Mastering Claude Code & AI Agents [2026]

Discover cloud code, an agentic AI coding tool that reads your codebase, edits files, runs commands, and autonomously builds apps in VS Code.

Demonstrate building a business landing page with Cloud Code, starting with no skills, then adding a front-end design skill to enhance a Sugar and Bloom HTML page.

Learn how Claude loads the front end design skill from a skill.md file to deliver production grade UI. Explore where skills live and how they load automatically.

Install the front-end design skill for Claude in a dedicated project folder, then verify its setup to enable production-grade landing pages with bold typography and color.

Rebuild the sugar and bloom bakery landing page with the front end design skill and Claude Code to include a hero, quiz, menu, testimonials, and a contact form.

Learn skill.md fundamentals and why two folders, Claude and agents, reference the same skill.md. Use CLI and VS Code to share skills across Claude, Gemini, and other agents.

Build a pet grooming landing page with a mindful paws hero, interactive quiz for pet type and size, service options, price estimate, services, gallery, and a booking form.

Build a landing page from scratch using Claude Code, first without skills, then with the front end design skill. See how to structure hero, services, quiz, gallery, and price estimate.

Learn how to use built-in slash commands in cloud code to speed up workflows, switch models, manage context, and generate a Claude.md project guide.

Learn to create a reusable Claude Code slash command that applies your brand identity—from colors to typography—to generate branded flyers, emails, and social posts with consistent, warm, professional outputs.

Design and deploy a my brand slash command in Claude Code to apply your brand identity—colors, fonts, tone, and vocabulary—to content across emails, social posts, and pages.

activate the my brand slash command in Claude Code to generate branded emails, flyers, and social posts with html formatting, using your brand voice and colors.

Create a brand voice for Verde kitchen and build a slash command in Claude Code, then test by generating a branded email and a flyer in the same style.

Create branded assets with slash commands using Claude code and Gemini to generate a hero image and flyer, applying the Verdi kitchen brand identity.

Understand cloud plugins that bundle skills, tools, and sub-agents via the model context protocol, enabling workflows, hooks, and automated development with Ralph loops and PlayWrite.

leverage cloud code with playwright and marketing plugins to perform competitor analysis, capture screenshots, assess messaging, and craft a four-week content calendar and brand positioning for Pulse and Flow Studio.

Use Claude with the Playwright plugin to browse competitors, capture screenshots, and extract hero messages, call to action, and pricing for Austin, then generate a competitive analysis with actionable recommendations.

Create a marketing action plan for Pulse and Flow Boutique Studio in Austin, blending hiit with yoga recovery, using competitive analysis, brand positioning, content strategy, landing pages, and quick wins.

Run a competitive analysis with Playwright and marketing plugins to compare Ember and Origin to Blue Bottle, Stumptown, Counter Culture, and outline differentiation strategies for origin, sustainability, and brand messaging.

Use Cloud Code with Playwright and marketing plugins to perform competitor analysis of three coffee brands, craft Ember and Origin brand positioning, and generate a marketing plan and content calendar.

Learn to structure cloud.md, manage context size, and build real-world apps with cloud code without coding. Define a concise permanent briefing with tech stack and workflows.

Explore how context windows work in Claude with token-based limits, system prompts, tools, and memory; learn to monitor and compact context to preserve project history.

Build a no-code calorie tracker app using cloud code across three phases, adding ai-powered image calorie estimates via Gemini API and iterative improvements with Ralph Loops and plan mode.

Build a calorie tracker web app with Next.js and TypeScript, using a local SQLite database to log foods and calories, while configuring a no-js runtime and Gemini API key.

Transform your calorie tracker by adding ai-powered features that estimate calories from text, photos, or quick add entries using the Gemini API and a new backend to store nutrition data.

Design and implement backend API routes for text and image nutrition lookups using the Gemini API, integrate with the existing calorie tracker, and update cloud docs to reflect the changes.

Connect the back end and front end by wiring three food-adding methods: text-based queries, image analysis, and quick add through Gemini API routes, completing phase two of the app.

Leverage the Ralph Loop plugin to iteratively improve the calorie tracker app over three high-impact iterations, combining front-end design skills for a professional, responsive UI with calories, macros, and categories.

Implement AI feedback loops with the Ralph loop plugin and front-end design skill to iteratively review, improve, and polish a calorie tracker app built in Claude code.

Learn the fundamentals of ai agents and how cloud code enables end-to-end agent creation, including building other agents in the autonomous era.

Explore the fundamentals of ai agents powered by llms that plan, execute tasks, use memory and tools, and coordinate with guardrails and handoffs to deliver automated outcomes.

Explore how AI agents built on an LLM use tools, memory, and a planning loop to act. See weather walkthroughs with a system prompt, memory updates, and API calls.

Explore the model context protocol (MCP) as an open standard for AI tool interaction. See how MCP provides a plug-and-play unified API for Gmail, Calendar, and currency converters.

Explore high level agentic frameworks for ai agents, including OpenAI Agents SDK, Cloud Agents SDK, open-source options like LandGraph, Crue AI, Autogen, plus low-code tools such as N8n.

Explore the OpenAI Agents SDK, a lightweight Python-first, open-source framework for building agentic AI apps with few primitives—agents, tools, handoffs, guardrails, and tracing—usable with 100+ LLMs.

Discover how to build AI agents with memory using the OpenAI Agents SDK, defining an agent with a name, persona, tools, handoffs, guardrails, and output type, then run it.

Build a personal finance AI agent with memory using the OpenAI Agents SDK and sqlite-based session storage to remember expenses, budgets, and past conversations for personalized guidance, with end-to-end testing.

Build a personal finance AI agent with memory using the OpenAI Agents SDK in Google Colab. Define, run prompts, and prepare memory enhancement via cloud code automation.

Add memory to an ai agent with a sqlite session so it remembers past conversations and budgets, tracking groceries, Uber, and dining.

Automate ai agent development using Claude Code and OpenAI agents sdk with cloud code, install skills, and configure the environment with OpenAI api key to build memory-enabled and memory-free agents.

Set up a virtual environment named venv, install the OpenAI Agents SDK, and configure a .env file with the OpenAI API key to enable Cloud Code driven agent development.

Build a no memory ai personal finance advisor using cloud code and the OpenAI Agents SDK, tracking spending by category and offering budget advice.

Enhance a Jupyter notebook finance advisor by adding memory with an SQLite session and test it against a no-memory baseline.

Design a team of AI agents—researcher, analyst, and writer—using Tavli search and a manager function to orchestrate a structured, end-to-end workflow with Pydantic-driven outputs.

Build a multi-agent workflow by wiring a researcher, analyst, writer, and manager agents in a Jupyter notebook running on Google Colab, using the Tavli search tool and OpenAI Agents SDK.

Build and run an analyst ai agent that analyzes research notes from the researcher agent to extract key trends, risks, and insights, then generate an executive report with follow-up questions.

Explore building a team of AI agents using the OpenAI Agents SDK and Cloud Code, orchestrating a multi-agent workflow with researcher, analyst, and writer roles, prompts, and self-improving automation.

Build a multi-agent workflow by integrating Tavli web search with OpenAI agents, configure API keys in .env, and define researcher and analyst roles using Pydantic models in a Jupyter notebook.

Build a multi-agent workflow with researcher, analyst, and writer, and a SQLite session for persistent memory to deliver a fully automated executive report from question to summary, analysis, and follow-ups.