El Sistema de Skills que Cambió Cómo Trabajo con IA (Curso Completo)

Understanding Agents and Architecture in AI

Introduction to the Video

• The speaker introduces a new video focused on agents and an innovative architecture they have developed, claiming it is effective despite being self-invented.

• Emphasizes the continuous evolution of technology and invites viewers interested in leveraging AI for their projects to stay tuned.

Learning Objectives

• The session aims to teach how agents can communicate effectively with users, emphasizing software engineering rather than just coding.

• Introduces the concept of a Markdown file (MD), which serves as a crucial resource for agents to understand project context.

Importance of Agen MD

• Explains that the Agen MD file helps define agent behavior and project requirements, distinguishing it from traditional human-readable files.

• Mentions that agents can utilize skills, hinting at further explanations with visuals later in the discussion.

Project Context and Codebase Interaction

• Describes working within a project where an agent interacts with user requests by querying a codebase for information.

• Highlights potential challenges when an agent must sift through extensive code to fulfill user requests efficiently.

Role of Agen MD in Enhancing Efficiency

• Discusses how Agen MD facilitates communication between the agent and codebase, allowing quicker access to necessary information about project structure and technologies used.

• Stresses that this process improves user experience by enabling faster responses from the agent based on structured data retrieval.

Best Practices for Creating Effective Agen MD

Recommendations for Size and Structure

• Advises keeping Agen MD files concise; larger files may hinder performance due to excessive context processing demands on agents.

• Suggestion that optimal sizes range around 250–500 lines; exceeding this could lead to inefficiencies or errors in agent responses.

Alternative Approaches for Large Codebases

• Proposes creating multiple smaller Agen MD files tailored to specific aspects of a project (e.g., authentication, UI, API), enhancing manageability.

Organizing Codebase by Features

Structuring the Codebase

• The application codebase is organized by features rather than a single monolithic structure, allowing for better management and clarity.

• Each feature has its own directory (e.g., UI, API, authentication), which helps in maintaining separation of concerns within the codebase.

Agent Functionality

• An "agent root" is introduced to facilitate information retrieval across different directories when the user queries from the application's root.

• The agent can provide context-specific responses based on user inquiries about various components like UI or specific technologies.

Skills and Context Management

• Skills are defined as specialized knowledge areas that help reduce the amount of context provided to agents, ensuring they only receive relevant information when needed.

• As more skills are added (e.g., React, Python), it becomes essential to manage how much context an agent receives at any given time to avoid overwhelming it.

Workflow Automation with Skills

• Users can create custom skills for repetitive tasks (e.g., commits, pull requests), streamlining workflows and automating processes that would otherwise require manual intervention.

• These skills encapsulate cultural practices and specific formats used within a team or project, enhancing consistency in operations.

Triggering Agents Automatically

• Agents operate automatically based on triggers set for specific tasks related to different programming languages or actions like commits and pull requests.

• Documentation suggests that skills should be organized within designated folders for automatic recognition by agents during their operation.

Skill Scope Definition

• Each skill will have a defined scope indicating where it applies (e.g., React in API vs. UI), facilitating targeted functionality without unnecessary overlap.

• A structured approach allows for clear identification of which skills can be triggered under certain conditions, improving overall efficiency in task execution.

Subagents Concept

• Subagents function similarly to skills but operate with smaller contexts; they are designed to handle specific tasks without overloading the main agent's processing capacity.

Orchestrating Agents and Subagents in Project Management

Introduction to Orchestrators and Subagents

• The main concept introduced is the transition from calling a primary agent to an "orchestrator," which manages multiple subagents.

• The orchestrator's role is to handle repetitive tasks in parallel, such as editing 500 files simultaneously, by generating subagents that perform these tasks independently.

Functionality of Agents and Subagents

• Each subagent operates within its own context, allowing for independent task execution without interference from others.

• Upon completion of their tasks, subagents return a summary of their work to the orchestrator, maintaining a clean workflow without cluttering the context with unnecessary details.

Architecture and Skills Organization

• By organizing subagents with well-defined skills under the orchestrator, a robust architecture can be established for efficient project management.

• The discussion transitions into practical application within a repository (Prowler), emphasizing how projects are structured for clarity and collaboration.

Open Source Collaboration Guidelines

• The repository includes guidelines on contributing to the project while ensuring contributions align with existing workflows and standards.

• This structure aids new contributors in quickly acclimating to the project environment by providing clear instructions on necessary skills and practices.

Skill Invocation Mechanism

• A critical observation is made regarding skill invocation; even if contributors lack certain skills initially, they can still access necessary information through designated files.

• Contributors must autoinvoke skills when performing actions related to various components (e.g., API calls or UI modifications), ensuring proper functionality throughout development.

Metadata Structure for Skills

• Each skill has associated metadata detailing its purpose, triggers for execution, author information, versioning, and applicable tools available for use by agents.

• This metadata serves as essential documentation that guides users on when and how to utilize specific skills effectively within their projects.

How to Manage Skills in Your Project

Overview of Skill Management

• The speaker discusses controlling the capabilities of a skill, emphasizing that it can be tailored for specific tasks like documentation and repository access.

• An introduction to server actions and components is provided, highlighting how to effectively work with Next.js in more complex scenarios.

Compliance Structure

• The structure of compliance within the project is explained, noting similarities with Next.js and detailing triggers for usage.

• Emphasizes the importance of providing detailed examples when creating skills, as they enhance understanding and usability.

Support for Various Agents

• Acknowledges that not all agents support MD files; different agents require different file types (e.g., cloue.md).

• Introduces a setup script that supports multiple coding environments (Cloud Code, Gemini, Codex, GitHub Copilot).

Installation Process

• Demonstrates executing a command to install skills across various platforms, showcasing an efficient installation process.

• Explains how the installation copies skills into respective folders while addressing compatibility issues with certain platforms.

Symbolic Links and Maintenance Challenges

• Discusses the creation of symbolic links for skills instead of duplicating files across multiple directories.

• Highlights a script's functionality that renames agent files for cloud compatibility while maintaining organization.

Synchronization and Skill Creation

• Addresses maintainability concerns when adding new skills manually across multiple locations within the project.

• Introduces two key skills: one for creating new skills and another for synchronizing them across agents automatically.

Practical Application Example

• Concludes by demonstrating how to check available skills in a project configuration before proceeding with practical implementations like creating UI elements.

How to Load a Finding in Prwler

Understanding Findings in Cybersecurity

• A finding refers to an identified issue within a resource, such as AWS, and is specific to the Prwler cybersecurity tool.

• The speaker demonstrates loading the skill name "Prer UI" and explores its task execution by observing the sub-agent's work.

Exploring Code and Task Execution

• The speaker uses Open Code to monitor ongoing processes, emphasizing delegation and task management within the system.

• The orchestrator prompts agents to explore UI structures for findings, focusing on component identification and action patterns.

Summary of Actions Taken

• After completing tasks, the sub-agent provides a summary of actions taken back to the orchestrator, indicating program completion before coding begins.

• The speaker highlights their agent's personality traits designed for teaching rather than direct coding assistance.

Creating Reusable Components

• A request is made to create a reusable button for launching scans; this involves reviewing existing code for consistency.

• Skills can be called upon as needed, allowing cultural adaptation in implementation strategies.

Synchronizing Skills Across Agents

• Introduction of concepts like scope and outoke related to skill synchronization through scripts that categorize skills based on properties.

• The synchronization process organizes skills into designated categories (UI, API), while also identifying those lacking metadata.

Final Thoughts on Implementation

• New elements are added to existing skills after synchronization; this enhances overall functionality within the system.

• The speaker encourages viewers to explore the Prwler repository for further understanding of architecture and invites feedback on usability.