People often ask me what tools I use daily. Here’s my complete stack, with the reasons behind each choice.
For working with LLMs
Claude Code — My main tool for anything code-related and codebase exploration. The quality of instruction following and large context window make it my first choice.
Claude.ai — For long conversations, spec writing, brainstorming. I use projects to maintain context between sessions.
ChatGPT — For tasks where I need image generation (DALL-E), or when a client is in the OpenAI ecosystem and I need to test in their environment.
Mistral Le Chat — For projects with data privacy constraints. European hosting, useful for certain clients.
For agent prototyping
n8n (self-hosted) — For simple to moderate agent workflows. Visual interface, ready-made integrations, rapid deployment. Ideal for validating a use case before coding.
LangChain / LangGraph — When you need more complex agents with state and loops. More code, more flexibility.
Claude Code + MCP — For prototypes that need to interact with real systems from the start. The most powerful combination I’ve found.
For project management
Linear — For task and sprint tracking. Clean interface, GitHub integrations, smart notifications.
Notion — For agent documentation: system prompts, data schemas, architecture decisions, evaluation results.
Loom — For sharing async demos with clients. Much more effective than a meeting for showing “how the agent behaves in this case.”
For evaluation
Braintrust — LLM evaluation platform. Lets you define test datasets, run automated evaluations, compare prompt versions.
Google Sheets — For manual evaluations on small datasets. Simple, shareable, sufficient for 50-100 test cases.
What I’ve stopped using
Consumer AI no-code platforms — Seductive at first, but limitations appear quickly once you go beyond simple use cases.
Proprietary LLM wrappers — Several startups offer their “abstraction layer” on top of LLMs. In practice, this adds complexity and dependency without real added value for most projects.
My rule: if I can do the same thing directly with the LLM API in 2 hours, I don’t pay for a wrapper.
Further reading :
