Show Notes
Use your brain: AI is a multiplier, but the real lift comes from planning, disciplined workflows, and building memory around your codebase. Here’s the punchy playbook from today.
Why planning is the biggest lever
- Planning is a real role: product management-style thinking about what you’re building and why.
- It creates a shared understanding so AI can grasp constraints and goals.
- A good plan prevents prompt quality from spiraling into garbage-in, garbage-out.
Ideation to implementation: the framework
- Left to right: ideation (concepts, what we’re building) → implementation (execution, how we build it).
- Use a structured prompt flow and move from discovery to execution with agent mode as you mature.
- Multi-turn prompts require discipline; don’t shortcut thinking or you derail context.
Memory banks and AI docs
- Build memory banks for the entire codebase: AI docs + rules that govern them.
- Example memory banks:
- Core API (FastAPI)
- Client/UI (TanStack)
- Infra (CI/CD, databases, cloud)
- Add file-tree context so AI stays grounded in your structure.
- Rules + research live in these memory banks to keep context tight and scalable.
Prompts, context, and tooling
- Start with asking questions (Ask mode) early; you’ll pivot to agent mode as you clarify.
- Manage context: provide clear constraints and anchor AI to specific docs/rules.
- Don’t rely on AI as your sole idea architect. Garbage-in, garbage-out still applies.
- For straightforward tasks, lightweight tools like Taskmaster can help; for complex features, you need deeper thinking and structure.
Filtering signals and staying sharp
- Vet sources: is the voice a builder or a marketer? Filter accordingly.
- In the community, you’ll hear a lot of noise; focus on developers doing real work and verified progress.
- Find the “teacher of the teachers” by validating what they actually build, not just what they say.
Practical steps you can apply today
- Define the problem and success criteria up front (planning mindset).
- Create AI docs and project-specific rules to ground the model.
- Build memory banks for core domains (API, client, infra) and wire them into your prompts.
- Start with Ask mode; move to Agent mode as your prompts improve.
- Keep your context tight with clear constraints and updates to memory banks as you learn.
- Validate sources before adopting new approaches or tools.
Community, news, and next steps
- The landscape is noisy; curate who you listen to (builder vs marketer) and learn from actual builders.
- The daily cadence will stay focused on practical skills, not just news noise.
- Frameworks and patterns are coming together; expect more structured playbooks and pods in the future.
Links
- Cline (product management insights for AI-driven coding)
- Task Master (useful for straightforward tasks like forms/static pages)
- FastAPI (reference for API-coding workflows)
- Gemini (Google) releases and related AI updates
- OpenAI Codex vs Claude Code (pricing/availability notes)