Welcome to Langfuse Academy
Building AI applications and agents is very different from traditional software. Outputs are probabilistic, and teams need to reason about quality, cost, latency, and the tradeoffs between them. Langfuse Academy explains the AI engineering lifecycle to help you understand how the pieces fit together and what it takes to ship from prototype to production.
What you will find here
The structure of the academy follows the AI engineering lifecycle, which is a continuous loop. It explains why each step exists, why, and how the steps connect. For each step, you can choose how deep you go.
Start with The AI Engineering Loop, or dive into an individual step right away:
Some pages explain the high-level concepts. Others are deeper dives into individual parts of the lifecycle. You can read the full sequence or jump to the topic that is most relevant to your team right now.
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 way of making the core ideas, vocabulary, and workflows behind LLM application development easier to access for everyone.
Who this is for
- AI engineers and software engineers building LLM applications and agentic systems
- Product managers who need to reason about quality, iteration, and tradeoffs
- Technical and business leaders who need a working understanding of how AI systems are built and improved
- AI agents that support humans in understanding AI engineering concepts and workflows
