The New Developer Workflow How AI Transforms Ideas into Code Daniel Sogl @sogldaniel Software architect 

Daniel Sogl • Software architect @ Thinktecture AG • Focus: Angular, Capacitor and AI-Coding • Creator of https://codingrules.ai • Socials: https://linktr.ee/daniel_sogl About me 

https://tinyurl.com/tt-smarter 

From suggestions to end-to-end support Idea MVP Code Review • Ideas can be explored and refined with AI tools like ChatGPT or Gemini. • Product concepts can be validated using MVP platforms like Lovable.dev or Firebase Studio. • Code can be generated efficiently with AI- powered plugins like GitHub Copilot or AI-first IDEs like Cursor and Windsurf. • Code can be tested, documented, and reviewed using AI agents like GitHub Copilot and Google Gemini Code Assist. The New Developer Workflow 

• Start with a rough idea – e.g., a productivity tool or developer helper • Use ChatGPT or Gemini Deep Research to refine your concept, identify use cases, and generate user stories • Define clear features, personas, and goals • AI is your thinking partner – not just your coding assistant Tipp: Use GPT Researcher as an Open-Source alternative with your own API keys Finding the Idea: Deep Research with ChatGPT 

• Use platforms like v0, Lovable.dev, or Firebase Studio • Generate first screens, forms, flows, and ideas • Visualize user interaction and validate core features • Outcome: A lightweight MVP that guides implementation Build a Visual MVP with AI Tools 

• Create a GitHub repository with your app structure (Angular or another framework) • Define the initial structure: folders, components, services • Add a task list and define your scope (start small!) • Keep it simple – Copilot and AI tools thrive in structured environments Tipp: Use GitHub Copilot MCP-Server to create the tasks based on your previously created idea Set Up Your Project Foundation 

• Configure Custom Instructions to match your coding style (with the help of codingrules.ai) • Example: How functions, tests, and comments should look or how the architecture is defined • Set up the MCP Server to fetch external knowledge • AI works best when it knows your rules – make them explicit Tipp: use short, self-contained statements Customizing Copilot with Instructions & MCP 

• Break down the app into clear tasks: services, components, logic units (sequential-thinking MCP server) • Prepare reusable prompts for repeated patterns (e.g. “Generate an Angular Service that...”) • Reuse your instructions to guide Copilot consistently • Save time and ensure quality with predictable outputs Define Smart Tasks with Reusable Prompts 

• Use Copilot with VS Code or AI-first IDEs like Cursor or Windsurf • From prompts and comments to full services or UI components • See how Copilot auto-completes entire flows – respecting your structure (using Agent mode) • Your job: guide, validate, refine Generate Code with GitHub Copilot 

Guide Validate Refine Your job 

Bonus: Choosing the Right AI Model • Balance between cost and performance: Go with GPT-4.1, GPT-4o, or Claude 3.5 Sonnet • Fast, lightweight tasks: o4-mini or Claude 3.5 Sonnet are your buddies • Deep reasoning or complex debugging: Think Claude 3.7 Sonnet, o3, or GPT 4.5 • Multimodal inputs (like images): Check out Gemini 2.5 Pro or GPT-4o 

• Let Copilot write unit tests based on the logic it just generated (or the other way around using TDD) • Improve readability by generating inline comments and doc blocks • Bonus: Generate Markdown files like README.md or api.md • Result: More time for logic – less for boilerplate Write Tests and Documentation with Copilot 

• Use GitHub Copilot for inline code reviews • Let it highlight performance issues, refactoring suggestions, or missing checks • See suggestions directly in VS Code • Copilot becomes your pair reviewer – early and fast Review Code in Your IDE with Copilot 

• Let Copilot review your Pull Requests on GitHub • It generates meaningful comments on diffs and suggests improvements • Auto-generates PR descriptions summarizing your changes • You focus on logic – AI helps with structure and clarity Review PRs with Copilot on GitHub 

• We started with an idea... • Turned it into a visual MVP • Implemented logic with Copilot • Generated tests, docs, and reviews From Idea to App – The Result Idea MVP Code Review 

• Clear prompts = Better suggestions • Customize Copilot for better results • Use MCP-Servers for external context • Always validate AI-generated code • Treat AI as a partner, not a replacement Lessons Learned & Best Practices 

Q&A Daniel Sogl @sogldaniel https://linktr.ee/daniel_sogl