# Hud

Runtime intelligence layer for AI-safe code generation and issue detection.

- Category: Developer Tools
- Pricing: Free plan available
- Free trial: yes
- Tags: Coding Assistants
- Website: https://www.hud.io/?ref=aigregator&utm_source=aigregator&utm_medium=referral
- Aigregator page: https://aigregator.com/tools/hud
- API: https://x402.aigregator.com/v1/tools/hud

## Overview
Hud is a runtime intelligence platform designed specifically for coding agents and AI-generated code. It operates as a runtime layer that runs alongside production code, automatically detecting errors, performance degradations, and CPU spikes while capturing detailed forensic context. Unlike traditional observability tools built for human analysis, Hud is purpose-built for AI coding agents like GitHub Copilot, Cursor, and Windsurf, providing real-time function-level runtime data directly into the IDE.

The platform works by mapping the entire codebase with no configuration required, gathering deep forensic context when issues occur, and sending this context to AI agents for generating safe, code-level fixes with impact and risk analysis. It installs in seconds with a single line of code and requires no maintenance or manual instrumentation. A key distinction is that Hud captures everything without sampling, ensuring critical events are never missed, whereas traditional observability tools sample data and require manual threshold configuration.
## Key Features
- 10-second installation with single line of code
- Zero-configuration codebase mapping
- Function-level runtime data collection
- Deep forensic context capture for production issues
- No data sampling - captures all events
- Automatic code issue detection and categorization
- Integration with AI coding agents
- Real-time alerts with root cause identification
- Auto-generated fixes with impact analysis

## Use Cases
- Automatically detecting performance regressions in new deployments with specific code paths
- Detecting endpoint error increases in canary deployments with root cause analysis
- Catching extreme performance spikes with execution details and parameters
- Detecting newly introduced exception types with affected functions and deployment correlation

## Who It Is For
- Engineering teams using code-generating AI agents
- Teams using GitHub Copilot, Cursor, or Windsurf
- Organizations needing to validate AI-generated code safety
- Companies requiring production code monitoring for AI agents

## Pros
- Purpose-built for AI coding agents, unlike traditional observability tools designed for human analysis
- Installs in seconds with no configuration or maintenance required
- Captures all events without sampling, ensuring no critical issues are missed
- Provides deep forensic context ready for AI consumption, enabling automatic safe fix generation

## Cons
- Limited to being a new platform compared to established observability solutions with broader feature sets
- Requires integration with specific AI coding agents (Copilot, Cursor, Windsurf) to deliver full value

## Pricing Plans
- Free: Free
- Basic: $100/month
- Pro: $500/month

## Alternatives
- [Bloop AI](https://aigregator.com/tools/bloop-ai)
- [GitHub Copilot](https://aigregator.com/tools/github-copilot)
- [Amazon Q Developer](https://aigregator.com/tools/amazon-codewhisperer)
- Datadog
- New Relic

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Source: Aigregator — AI tools directory. https://aigregator.com/tools/hud