Current AI tech stack
As a (constantly evolving) AI-native builder, I use Zapier’s AI fluency rubric to measure how I stack up in my AI usage and then use it against to measure how I can level up.
Imagine what Coinbase aims to be: a company with humans centred around intelligence. Think of what role you would occupy in such a future organization, and work towards becoming that person.
My current AI usage stands at:
- Ship prototypes using multi-agent coding (Claude Code for code generation + Codex for code review) with adversarial review
- Using ChatPRD for writing PRDs - but also use Claude Code to optimize prompts that can double as PRDs
- Using Refero for design is an inspiration
- Build design systems using Paper/Figma Make
- Integrate coding agents like Amp and + Factory AI droids into workflows
- Test UI/UX flows using Playwright
- Capture client meetings and user interviews with AI (Granola/Circleback) and auto-extract decisions and action items > email them to the client right after. Once I hit a certain threshold of knowledge, the natural next step would be to build a knowledge base/RAG or maybe even train an LLM so they can provide me with greater context on client relationships going forward.
- Use voice-first workflows (Wispr Flow) for rapid and more effective prompting and drafting texts - this is one product I can not live without
- Research augmentation using deep research tools (GPT Deep Research) for structured insight synthesis
- Run cron jobs for recurring workflows (summaries, syncing, cleanup)
- Generate brand-aligned PowerPoints and Excel models using Claude Code (However, these are never truly client-ready and require a lot of work to polish. I would expect the frontier models to get there in a few more updates!)
- Use Do browser agents to automate repetitive web tasks
- Using Remotion to make videos for new product launches
- Get Claude Code-generated email summary over Google Drive, emails, and past notes before the start of the day
- Automated daily briefings via Claude Skills across Slack, email, calendar, and Drive
- Design structured Claude skills to improve LLM output quality and consistency
Core Claude.MD skills
- Design skill on GitHub
- Coding workflow on GitHub
AI tools I am still learning to use:
- Sauna.AI
- Sub-agents in Claude Code
- Palantir Ontology
- Conductor for multi-agent orchestration
- Devin by Cognition Labs
- Antigravity/Augmented IDE - for now, I am somewhat indifferent to IDEs, especially given that Codex and Claude Code UIs are tolerable for now
- multi-agent orchestration looks like without agent drifting
- Braintrust for agent observability