Spec Kit
Kiro
Name: Diagnosing high_memory_usage based on the AgentClinic study code
Scenario: A student is taking the assessment path of the second volume and working with the main case high_memory_usage — a peak in SQLite reads after deploy in the AgentClinic study project.
Challenge: It is necessary to connect an abstract production symptom with concrete study code (SQLite + review migrations from part 12 of the first volume) and apply the SDD cycle for diagnosis: from symptom detection through recovery/refinement of the specification to validation of the fix.
Solution: 1. According to the domain map from Appendix A: high_memory_usage → "SQLite + review migrations (part 12)." 2. The student re-read part 12 of the first volume to restore context: how migrations and review reads are organized. 3. In the second volume (Part 2 — diagnosis of specification defects), the student analyzed how a defect in the migration specification can lead to suboptimal SQL queries. 4. Using the concepts from Part 5 (mutation testing of specifications) — checked whether the specification catches the mass-read scenario. 5. Formed an evidence package with merge gate criteria.
Result: The student successfully completed the assessment path, demonstrating that the study code of the first volume is a sufficient basis for production thinking. The evidence package included: an updated specification taking into account the high-load scenario, mutation tests confirming the completeness of the specification, and metrics before/after optimization.
Lessons learned: The domain map from Appendix A is critically important for quick context switching between volumes.
The main case high_memory_usage is well-suited for the assessment, as it touches the specification, the code, and the metrics.
The need to return to part 12 of the first volume is a normal part of the process, not a sign of a knowledge gap.
Related concepts: AgentClinic domain map
Diagnosis of specification defects
Mutation testing of specifications
Evidence package
Study tips: Start with Appendix A before reading any chapters of the second volume — it sets the context and prevents frustration from unfamiliar terms.
Be sure to work through the table "Minimum without which the second volume cannot be read" as a checklist — return to unfamiliar parts of the first volume before continuing.
Maintain a parallel glossary: when encountering production entities of the second volume, write down which study component they correspond to according to the domain map.
If your team uses Spec Kit or Kiro — create a physical cheat sheet of artifact correspondence and keep it handy when reading.
For the assessment path, focus on high_memory_usage as the main case — this will save time and provide sufficient depth.
Part 0 (AgentClinic-production Laboratory) is a mandatory entry point; it determines which artifacts are filled out manually, which examples are run locally, and which belong to the full implementation track.
When reading anti-patterns (Part 12 of the second volume), pay attention to the reference blocks to the first volume in the chapter footers.
Additional resources: Part 0. AgentClinic-production Laboratory: Entry point to the second volume: transitions the base AgentClinic to the study production model.
Part 6 of the first volume — creating the constitution: Introduction to the mission.md, tech-stack.md, roadmap.md structure.
Part 7 of the first volume — feature specification: requirements.md, plan.md, validation.md formats.
Part 9 of the first volume — feature verification: Merge gate criteria, EARS, Given/When/Then.
Part 20 of the first volume — SDD anti-patterns: Basic anti-patterns that are expanded in Part 12 of the second volume.
Appendix A of the first volume — SDD dialects: Detailed comparison of Spec Kit, Kiro, and the author's dialect with correspondence tables.
Appendix B of the first volume — AgentClinic domain: Full description of entities: patient agents, ailments, therapies, appointments, reviews.
Summary: Appendix A is a navigation bridge between the two volumes of the course. Its key functions are: (1) define mandatory prerequisites from the first volume through a table of 10+ concepts; (2) ensure portability between SDD dialects through mental renaming of artifacts; (3) connect each production symptom of the second volume with a specific study component of the first volume through the AgentClinic domain map; (4) provide an overview of the new production layers added by the second volume. For effective study: start with Part 0, conduct a self-audit of prerequisites, use high_memory_usage as the main assessment case, and always refer to the domain map when encountering unfamiliar production entities.