If you're building applications with OpenAI, Gemini, or LangChain agents, you already know the pain:...
If you're building applications with OpenAI, Gemini, or LangChain agents, you already know the pain: Large Language Models are unreliable.
You ask for a JSON response. You set up a strict parser like Pydantic or Marshmallow. But then:
The LLM cuts off mid-sentence because it hit the token limit.
The output has a missing closing bracket }.
The LLM outputs Python-style single quotes ('id') or True instead of standard double quotes and true.
If you stream tool calls or structured output from an LLM, you have almost certainly seen one of...
If you're building AI agents or running LLM pipelines in production, you already know the pain: tool...
LLMs are probabilistic text generators. In a notebook demo, that's fine. In production, it means your...
Every team we talk to has a version of the same story. They built an LLM integration that works well...
Have you ever tried to read a massive pile of reports and summarize them in under 50 words? It’s...
LLMs are great at generating text. They're terrible at generating structured data reliably. If you've...
