Show Notes
Parker breaks down learning to build AI agents, shares a concrete plan for an “agent server” you’ll be able to use in 2025, and riffs on the latest AI news. Short, practical, and straight to the point.
Q&A Highlights
- Learning agents as a teen: start with a real problem you want to solve. Use a problem-first approach, then pick tools to ship a small solution.
- Create a learning automations plan (e.g., a scheduled learning curriculum) and document it.
- Use the fisherman prompt concept to split topics into bite-sized lessons.
- Favor one primary model provider (Google/Vertex-like path) and a no-code tool to iterate.
- Build a simple automation first (lead enrichment from email helps you learn end-to-end) and publish what you build.
- Leverage “code + media” as high-leverage activities; document your progress to grow a following.
- Tools & learning path: focus on a few core players (e.g., Google OpenAI/Anthropic options; Gum Loop as a no-code workflow aid); keep yourself to a manageable stack to learn deeply.
- Recording setup for daily content: use OBS Studio with easily switchable scenes; aim for quick on-camera production and plan for chapter markers and future AI-assisted UI elements (e.g., a progress bar tied to AI-generated chapters).
- Levels of AI tooling:
- Level 1: web/app prompt interfaces (e.g., basic Gemini-like apps)
- Level 2: “AI Studio” style playgrounds with more control
- Level 3: cloud-provider level (Vertex AI, Azure, etc.)
- Vertex AI is Parker’s preferred endgame for heavy lifting; plan to cover Vertex in a dedicated video.
- Automations that actually help you learn/high-leverage setups:
- Start with a single, meaningful problem (e.g., auto-enrich email leads) and build a two-node workflow rather than sprawling, multi-step monsters.
- Don’t chase flashy “gajillion nodes” videos; focus on practical solutions you’ll use and can document.
- Building high-leverage, reusable tools:
- Get more technical (don’t rely on “Make wizardry” alone).
- Explore templates and self-hosted patterns (Next.js AI chat, self-hosting prompts, etc.).
- Use open-source references like Kaj K hoj (model aggregator) and Flowies for automation ideas.
- YouTube channels: Parker’s daily channel is where the bite-sized, practical updates come from; main channel covers longer-form topics.
- Quick note on the future: everyone and their mom will have an agent server. Parker’s goal is to prototype and document this Stack so others can iterate fast.
The Agent Server (Public Roadmap)
- What Parker is building: a public, pluggable agent server that sits atop a company’s data, apps, and workflows.
- Core tech stack (high level):
- Supabase for database + edge functions
- Kong + reverse proxy for routing
- Storage and vector storage (for embeddings)
- Redis for fast state/queueing
- Open Web UI (dashboard for agents)
- GitHub-based CI/CD to auto-deploy changes
- Real-time components via Elixir (scalable chat/streaming)
- Supabase Studio + Postgres language server for type-safe, reliable code
- Next.js apps + Astro for marketing sites
- Concept: each company will have an “agent team” inside its own box, plus separate apps (CRM, marketing sites, internal tools). The goal is an integrated, automated knowledge/execution layer that powers operations end-to-end.
- What’s next:
- Add dedicated CI/CD pipelines with preview branches
- Expand multi-app orchestration and onboarding for new members
- Improve provisioning for new users so onboarding is seamless
Roadmap & Content Strategy
- The daily content plan: mix live streams, recorded deep-dives, and behind-the-scenes builds.
- Map/product under development: a multi-agent platform with five core tools plus sub-agents and a master agent.
- Notes, Tasks, Health, Chat, Calendars (each with sub-agents)
- Channel model: “Netflix-style” cadence for nerds—prepped content, live Q&A, and documented progress.
- Community angle: Vibe with AI school/community to get feedback, iterate, and co-create the agent server.
AI News & Trends (Key Takeaways)
- Visuals-to-product thesis: ChatGPT-style image generation (up to 40 images per prompt) can seed vertical SaaS ideas (landing pages, assets, etc.). The challenge is turning assets into a shippable product.
- Human-in-the-loop is essential: design flows across sketch -> prototype -> code, with human refining steps to stand out.
- Standout content: in the age of AI content, your unique voice and proof of value are your moat. Stand out by proving you can solve real problems, not just create cool prompts.
- Automation and analytics: mechanical-turk-like concepts will evolve into intelligent, auditable agent-based workflows that handle tasks, root-cause analysis, and KPI monitoring. Expect AI agents to take on more of the "decision + execution" burden.
- Shift toward a unified agent stack: many companies will adopt an internal agent server to coordinate data stores, apps, and workflows—Parker believes this will redefine how teams operate.
Quick Takeaways & Actionable Steps
- Start with a real problem you care about. Build something small that solves it and document the process.
- Use the fisherman prompt pattern to design a 30-minute daily learning sprint.
- Pick a primary model/provider path (e.g., Google Vertex) and a no-code tool to prototype quickly.
- Set up a basic automation you’ll actually use (e.g., email lead enrichment) and iterate.
- Get comfortable with OBS for rapid daily content production; plan for AI-assisted chapter markers and UI tweaks later.
- If you’re technical, study templates and self-host patterns (Next.js AI chat, Supabase edge functions, etc.) to build reusable components.
- Follow the Vibe with AI journey to learn from live builds and community feedback; the “agent server” is the thesis you’ll want to test.
Links
- OBS Studio (recording setup)
- Vertex AI (Google Cloud) - referenced as the preferred advanced path
- Supabase UI Library
- Supabase (back-end stack for real-time apps)
- Next.js AI chat templates
- Flowise AI (open-source visual AI agent builder)
- Khoj AI (open-source self-hosted AI second brain)
If you’re following along, check the video description for links to the community, the tools database, and the upcoming Vertex AI deep-dive.