Capital Area .NET Users Group

SAM BASU IN-PERSON; NOTE: THIS IS THU, NOT TUE AS NORMAL

Code is cheap, but software is expensive. Modern AI is a big opportunity to streamline and automate developer workflows for better productivity. There are some challenges though – AI Models often lack knowledge and AI Agents need expertise/guidance to reliably pull off complex workflows. Context is everything for modern AI and you can bring it.

Model Context Protocol (MCP) aims to provide a standardized way to connect AI Agents to different data sources, tools and non-public information - the point is to provide deeply contextual information/expertise to AI. Skills are higher-level behaviors and instructional guardrails, that define how and when AI Agents should leverage tools to accomplish something meaningful. Subagents in AI are specialized, task-focused agents designed to handle specific, well-defined tasks within a larger AI system.

In terms of the food industry:
AI Agent = Chef 👨‍🍳👩‍🍳
MCP Tools = Raw Ingredients 🥔 🥩
Skills = Recipe Cards 📝 📇
SubAgents = Sous Chef 🔪 🍳
Loops = Door Watcher 💂👀
Developer = Restaurant Owner 👑.

So, what should developers use to bring context and guardrails to make AI work their way? Well, it depends and sometimes, the answer might be whatever combination makes developers most productive. With official SDKs and well-thought-out guidance, it is a breeze to work with MCPs, Skills or SubAgents. Developers could bring their own data, APIs, services, coding patterns and structured guidance to make AI Agents work their way. And AI Agentic workflows work the same way in IDEs or Terminals, paving the way autonomous ways of getting work done with AI. With contextual expertise to light up unique coding workflows, AI Agents can make developers ultra productive – upwards and onwards.

Spec-driven development flips the traditional workflow on its head: instead of code being the source of truth, the specification becomes the backbone of design, collaboration, and delivery. In this session, we’ll explore how GitHub Spec-Kit enables teams to treat specifications as first-class artifacts—living documents that drive architecture, implementation, and verification.

You’ll learn how Spec-Kit helps teams clearly express intent using structured, version-controlled specs that live alongside code. We’ll walk through a practical workflow that starts with defining system behavior and constraints, then progressively refines those specs into testable, automatable outcomes. Along the way, we’ll show how specs can reduce ambiguity, improve cross-functional collaboration, and make design decisions explicit before a single line of production code is written.

This talk will cover:
--What spec-driven development is (and what it isn’t)
--How GitHub Spec-Kit fits into modern developer workflows
--Using specs to align product, engineering, and AI-assisted development
--Real-world examples of turning specs into implementations with confidence

Whether you’re building greenfield systems, integrating AI into your stack, or trying to reduce costly rework, spec-driven development offers a scalable way to move faster without sacrificing clarity. Attendees will leave with concrete patterns and a clear mental model for adopting GitHub Spec-Kit in their own projects.

.NET 10 is here alongside a practically rewritten Visual Studio 2026. Learn about the new C# 14 features, VS2026 niceties, and more!