Show Notes
Parker shares a pragmatic path from chasing unicorns to building $20K/mo in AI services, plus a clear content and product strategy to push toward $100K/mo. Two growth lanes (Cursor-focused AI tools and broad AI education) power a content engine that feeds paid courses and a community.
Strategy snapshot
- Pivot point: go all-in on AI services after a stint chasing VC success; hit $20K/mo within the pivot week.
- Revenue path: build goodwill with free content first, then monetize with paid courses and services.
- Two-pronged approach: Cursor-centric tooling and broad, mass-audience AI education. Both feed a single channel and funnel to a paid school/community.
Niches and positioning
- Cursor niche: focus on the best-in-class coding/AI automation setup, multi-agent platforms, and practical builds.
- Mass AI education: teach fundamentals, prompting mastery, and practical workflows for non-experts who want results fast.
- Strategy balance: publish broadly to attract attention, then convert that audience into paid courses and a community.
Content strategy and formats
- Core ideas:
- 10x prompts and meta-prompts: push for higher-quality outputs by giving more context and a strategic prompt frame.
- Prompt scaffolding: level-based prompts (zero, one, two, etc.) and meta prompts to unlock better results.
- Show-how demonstrations: practical setups (cursor + mCP, browser debugging, etc.) over theory.
- Content cadence:
- Daily updates on AI journey.
- Long-form masterclasses and tutorials on key topics (to be hosted in the paid school).
- Listicles and tool-dove content to surface new tools and use cases.
Tools and tech stack
- Core tools:
- mCP (Model Context Protocol) by Claude
- Claude family for agents and tool calls
- Cursor (AI-enabled coding/automation assistant)
- Superbase as a backend toolset
- Warp and Whisper for content pipeline (transcriptions)
- YT DLP for video download
- Zed (Rust-based IDE) for fast tooling
- Webflow, Figma, Squarespace, WordPress as website options (with quality vs ease-of-use tradeoffs)
- Workflow enablers:
- Make.com for no-code automations
- YouTube-to-blog post pipeline (transcriptions → blog posts)
- Blog posts as evergreen content to reinforce paid courses
The content pipeline (YouTube to paid content)
- Core flow:
- Record daily AI journey videos
- Transcribe using Whisper (via Warp)
- Turn transcripts into blog posts with structured prompts
- Use blog posts to funnel to paid courses and community
- Example prompts/tools:
- YouTube to blog post prompts (comprehensive prompts tailored to video type)
- Output verification matrix (keeps content quality in check)
- Airtable as the content planning hub
- Content ideas to repurpose:
- Calorie tracker in 10 minutes
- Build a WordPress clone in 10 minutes
- 10x prompting and meta-prompt deep-dives
- “What tools I wish I knew” listicles
Product and monetization plan
- Paid products:
- Courses and masterclasses (longer than 30 minutes)
- A paid school/community with ongoing updates
- Traffic strategy:
- Channel content drives traffic to the school
- Two niches feed the same hub for scalable monetization
- Evergreen content:
- Glossy, tool-agnostic concepts (product analytics, CRO, and prompt engineering)
- Emphasis on fundamentals so tools’ noise doesn’t overwhelm learning
Browser tools and debugging with mCP
- End-to-end flow:
- Set up mCP browser tools extension (Chrome) to expose browser actions to the agent
- Run the browser tools server and connect it to Cursor via mCP
- Use the integrated debugging to capture console errors, network logs, and screenshots
- Practical use:
- Debug client-side issues without flipping between dev tools and chat
- Create a debu commands workflow to automate debugging steps
- Visual example:
- The extension acts as a logger and screenshotter; you can prompt the agent to read logs, take screenshots, and report back
Quick experiments and ideas highlighted
- “YouTube counter” concept: a YouTube channel that comments on popular videos to attract creators and showcase capability
- AI-driven social media agent: autonomous posting and engagement experiments
- Cross-tool bridges: pining the gap between Figma and Cursor to streamline design-to-implementation
- Real-world test ideas: Peter Levels’ flight simulator, a mortgage/ads-based game, etc., to illustrate practical AI productization
Actionable takeaways
- Build two growth lanes: Cursor-focused projects and broad AI education. Let them feed one another.
- Publish freely and often to build goodwill before charging; your audience buys into you, not just your tool.
- Create a tight pipeline: daily video → transcription → blog post → lead into paid courses.
- Master prompting: start with level-based prompts, then move to meta prompts to extract stronger outputs.
- Leverage browser-enabled mCP tools to debug and iterate faster; connect the browser tools to Cursor for end-to-end visibility.
- Document your process in a public way (Airtable, resources page) to lower friction for learners and potential students.