Hud Names Shai Alani VP of Marketing as Runtime Intelligence Emerges in AI Software Development

The rise of AI coding assistants has changed how software is written, allowing engineering teams to generate and ship code faster than ever before. Yet as development accelerates, another challenge is becoming more visible: understanding what happens after that code reaches production.

While AI can generate applications in minutes, determining why software fails in production remains a far more complex task. The gap between writing code and understanding its real-world behavior has created an opportunity for technologies designed to provide engineering teams with deeper runtime insight.

Hud believes that opportunity represents an entirely new category. The Runtime Intelligence company has appointed Shai Alani as Vice President of Marketing as it looks to expand awareness of the role runtime evidence can play in AI-native software development.

Faster Development Doesn't Eliminate Production Complexity

Modern AI development tools have dramatically shortened the software creation cycle. But when applications experience unexpected behavior, developers often find themselves piecing together logs and telemetry from multiple systems to determine what happened.

According to Hud, this process remains difficult for AI coding agents as well. Although they can analyze source code, they typically lack direct visibility into how that code performed under real production traffic. Without that runtime context, identifying root causes and validating fixes can become an inefficient process.

Hud's platform is designed to address this challenge by capturing function-level production behavior and forensic context whenever issues occur. The company says this allows both human engineers and AI coding agents to understand failures more precisely and deliver safer fixes with greater confidence.

"AI has changed the speed of software creation, but production is still where code proves itself," said Roee Adler, Co-founder and CEO of Hud. "The next major category in the AI SDLC is Runtime Intelligence: production behavior resolved to the function level, coupled with deep forensics when things go wrong, so humans and agents can understand, fix, and validate software with confidence. Shai brings the experience we need to build that category and scale Hud into a defining company for AI-native engineering teams."

Expanding Go-to-Market Efforts

As Vice President of Marketing, Alani will lead Hud's global marketing strategy, brand development, category creation, and demand generation efforts.

He joins the company after serving as VP Marketing at Lightrun and previously holding marketing leadership positions at Coralogix and Aporia. His appointment reflects Hud's focus on introducing Runtime Intelligence to organizations that are increasingly incorporating AI into their software engineering workflows.

For Alani, the industry's rapid adoption of AI has made production visibility a more pressing issue rather than eliminating it.

"Runtime Intelligence is the missing layer in the AI software stack," said Shai Alani, VP Marketing at Hud. "AI has made it easy to generate code, but it has not made it any easier to stand behind that code once it is running in production, where reliability is actually decided. That gap is fast becoming one of the defining problems for AI-native engineering teams, and it is exactly the kind of category you build a company around. That is why I joined Hud, and it is the story I am excited to take to market."

Connecting AI Development With Production Reality

Hud's Runtime Intelligence platform operates by running a runtime code sensor alongside every function in production. When an issue occurs, the platform captures detailed forensic information that can help identify the exact root cause while providing evidence to validate a potential solution before deployment.

The company says this production-level visibility enables engineering teams to resolve incidents more efficiently while giving AI coding agents access to the runtime evidence they need to make more informed decisions.

Hud's technology is already being used across millions of production services by engineering organizations, including Monday.com, Lemonade, Axonius, and Cyera. Backed by $21 million in funding led by Aleph and SquarePeg, the company aims to help engineering teams investigate issues faster, merge code with greater confidence, and incorporate production behavior directly into AI-assisted development.

As AI continues to reshape software engineering, companies are increasingly looking beyond code generation alone. Hud is betting that bringing production intelligence into the development process will become an essential capability for teams building software in the AI era.