From Workflow to Agents: API and AI As Product

This lesson explores the shift in software development from structured operations to intelligent, autonomous systems, emphasizing APIs and AI agents as strategic products. APIs—interfaces that enable software to communicate—are vital to automation and business workflows. REST and GraphQL are two common API architectures: REST uses standard HTTP methods, while GraphQL allows more precise data queries. When treated as products, APIs require strong documentation, customer-centric design, and alignment with business goals. An API-first mindset enhances collaboration and long-term success.

As AI evolves, workflows increasingly integrate Large Language Models (LLMs). Two approaches emerge: agentic workflows, where LLMs perform defined tasks within existing processes, and AI agents, which act autonomously to achieve broader goals. The Model Context Protocol (MCP) supports this future by standardizing how LLMs access tools, data, and prompts. Open-sourced for easy adoption, MCP bridges APIs and AI agents. Together, they redefine digital services, requiring thoughtful design, measurable value, and seamless developer experiences.

Self-study Videos

1. What is Workflow Automation? (2 min 27 sec)
2. What is an API? (explained in 3 minutes) (3 min 17 sec)
3. API Workflows: Describing and Documenting Business Processes (16 min 17 sec)
4. What is a REST API? (9 min 11 sec)
5. GraphQL vs REST: Which is Better for APIs? (7 min 30 sec)
6. How to create an API Product Strategy (36 min 22 sec)
7. API-as-a-product: The Key to a Successful API Program (33 min 20 sec)
8. Master API-First Design: A Developer’s Success Guide (7 min 4 sec)
9. The API product owner (7 min 50 sec)
10. Agentic AI: Workflows vs. agents (5 min 30 sec)
11. Service Design in Era of AI (4 min 30 sec)
12. The Model Context Protocol (MCP) (19 min 34 sec)
13. Why Everyone’s Talking About MCP? (5 min 3 sec)