Over the last few months I’ve been fine-tuning my AI developer stack, and I’ve settled on a workflow that balances power, cost, and practicality:
- Claude Pro (€20/month) as the foundation.
- Claude for Desktop for context-rich conversations.
- Claude Code for agentic programming support.
- Cursor IDE (also €20/month) as the coding environment where Claude and GitHub Copilot alternatives really shine.
- CLAUDE.sh and CLAUDE.md as optional community add-ons.
If you’re investing in these tools (and I’d argue €40/month for Claude Pro + Cursor is the best value in AI right now), here’s how to set them up and use them effectively.
1. Claude Chat – the Everyday Assistant
Claude Chat (in the browser) is the hub. It’s where I draft ideas, run exploratory prompts, or paste in long documents/codebases. The 100k context window in Claude Pro means you can load entire repos or manuals and ask structured questions.
Best practices:
- Keep a knowledge folder of your prompts (Markdown or Notion).
- Use Chat for long-form reasoning – architecture decisions, debugging narratives, planning blog posts.
- Don’t overload Chat with “agentic” work – save that for CLAUDE.sh or Cursor.
2. Claude for Desktop – Context Without Tabs
Claude Desktop brings AI into your OS like a background co-pilot. Highlight some code, press the hotkey, and Claude helps inline.
Best practices:
- Use Desktop for quick reviews (snippets, emails, diffs).
- Combine with Chat sessions for long reasoning.
- Handy for cross-tool workflows: move snippets between Cursor and Claude seamlessly.
3. Claude Code – Agentic Repo Support
Claude Code (inside Pro/Max) is designed for deep repo reasoning and structured programming. It shines when you need AI to operate across multiple files, plan refactors, and debug entire systems.
Best practices:
- Use for repo-wide refactors and debugging sessions.
- Pair with Cursor IDE for execution.
- Treat Claude Code as the architect, Cursor as the builder.
4. Cursor IDE – The Coding Workbench
Cursor IDE is a Claude-native VS Code fork. For €20/month it’s arguably better value than GitHub Copilot.
Why it matters:
- Tight integration with Claude for completions.
- Repo-wide understanding.
- Strong agentic workflows (“fix this error” is a killer feature).
Best practices:
- Configure Claude Pro as your main model.
- Lean into multi-file refactors.
- Pair with tests → ask Cursor to fill in implementations.
5. CLAUDE.sh vs CLAUDE.md – Which One Do You Need?
Here’s where it gets interesting:
| Tool | What It Does | Best Use Case | Pairing With Cursor |
|---|---|---|---|
| CLAUDE.sh | Command-line agent that reads/writes files and runs shell commands. | Automating workflows, scaffolding projects, repo-wide edits from terminal. | Excellent, Cursor handles editing, CLAUDE.sh handles automation. |
| CLAUDE.md | Markdown-centric workflow tool. Keeps prompts, docs, and outputs structured in .md files. | Literate programming, keeping a transparent “AI notebook” of repo changes and reasoning. | Good for documentation-driven teams, less agentic. |
In practice:
- If you want agentic automation → go with CLAUDE.sh.
- If you want repeatable docs + code reasoning trails → use CLAUDE.md.
- Many power users actually combine both: CLAUDE.md for “explain & document,” CLAUDE.sh for “do & automate.”
6. Why You Should Add Connectors and MCPs
Here’s the secret sauce: adding connectors and MCPs (Model Context Protocols) makes Claude and Cursor far more capable.
- Connectors let Claude access external systems, e.g. GitHub repos, Notion, Jira, Confluence, databases.
- MCPs provide structured, standardized APIs for Claude to pull in context while staying safe and modular.
Why this matters:
- Claude doesn’t hallucinate file state if it can fetch directly from GitHub.
- It can reason with real data, not just pasted context.
- You cut down on copy/paste overhead and improve accuracy.
Example workflow:
- Use CLAUDE.sh with a GitHub connector → Claude pulls open PRs.
- In Cursor IDE, Claude suggests multi-file fixes → you approve and commit.
- Claude.md logs the reasoning in Markdown → creating a permanent record.
This is how you evolve from “chatting with an LLM” to building a connected AI dev environment.
7. Choosing the Right Claude Model – Sonnet vs Opus
When you’re running Claude Pro, you get access to multiple model variants. The temptation is to always use Claude Opus 4.1 (the biggest model), but in practice that’s not necessary.
- Claude Sonnet 4 is “good enough” for 90% of daily work.
- It’s fast, responsive, and handles repo-level reasoning with ease.
- Great for chat, inline edits in Cursor, everyday refactors, and planning.
- If you’re prompting regularly or doing lots of small/medium tasks, Sonnet is your best balance of speed and cost.
- Claude Opus 4.1 is for the heavy lifts:
- Complex multi-file refactors where you need deep reasoning.
- Large architectural planning sessions (system design, technical strategy).
- When you’re hitting limits with Sonnet (e.g., context overflow or nuanced reasoning that requires extra depth).
Rule of thumb:
- Stay in Sonnet by default.
- Switch to Opus only when the task is deep, complex, or mission-critical.
- Think of Opus as your “surge mode”, powerful, but slower and heavier.
This way you’re not just saving credits, you’re also keeping your workflow snappy and efficient. Cursor + Claude Sonnet 4 is often indistinguishable in output quality from Opus unless you’re really pushing the model with intricate reasoning.
8. Putting It All Together – My Daily Flow
- Claude Chat (Browser) – Plan feature, explore design, draft docs.
- Claude Desktop – Quick reviews, snippets, diffs.
- Cursor IDE – Implement with completions + multi-file refactors.
- Claude Code – Repo architect for debugging/refactors.
- CLAUDE.sh – Run agentic tasks, scaffolding, automation.
- CLAUDE.md – Keep a literate programming log of prompts + outputs.
- Connectors & MCPs – Pull in live context from repos, tools, and docs.
For €40/month (Claude Pro + Cursor), you get a full-stack AI dev environment. Add CLAUDE.sh, CLAUDE.md, and connectors, and you move into the world of agentic AI, where Claude isn’t just suggesting code, it’s orchestrating workflows across your system.
In Summary
The real value of Claude comes not from Chat alone, but from the stack:
- Chat = Thinking space.
- Desktop = Inline helper.
- Claude Code = Repo architect.
- Cursor IDE = Execution environment.
- CLAUDE.sh = Terminal agent.
- CLAUDE.md = Literate notebook.
- Connectors/MCPs = Real-world context.
Stack them together, and you transform Claude from a chat assistant into a full-fledged AI development environment.
Final Thoughts & Call to Action
This setup, Claude Pro + Cursor IDE, with CLAUDE.sh, CLAUDE.md, and connectors, gives you a full-stack AI development environment that balances speed, depth, and agentic automation.
The key is knowing when to use each layer: Sonnet 4 for fast, everyday reasoning, Opus 4.1 when the task is truly deep. Chat and Desktop for thinking, Cursor for execution, CLAUDE .sh and CLAUDE.md for automation and documentation, and connectors/MCPs for real-world context.
💡 Over to you:
If you’ve got specific questions on how to set this up in your own workflow,or if you’d like me to go into more detail on any of the tools, connectors, or model use cases, I’d love to hear from you.
👉 Drop a comment below, or reach out to me directly, and I’ll either answer in-thread or create a dedicated deep-dive post with examples.
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