Artificial intelligence has dramatically accelerated how software is written, enabling engineering teams to generate and ship code at unprecedented speed. But while code creation has evolved rapidly, understanding how that code performs in production remains a persistent challenge. As organizations increasingly rely on AI-assisted development, a new focus is emerging around providing coding agents with the runtime context needed to produce reliable software.
Against this backdrop, Hud has appointed Shai Alani as Vice President of Marketing, a move that reflects the company’s ambition to expand awareness of what it describes as the next major category in AI-native software development: Runtime Intelligence.
The Growing Need for Production Reality
AI coding tools have transformed software development by helping engineers generate code more quickly. However, when applications encounter issues in production, speed alone is no longer enough.
Traditional observability platforms can alert teams that something has gone wrong, but identifying the underlying cause often requires piecing together information from logs and multiple data sources. According to Hud, this process becomes even more challenging for AI coding agents, which can understand source code but lack visibility into how that code actually behaved under live production conditions.
Rather than relying solely on logs, the company positions Runtime Intelligence as a way to provide production behavior at the function level, allowing both engineers and AI systems to understand failures, identify root causes, validate fixes, and deploy changes 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.”
Building a Category Around Runtime Intelligence
Alani joins Hud with experience leading marketing organizations at several B2B technology companies. Before joining Hud, he served as VP Marketing at Lightrun and previously held marketing leadership positions at Coralogix and Aporia.
In his new position, he will oversee the company’s global marketing strategy, category creation, brand development, and demand generation as Hud expands its presence within the AI software development ecosystem.
The appointment comes as engineering organizations continue adopting AI-assisted development workflows while seeking better ways to understand application behavior after deployment. Hud’s strategy centers on positioning Runtime Intelligence as a foundational layer that complements AI-generated software by supplying production evidence that coding agents cannot derive from source code alone.
“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.”
Bringing Runtime Evidence Into AI Development
Hud’s platform is designed to bridge the gap between software creation and production behavior. Its runtime code sensor operates alongside every function in production, capturing forensic context whenever issues occur. The platform converts live production behavior into function-level evidence intended to help engineering teams and coding agents determine what happened, identify the precise root cause, and validate fixes before deployment.
As AI becomes more deeply embedded in software engineering workflows, access to runtime evidence may become increasingly important for organizations looking to move beyond faster code generation toward greater confidence in production reliability.
Hud says its technology is already deployed across millions of production services, with engineering teams at Monday.com, Lemonade, Axonius, Cyera, and other organizations using the platform. Backed by $21 million in funding led by Aleph and SquarePeg, the company is focused on helping engineering teams shorten investigation times, merge code with greater confidence, and incorporate production reality into the AI development lifecycle.
With Alani now leading marketing efforts, Hud is positioning itself to define Runtime Intelligence as organizations continue adapting software development practices for the AI coding era.
