Anthropic

MCP 201 | Code w/ Claude

MCP at Sourcegraph

Prompting 101 | Code w/ Claude

In this "Prompting 101" podcast, Hannah and Christian from Anthropic's applied-ai team discuss best practices for prompt engineering, which involves writing clear instructions and providing context to language models like Claude. They use a real-world scenario inspired by a customer dealing with Swedish car insurance c...

Prompting for Agents | Code w/ Claude

Hannah and Jeremy from Anthropic's Applied AI team discuss prompting strategies for AI agents, contrasting them with basic prompting techniques. They define agents as models using tools in a loop for complex tasks, emphasizing the importance of understanding the agent's environment and providing clear heuristics. They ...

Spotlight on Canva: Empowering the world to design with code

Spotlight on Databricks: Driving data intelligence with AI

Spotlight on Manus

Spotlight on Shopify

Startup Innovation: How startups power new products with Claude

The podcast features a panel of founders who discuss their experiences building startups using Claude, Anthropic's AI model. They cover various industries, including agentic coding, design, and music generation, highlighting their journeys from zero to multi-million users within a year. Kevin from Tempo Labs introduces...

Student Innovation: How students build with Claude

Vibe coding in prod | Code w/ Claude

Erik Schulntz discusses "Vibe coding" and how to responsibly implement it in production, defining it as coding where one fully trusts AI-generated code, emphasizing the exponential growth in AI task capabilities and the need to adapt. He draws an analogy to compilers, advocating for trusting the system while focusing o...

Claude for Financial Services Keynote

Affective Use of AI

The Model Context Protocol (MCP)

In this podcast episode, Alex interviews Theo and David about the Model Context Protocol (MCP). They discuss MCP's function as a way to provide context to AI applications using LLMs through tools, resources, and prompts. They trace the origins of MCP to internal developer frustrations with data transfer and its subsequ...

Lesson 11: Conclusion | AI Fluency: Framework & Foundations Course

This podcast episode concludes a course on AI fluency, reviewing the four core competencies ("the four D's"): Delegation (deciding what tasks are best suited for AI vs. humans), Description (communicating effectively with AI systems), Discernment (critically evaluating AI outputs), and Diligence (ensuring responsible A...

Lesson 10: A closer look at Diligence | AI Fluency: Framework & Foundations Course

This podcast episode focuses on the "Diligence" competency within the AI Fluency framework. The speaker explains that diligence in AI interaction involves ethical and safe practices, encompassing responsibility for AI interactions and their implications. Three key aspects of diligence are highlighted: creation dilige...

Lesson 8: A closer look at Discernment | AI Fluency: Framework & Foundations Course

Professor Rick Dakan defines AI fluency and its key competency: discernment. He explains discernment as the critical evaluation of AI outputs, processes, and behaviors, acting as a quality control system for AI collaboration. The professor breaks down discernment into three categories: product discernment (evaluating...

Lesson 7: Effective prompting techniques (Deep Dive) | AI Fluency: Framework & Foundations Course

This podcast episode focuses on the practical skill of crafting effective prompts for AI systems like Claude. It emphasizes that prompting is about clearly communicating what you want, how you want it done, and how you want to interact with the AI. The episode outlines six foundational prompting tips: providing context...

Lesson 6: A closer look at Description | AI Fluency: Framework & Foundations Course

This podcast segment focuses on the concept of "AI fluency," specifically the competency of description in effective human-AI interaction. Professor Rick Dakan explains that effective communication with AI goes beyond simple prompts, requiring detailed explanations of tasks, context, desired formats, and audience. He ...

Lesson 4: A closer look at Delegation | AI Fluency: Framework & Foundations Course