May 09, 2026
Building an AI agent in a notebook is easy; making it work in production is hard. Literal AI is an observability and evaluation platform designed specifically for the "agentic" era of software, where LLMs make decisions and take actions autonomously.
Literal AI tracks every step of your agent's reasoning process. You can see the raw prompts, the model's intermediate thoughts, and the final actions in a clean, visual timeline. This "step-by-step" visibility is crucial for debugging why an agent failed or why it took a specific, unexpected path.
The platform allows teams to quickly curate datasets from production logs and run evaluations against them. By comparing different model versions or prompt strategies, you can quantitatively measure improvement, ensuring that your AI agents are getting more reliable and accurate over time.