Real-Time Production Insight. Zero Overhead.

Hud brings real-time, function-level runtime context directly into your IDE - giving both developers and code-generating agents continuous visibility into how code actually runs in production.
At the center is Hud’s Runtime Code Sensor, which streams structured execution data-including performance characteristics, errors, and function-level activity-into your development workflow. This powers an integrated Runtime Intelligence Layer with four core capabilities:

Function-Level Runtime Insight

Hud automatically captures how every function behaves in production, including:

Execution durations
Unhandled exceptions
Real-time function activity

This context is streamed with no setup or instrumentation, giving developers immediate visibility during development and review.

IDE-Integrated Runtime Feedback

In supported IDEs (VSCode, JetBrains), Hud overlays each function with a compact runtime summary called a Hudder. Hudders display key runtime signals, such as:

Error spikes
Shifts in performance
Function execution behavior

Clicking a Hudder opens an in-context panel with additional metrics like caller/callee relationships and impact scope-so developers never leave their IDE to understand what’s happening in production.

Automated Runtime Diagnostics

Hud continuously analyzes live behavior to identify issues without requiring rules or thresholds. It surfaces:

Behavioral changes after deployments
Newly introduced exceptions
Performance regressions across services

Each signal is tied to the specific function responsible, along with relevant upstream and downstream context-supporting fast, in-context root cause identification.

Real-Time Runtime Context for Code-Generating Agents

Hud’s MCP server streams function-level runtime data directly into supported code-generating agents (e.g., Copilot, Cursor, Windsurf), enabling them to:

Align code suggestions with how the system actually behaves
Avoid generating logic that introduces runtime risks
Offer more relevant, production-aware completions and reviews

This makes AI-generated code safer and more reliable by default, accelerating delivery without compromising stability.