Thu, Oct 23 · 7:45 PM EDT
AI is transforming how software gets built — and how leaders think about innovation, productivity, and strategy. In every company and organization, intelligent systems will soon play a central role. To lead effectively, it’s not enough to use AI — you need to understand how the new paradigm of Agentic Coding works.
This introductory session , part of the Vibe Coding for Absolute Beginners series, offers a clear, conceptual tour of this emerging landscape. Designed for aspiring AI leaders , it explains how Agentic Coding differs from traditional development — and what new tools are shaping the way humans and AI collaborate to write code.
No coding experience is needed. You’ll learn the categories of tools that define modern AI development, how they fit together, and why this matters for the future of software and organizations.
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## What You’ll Learn
You’ll gain an intuitive understanding of:
The key components of the Agentic Coding environment
How human developers and AI models now co-create software
The role of IDEs, models, and agentic frameworks in this new workflow
What it means to “guide” AI rather than program it
By the end, you’ll have a mental map of the agentic development stack — and a leadership-level grasp of how it changes the work of coding, collaboration, and creativity.
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## Workshop Stages
### Stage 1: The Coding Cockpit — The IDE
Every AI developer needs a command center — a cockpit for writing, testing, and interacting with AI-generated code. We’ll start with the Integrated Development Environment (IDE) , focusing on Visual Studio Code (VS Code) as the central hub for Agentic Coding.
You’ll see how modern IDEs integrate AI directly into the workspace, providing context, suggestions, and collaboration between human and machine.
Key Learning: The IDE is where human intent meets AI execution — your cockpit for coding with intelligence.
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### Stage 2: Workflow and Specifications
Before agents can code effectively, they need direction — a clear specification of goals, requirements, and workflow.define and communicate specifications to AI tools: what you want built, the desired behavior, and the structure of the output.
We’ll also look at workflow practices , including how tools like Git and version control systems fit into agentic collaboration — ensuring humans remain in charge of review, testing, and integration.
Key Learning: Clear specifications and structured workflows turn Agentic Coding from chaos into coordinated intelligence.
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### Stage 3: The Engines of Intelligence — The Models
Next, we’ll look at the engines that power AI coding: large language models. We’ll explore several leading models — Claude Sonnet , GPT Codex , and GLM — and discuss what makes each unique in how they “understand” and generate code.
You’ll learn how these models translate natural language instructions into working code, and why selecting the right model matters.
Key Learning: Models are the engines of Agentic Coding — they convert ideas into executable logic.
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Stage 4: The Orchestrators — Agentic Coding Tools
Finally, we’ll explore agentic coding tools as orchestrators — systems that manage, coordinate, and execute complex development workflows.OpenAI’s Codex , Anthropic’s Claude Code , and Droid can plan tasks, delegate work to models, and integrate results into a cohesive solution.
Rather than simply co-piloting, these agents oversee an entire process — reasoning about dependencies, sequencing steps, and adapting to feedback.Key Learning: Agentic Coding tools act as orchestrators, turning AI from a helper into a system capable of managing multi-step, collaborative workflows.
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## What You’ll Take Away
A clear conceptual map of the Agentic Coding ecosystem
Understanding of how IDEs, specifications, models, and agents work together
Awareness of leading tools shaping the next generation of AI-driven development
Confidence to discuss the future of software creation from a leadership perspective
