Welcome to Langfuse Academy
Building with LLMs changes the job of engineering teams. Once outputs become probabilistic, a system can be technically healthy and still produce responses that are wrong, incomplete, off-brand, unsafe, or simply not useful.
That changes what teams need to understand and manage. It is no longer enough to ask whether the system ran. You also need a way to reason about output quality, iteration, and the tradeoffs that come with shipping AI products.
Langfuse Academy exists to help you build that mental model. It maps the AI engineering lifecycle step by step so you can understand how the pieces fit together and what it takes to move from prototype to production.
Why we are publishing this
Langfuse is open source, and we want to open source the conceptual side of AI engineering too. The Academy is our attempt to make the mental models, vocabulary, and workflows behind LLM application development easier to access for everyone.
Who this is for
- AI engineers building LLM applications and agents
- Software engineers moving into AI product development
- Product managers who need to reason about quality, iteration, and tradeoffs
- People learning the field and trying to understand the core concepts
- Technical and business leaders who need a working model of how AI systems are built and improved
What you will find here
Academy follows the AI engineering lifecycle from first visibility into production behavior all the way to structured improvement and evaluation. The goal is to explain why each step exists, what problem it solves, and how the steps connect.
Start with The AI Engineering Loop for the high-level map, then go deeper into the individual parts:
Some pages stay at the conceptual level, and some go deeper into specific disciplines. You can read the full sequence or jump to the topic that is most relevant to your team right now.
Academy and docs do different jobs
Academy focuses on high-level concepts and mental models. The docs and guides cover Langfuse features, product implementation details, and step-by-step how-tos.
Use Academy to understand the lifecycle. Use the docs when you are ready to implement it in Langfuse.