5 Essential Terms for Building and Using AI Coding Agents

This video explains the core concepts behind AI-assisted software development, covering five key terms with practical examples and best practices so you can leverage AI models the way leading teams do.

■ Prompt Engineering
- Crafting instructions for a model, from role-based prompts to domain expertise
- Few-shot prompting and chain-of-thought examples for smaller, locally run models
■ Context Engineering
- Managing the context window: system prompts, tools, MCP servers, documents, and codebases
- Compacting, summarizing, and using sub-agents to preserve context quality
■ Harness Engineering
- Runtime capabilities that let a model act, verify results, and iterate
- Sandboxing, orchestration, and connections to CI pipelines and observability tools
■ Loop Engineering and Graph Engineering
- The agent loop, triggers such as cron jobs, pull requests, and alerts
- Human-in-the-loop approval, parallel agents, and graph structures
■ Software Factory
- Automating the software development lifecycle with task-based agents
- Isolation, identity, and observability for each agent

It is aimed at developers, students, designers, and managers who want to understand agentic engineering. Viewers will gain a working vocabulary for AI-assisted development and clear guidance on where to start applying these concepts to their own work.