Exploring the components and different levels of “meta prompting” provides a structured methodology for advanced prompt engineering in AI models.

Use FFMPEG to extract video/audio segments, overlay captions, and adjust aspect ratios for optimized social media snippets (TikTok, Instagram, YouTube...Show more

Feed structured documentation into AI models (slash agents) to generate agent cards and plan sub-agents effectively without triggering actual creation...Show more

Design sequential workflows using multiple sub-agents—extraction, analysis, optimization, and distribution—to modularize AI tasks instead of one monol...Show more

Implement a pipeline that extracts raw transcripts from audio or video, processes them for summaries and insights, and identifies shareable segments.

Demonstrate AI workflows step-by-step in public to build trust through transparency and process visibility.

Tom implements an orchestration layer over video LLM calls to coordinate and automate video generation pipelines.

Cameron created a team of sub-agents inspired by HRM research to simulate collaborative AI behaviors and multi-agent interactions.

Tom discusses the structure and application of hierarchical reasoning models in AI to improve layered decision making.

Tom explains that the Orchestrator must declare the queries it will handle and that accepted inputs are defined in the team section.

Cameron reflects on task decomposition techniques and how recognizing pre-existing components can streamline AI workflows.

For new Claude Code projects, clone the repository and run 'init' immediately to prevent context clutter in the main MD file.

Use the 'init' command for existing projects to update the Claude MD file without overwriting previous settings.

Run '/initialize' on launch to create your cloud MD file and set up initial configurations for Claude Code projects.

Leverage MD files to handle Claude's memory and manage conversational context through dedicated context files.

Use built-in documentation to generate sub-agents in Claude Code, streamlining development and onboarding for new modules.

Follow Next.js directory structure conventions, influenced by training data, to maintain consistency and leverage familiar patterns in AI projects.

Develop agents capable of generating and executing scripts autonomously to boost automation and reduce manual intervention.

Embed JSON schema definitions within agent .md files to enforce structured output and validation for AI responses.

Design agent cards that specify system prompts, available tools, and output formats to clearly define AI researcher roles and capabilities.