Show Notes
Cursor AI Just Dropped the Ultimate Big Codebase Playbook — show notes
Cursor AI is moving toward writing big codebases, but the practical playbook is what actually moves projects. Here’s the concise, no-fluff rundown and the actionable takeaways from today.
Quick takeaways
- AI will soon write large swaths of code, but you should double down on the tools you already trust.
- Build around PRDs, Taskmaster, and Cursor for scalable, repeatable changes.
- Don’t chase every trend; optimize with what you know and what works in production.
- If you’re tackling Stripe in Next.js, two solid starters to speed you up: Verscell’s SaaS starter and Midday’s Polar-based project.
Vector databases: scam or solid tool?
- The hype around dedicated vector databases is often overstated for many use cases.
- Real-world cost win: moving from expensive vector-only workflows to PG Vector on Postgres can dramatically cut costs (example discussion cited: from hundreds to tens of dollars per month).
- Key benefit: you can leverage standard SQL features (foreign keys, joins) with vector data, keeping everything in one database.
- Practical note: for higher-dimension embeddings, you’ll trade off some fast indexing (e.g., HNSW) for simpler, slower search, but you can often work around this.
- Takeaway: in many projects, using your existing Postgres/SQL stack with PG Vector is the smarter, cheaper path.
Curated workflow for large codebases with Cursor
- Use Cursor to scale with large codebases by combining planning, exploration, and execution.
- Plan first, then implement: start with a PRD-like plan, define outcomes, and map dependencies.
- Tools and modes:
- Chat: broad exploration and multi-file understanding
- Tab: quick in-file edits (your driver seat)
- Command K: narrow to a single file/scope
- Agent mode: deeper, targeted digging and automation
- Key inputs to maximize Cursor:
- Include project structure and relevant folders for context
- Write domain-specific rules to codify onboarding and contribution norms
- Attach formatting rules via glob patterns (e.g., file naming, casing, language conventions)
- Planning discipline:
- Use a detailed planning prompt to assemble context from past chats, tickets, and docs
- Iterate with ask mode to refine plan before starting implementation
- Transition later to Taskmaster for PRD-to-task translation and concrete steps
- Practical mental model: treat plan creation like shaping a rough block into a sculpture—start broad, then progressively refine with focused prompts.
In-browser IDE tips and practical UX
- You can view and edit code in-browser using a web editor when you hit certain UI cues (period key tip from the community).
- Cursor + Next.js patterns you’ll see in examples:
- Server components, Next headers, and inline document components
- Real-time IDE-like editing within the page (no local clone required)
- Quick tool map:
- Tab: quick infile edits
- Command K: scope to a single file
- Chat: larger, multi-file changes and broader context
A practical workshop pattern to learn faster
- The speaker highlights a reusable workshop approach leveraging SSR, RAG, and web search templates
- Use cases and examples come from real projects (e.g., I vibe with AI workshop) to practice building with Cursor, PRDs, and Taskmaster
- Build a repeatable template you can drop into new big-code projects
Final notes and mindset
- AI isn’t coming; it’s here. Real-world impact includes agents closing real-world deals and changing how teams work.
- Be cautious with sensational claims or scams; verify sources and focus on robust tooling you can rely on.
- If you have questions, drop them in the comments—there’s a Q&A tomorrow.
Links
- Vercel SaaS Starter with Stripe (Stripe integration starter for Next.js)
- Next.js SaaS Starter (official Next.js SaaS template)
- Cursor AI (guide to using Cursor for large codebases)
- pgvector (PostgreSQL vector extension)
- Taskmaster AI (PRD-to-task translation tool)
- Vibe with AI Discord (workshop resources and community)
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