Show Notes
I spent a week and a lot of money trying every AI coding assistant, then boiled it down to what actually moves the needle. The takeaway: pick tools by where you are in your workflow, and don’t let AI replace your core skills.
Key takeaways
- AI tools are multipliers, not replacements. They fit different parts of the software delivery cycle.
- If you’re learning, experiment with tools to feel the surface, but for production SAS, you’ll eventually need a lean, coherent flow.
- Favor a minimal, effective setup: Cursor (for Q&A and exploration) and Warp; Taskmaster is optional if you want to build the core skill faster.
- Writing prompts well is the real skill. Your speed and correctness come from prompt craft and understanding the process, not just the tool.
- The trend is toward a one-stop shop in the long run, with ideation and QA becoming the differentiators.
Tool alignment with the software lifecycle
- Ideation and PRD
- Use AI to brainstorm problems, shape requirements, and draft PRDs or one-pagers.
- Architecture and implementation
- Tools like Taskmaster can help bridge PRD to concrete implementation and maintain context across steps.
- QA and testing
- QA remains a critical skill; AI should augment you, not replace rigorous testing and validation.
- Deployment and maintenance
- Automation and tooling support scale, but human oversight is still key for correctness and product fit.
Recommended workflow
- Define the problem and create a PRD/one-pager (don’t skip this step).
- Draft the PRD/FAQ and supporting docs (six-pager, PR FAQ) to set guardrails.
- Use Cursor for questions and rapid validation of ideas, staying within your existing stack (TypeScript primarily; Python for agents when needed).
- Use Warp for quick code generation and exploration, but don’t rely on it to learn fundamentals.
- Iterate: test, refine requirements, and QA thoroughly.
Tips:
- Focus on prompt-writing as your core lever. The actual coding speed comes from how you prompt versus which tool you use.
- If you’re already competent, you can layer tools to accelerate, but guard against over-reliance (muscle growth matters).
Skill-building vs shortcuts
- Shortcuts can accelerate you, but they can also atrophy core skills if you lean on them too early.
- Cursor is your “new raw-dogging” approach: ask smart questions, stay aligned with your TypeScript perspective, and watch where you’re learning.
- Regular practice with prompts, problem framing, and QA will keep your skills sharp even as AI handles repetitive tasks.
End-state and mindset
- The endgame is moving toward a one-stop tool with strong ideation and QA workflows.
- Testing will be paramount: you’ll need solid guardrails (PRDs, six-pagers, FAQs) to ensure outputs meet real needs.
- Adoption is inevitable; the question is how you structure your own workflow to maximize learning and output.
Community and next steps
- Consider joining the group for AI, product, and code integration; weekly workshops and a collaborative environment help you level up faster.
- The group currently offers half-off access and a focus on practical applications across product, marketing, and code.
Actionable takeaways
- Pick tools based on your current stage:
- Early learning: experiment with Cursor + Warp to gauge what’s possible.
- Building production SAS: define a clear PRD/FAQ, then use tools to support execution, not replace it.
- Invest time in prompt engineering. It’s the most scalable skill you’ll develop.
- Create the project scaffolding early: PRD, six-pager, PR FAQ, and clear acceptance criteria before heavy coding.
- Don’t overlook QA. Make it a core part of your process from the start.