Vibe Engineering Effect Apps

on YouTube ↗01h 43m

" summary

Claim: giving agents the library source beats better prompts; approach clones the Effect repo and extracts patterns to guide agents. Tools actually used: Bun, Vitest, TypeScript with TSGO, Effect beta and an Effect git subtree. Built a Todo HTTP API with an SQL client, migrations, tests, strict diagnostics, agents.md and OpenAPI docs. The prototype runs, tests pass and the workflow proves the core idea just clone the repo works.

AI-written summary · about

" chapters (19)

1. 0:00Start
2. 0:15Introduction and context setting for the workshop
3. 0:47Interactive audience poll on experience with Effect and AI tooling
4. 3:16Discussing the core philosophy: "Just clone the repo" for AI context
5. 5:59Understanding LLMs vs. the human brain and context window limitations
6. 13:13Project setup: Starting from an empty repository
7. 14:20Initializing the project with Bun, Vitest, and TypeScript
8. 19:18Adding Effect beta and configuring TSGo for the compiler
9. 30:30Configuring strict diagnostics for AI-assisted development
10. 35:20Adding the Effect repository as a git subtree for better agent access
11. 37:07Creating agents.md to establish rules and available commands
12. 41:40Researching Effect patterns for building an HTTP API
13. 43:08Discussing "Spec-Driven Development" and avoiding plan-mode limitations
14. 54:02Drafting the plan for the Todo HTTP API
15. 1:05:07Implementing the SQL client and migration patterns
16. 1:13:42Reviewing API schemas and handling identified code duplication
17. 1:18:14Starting the API server and verifying OpenAPI documentation
18. 1:20:56Cleaning up test suites and enforcing best practices for layers
19. 1:38:08Concluding remarks on workflows, clustering, and future stability in Effect

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