From Idea to Tutorial: Orchestre's New Command is a Masterclass in Context Engineering

Published: June 26, 2025 | 8 min read

If you've worked with AI, you know the feeling. You have a brilliant idea, but turning it into a functional application with an AI assistant feels like a game of chance. You write a prompt, get some code, and then spend hours trying to fit it into your project, fix its errors, and teach it about your specific needs.

The problem isn't the AI's power; it's the AI's environment. It lacks the deep, specific context of your project. This is why the most advanced AI engineering has moved beyond simple "prompt engineering" to a more holistic discipline: Complex Context Engineering.

And today, Orchestre is releasing a new command that perfectly embodies this shift: generate_implementation_tutorial.

For Our Non-Technical Readers: What is Context Engineering?

Imagine you hire a master chef to cook in your kitchen.

A basic approach (like simple prompt engineering) is to just give them a recipe title: "Make coq au vin." They'll make a technically correct dish, but it might not be what you wanted. They might use an ingredient you're allergic to, a pan you don't own, or make a portion size for two when you're hosting twenty.

Context engineering is like giving that chef a full briefing:

• "Here is our detailed recipe book that shows our family's preferred style (existing patterns)."
• "The pantry is stocked with these specific ingredients, and we have these pots and pans available (project dependencies and constraints)."
• "We're cooking for a 20-person dinner party, and Uncle Bob is allergic to mushrooms (user requirements)."
• "Remember, we always sear the chicken before braising for extra flavor (best practices and conventions)."

Suddenly, the chef isn't just cooking; they're creating the perfect meal for your specific situation.

Orchestre is the expert that briefs the chef (the AI), ensuring the final result is exactly what your project needs.

Introducing: generate_implementation_tutorial

We've transformed our command (formerly build-saas-from-master-plan, now generate-implementation-tutorial) to do something revolutionary. Instead of just generating a list of tasks, it now generates a complete, interactive tutorial tailored to your idea. It turns any concept into a step-by-step guide that you and your AI assistant can follow together.

It is the ultimate context engineering tool.

How It Works: Engineering the Perfect Workflow

When you run the command, Orchestre performs a multi-stage process:

1. Deep Discovery: It analyzes your idea, but more importantly, it scans your entire project. It reads your existing CLAUDE.md memory files, identifies your architectural patterns, and understands your technology stack.

2. Blueprint Creation: It designs a comprehensive, phased implementation plan. It maps out dependencies, identifies potential risks, and defines the optimal sequence of operations.

3. Tutorial Generation: This is the magic. It translates the blueprint into a user-friendly TUTORIAL.md file. This file doesn't just list tasks; it provides a narrative. For each step, it gives you:

   • The Goal: What you are trying to achieve.
   • The Exact Prompt: The precise, context-rich prompt you should give to your AI.
   • What to Expect: A description of the code or changes the AI should produce.
   • Verification Steps: How you, the human developer, can validate the AI's work.

An Example of the Generated Tutorial

Imagine you run: /generate-implementation-tutorial "Build a team collaboration feature for our project management app"

Orchestre creates TUTORIAL.md with steps like this:

### Step 2.1: Create the API Endpoint for Teams

**Goal:** To create a secure RESTful endpoint for managing teams, allowing users to create and view teams they belong to.

**Your Prompt:**

> /execute-task "Following our established API patterns, create a new RESTful endpoint for `/teams`. It should support `GET` to list teams and `POST` to create a new team. Ensure input is validated using our Zod schemas and that only authenticated users can access it. The endpoint should only return teams that the current user is a member of."

**What to Expect:**

The AI should create a new route handler file (e.g., `app/api/teams/route.ts`). This file will contain logic for handling GET and POST requests, including data validation, authentication checks, and database queries.

**Verification:**

1.  Check that the new route file was created in the correct directory.
2.  Review the code to ensure it uses your project's existing authentication middleware and validation patterns.
3.  Run the application and test the endpoint using an API client like Postman to confirm it works as expected.

This single command engineers the entire context for building a complex feature, guiding both you and the AI through a proven, safe, and efficient process.

Works for Any Project Type

Whether you're building:

• SaaS Applications: Multi-tenant architectures with billing and teams
• REST APIs: Scalable backend services with proper authentication
• Mobile Apps: React Native applications with native features
• Enterprise Features: SSO, audit logs, compliance requirements
• Bug Fixes: Systematic approaches to debugging and patching
• Microservices: Distributed systems with proper communication patterns

The command adapts to YOUR specific project type and generates the perfect tutorial.

Why This is a Game-Changer for AI Development

• Predictability: By providing the exact prompts and verification steps, it removes the guesswork. You get consistent, high-quality results every time.
• Learning & Onboarding: The generated tutorial is the best possible documentation. New developers can use it to understand not just what to build, but how and why your team builds it that way.
• True Collaboration: It fosters a powerful partnership between the developer and the AI. The developer provides the strategic oversight, and the AI handles the complex implementation, with clear checkpoints along the way.
• Capturing Expertise: It allows senior developers and architects to encode their best practices into a repeatable, automated process that the whole team can benefit from.

Conclusion: Stop Prompting, Start Engineering

The era of simply "prompting" an AI and hoping for the best is over. The future of software development lies in our ability to engineer rich, dynamic, and persistent context that guides AI to do its best work.

Orchestre's new generate_implementation_tutorial command is at the forefront of this movement. It's more than a command; it's a statement about how we believe software should be built in the age of AI—through intelligent partnership, guided by expertly engineered context.

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Ready to build your next great idea with a personal AI tutor? Get started with Orchestre and try the generate_implementation_tutorial command today.