Claude Code For Enterprise Software Development
Published 7/2026
Created by Arjun Vaid, School of AI
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 139 Lectures ( 10h 51m ) | Size: 10.2 GB
Build secure, scalable Claude Code workflows with CLAUDEmd, hooks, skills, MCP, subagents, plugins, and governance
What you'll learn
Configure Claude Code for professional development workflows and large enterprise repositories. Explore unfamiliar codebases and create effective repository maps using CODEBASE_MAPmd. Write clear global and service-specific instructions using root and nested CLAUDEmd files. Scope Claude Code sessions to reduce context noise and improve task accuracy. Define test, lint, type-check, build, and completion requirements for reliable validation. Protect secrets, generated files, dependencies, and sensitive directories through permission policies. Automate formatting, validation, reminders, and summaries using Claude Code hooks. Create reusable Agent Skills for investigation, implementation, testing, review, and documentation. Connect Claude Code to internal engineering knowledge through secure MCP integrations. Use code intelligence and language servers to navigate symbols, references, implementations, and dependencies. Design specialized subagents for repository investigation, security reviews, and testing analysis. Package instructions, skills, hooks, and integrations into reusable team plugins. Establish governance, human-review, privacy, security, and rollout controls for enterprise adoption. Measure improvements in code quality, accuracy, safety, rework, and development efficiency. Build and apply a complete Claude Code enterprise harness in a final hands-on capstone.Requirements
Basic familiarity with software development concepts is helpful but advanced expertise is not required. A working knowledge of at least one programming language, such as Python, JavaScript, TypeScript, Java, or C#. Basic familiarity with terminals, command-line tools, files, folders, and source-code repositories. A computer capable of running Claude Code and the course's sample enterprise commerce platform. Access to Claude Code and any account or subscription required to use it. A code editor such as Visual Studio Code, IntelliJ IDEA, PyCharm, or another preferred development environment. A willingness to work through hands-on repository exploration, configuration, and implementation exercises. Prior experience with CLAUDEmd, MCP, hooks, Agent Skills, subagents, or plugins is not required. Enterprise architecture or AI governance experience is helpful but not required. Step-by-step guidance is provided throughout the course.Description
This course contains the use of artificial intelligence.
Modern enterprise software development demands more than generating code from a prompt. Large repositories contain multiple applications, shared packages, service boundaries, legacy components, security requirements, validation workflows, ownership rules, and organizational knowledge that an AI coding assistant must understand before making safe changes.
Claude Code for Enterprise Software Development teaches you how to transform Claude Code from a general coding assistant into a structured, repeatable, and governedAI coding harness for real engineering teams. Throughout the course, you will work with an enterprise commerce platform and progressively build the context, controls, workflows, and integrations Claude Code needs to operate effectively inside a complex codebase.
You will begin with the fundamentals ofClaude Code, repository navigation, prompting, and codebase exploration. You will then learn how to reduce context noise by creating a practicalCODEBASE_MAPmd, defining global project rules withCLAUDEmd, and adding layered service-level instruction files. These techniques help Claude understand architecture, ownership, dependencies, commands, boundaries, and expectations before changing code.
The course goes beyond prompt engineering. You will design clearvalidation commands, establish a measurabledefinition of done, and require Claude to report test, lint, type-check, and build results honestly. You will also configure safer tool usage by protecting secrets, excluding generated files, reviewing terminal commands, and applyingleast-privilege permissions.
Every major concept is reinforced through hands-on implementation. You will install and configure Claude Code, map a multi-service repository, write global and nested instruction files, define validation workflows, create permission rules, automate checks with hooks, build reusable engineering skills, configure code intelligence, develop an internal MCP server, delegate investigation to subagents, and package the completed harness for team adoption. Rather than studying isolated features, you will see how each component works together as part of a production-oriented engineering system designed for consistency, traceability, maintainability, and controlled execution.
Next, you will automate engineering workflows usingClaude Code hooks, package repeatable procedures asAgent Skills, and improve large-codebase navigation throughcode intelligence and language-server capabilities. You will connect Claude Code to internal architecture, ownership, and engineering knowledge through theModel Context Protocol (MCP) while applying appropriate security and access controls.
For more advanced workflows, you will create specializedsubagents for read-only investigation, security review, testing analysis, and structured reporting. You will then package CLAUDEmd files, skills, hooks, MCP integrations, and review practices into reusableClaude Code plugins that can be versioned, tested, distributed, and maintained across teams.
The final sections focus onenterprise AI governance, adoption strategy, human review, privacy, data handling, effectiveness metrics, incident tracking, configuration ownership, and organization-wide rollout. In the capstone, you will use the completed harness to implement a refund feature and compare Claude Code's performance before and after the enterprise controls are introduced.
This practical, project-based course is designed for developers, architects, platform engineers, technical leads, and engineering managers who want to useAI-assisted software development responsibly at scale. By the end, you will have a complete blueprint for creating a safer, more accurate, and more productive Claude Code environment for large repositories and enterprise engineering teams.
Who this course is for
Software developers who want to use Claude Code for more than isolated code-generation tasks. Senior engineers working with large monorepos, microservices, shared libraries, or legacy systems. Software architects designing AI-assisted development standards for enterprise platforms. Platform and developer-experience engineers creating reusable tools and workflows for engineering teams. Technical leads responsible for code quality, validation, security, and development consistency. Engineering managers evaluating how Claude Code can be adopted safely across teams. DevOps and DevSecOps professionals interested in permissions, automation, validation, and governance. Security engineers responsible for protecting source code, secrets, environments, and internal knowledge. AI engineers building MCP servers, Agent Skills, subagents, hooks, and context-management workflows. Technology leaders planning controlled pilots and organization-wide Claude Code adoption. Consultants and forward-deployed engineers implementing AI-assisted development practices for clients. Developers preparing for the future of enterprise AI-assisted software engineering.HomepagePlease Login or Register to see this code Please Login or Register to see this code