Linum.ai Launches JIT-DDT for Real-time LLM Debugging

Linum.ai has launched JIT-DDT, a Just-In-Time Debugging & Development Tool engineered to provide real-time performance optimization and issue identification for applications built on large language models.

The US-based company, Linum.ai, introduced JIT-DDT on September 16, 2026, aiming to address the inherent complexities of prompt engineering and model output variability. The tool integrates directly into a developer's environment, functioning as either a VS Code extension or a command-line interface.

JIT-DDT operates by monitoring API calls, token usage, and response latency across various LLM providers, including OpenAI-compatible APIs, Claude, and Llama. It actively identifies prompt-response mismatches and unexpected model behaviors, offering immediate, actionable suggestions.

The system's core capability lies in its ability to diagnose subtle deviations in prompt execution that can lead to issues like hallucinations or irrelevant outputs. It then recommends specific prompt rewrites, adjustments to few-shot examples, or modifications to model parameters on the fly.

The system identifies subtle prompt deviations that lead to hallucination, offering immediate rewrite suggestions.

Pricing for JIT-DDT includes a free tier supporting up to 1,000 debug sessions per month. For more intensive use, individual plans are available at $49 per month, while team licenses for up to five developers cost $299 per month.

This tool enters a competitive landscape, differentiating itself from generic code debuggers and broader LLM observability platforms. While tools like LangSmith and Helicone offer comprehensive monitoring, JIT-DDT focuses on providing granular, in-workflow debugging and immediate corrective actions, aiming to accelerate the iterative development cycle for AI engineers.

For a Tokyo-based AI engineer, JIT-DDT could significantly shorten the feedback loop in developing and deploying LLM applications, allowing for quicker iteration on Japanese-language prompts and more reliable integration into local business systems.