TL;DR

Hud says AI generates or assists 42% of shipped code, rising to 65% by 2027. Its new integration with ClickHouse’s ClickStack connects function-level runtime intelligence with infrastructure-wide observability, creating a feedback loop where AI-generated changes are assessed before deployment, verified after release, and automatically investigated or rolled back if behavior deviates. monday.com is an early adopter of the combined stack.

The growing use of AI in software development is changing the bottleneck for engineering teams. Generating code is becoming faster, but reviewing its potential impact, validating releases, and responding to unexpected behavior still require context from production.

Hud says AI now generates or assists with 42% of the code developers ship, and that share is expected to reach 65% by 2027. The company’s new integration with ClickHouse is designed around that shift, bringing runtime information into workflows that assess and manage AI-generated changes.

The integration connects ClickStack, ClickHouse’s open-source observability stack, with Hud’s Runtime Code Sensor. Together, the products are intended to help engineering teams assess changes before deployment, verify them after release, and investigate issues when production behavior changes.

“AI is accelerating how quickly teams can generate code, but safely shipping it with high confidence requires production context,” said May Walter, CTO of Hud. “Hud and ClickHouse bring real production behavior at an unparalleled breadth and depth, so teams can build a production-aware AI SDLC: gating changes before they ship, proactively verifying them once deployed, and fixing issues as they arise – all using real runtime truth. Together with ClickHouse, we are bringing that intelligence across the entire AI SDLC.”

A Broader View of What Happens in Production

The integration combines two distinct perspectives on application behavior. ClickStack provides visibility across applications and infrastructure, helping teams identify the service, deployment, or endpoint associated with an issue.

Hud works closer to the code, following function-level behavior and connecting production activity to the functions and code changes responsible for it. The platforms can be connected by a coding agent using shared trace IDs, allowing teams to move from an issue in ClickStack to relevant code-level context in Hud.

“Our users already trust ClickHouse to store and query their Open Telemetry data at scale,” said Mike Shi, Head of Observability of ClickHouse. “The shift now underway is from simply watching systems or investigating issues to using that data to make day-to-day engineering decisions. Hud connects observability data to the code and changes behind it, making the entire stack more useful for teams building and shipping software with AI.”

That connection gives production data a role earlier in the engineering process. Instead of relying on runtime information primarily for troubleshooting, teams can use it when deciding how AI-generated changes should move through development and deployment.

Using Runtime Behavior to Guide Releases

The Hud+ClickStack integration supports pre-deployment risk assessment for code changes. Teams can evaluate changes against real-time data on how affected code behaves in production, allowing higher-risk changes to be held for additional review while safer changes can move faster or be automatically merged.

The workflow also extends into deployment. The integration supports release verification, automatic reversion upon regression, automated detection and investigation, and agentic workflows that can create pull requests to address underlying code issues.

This creates a feedback loop around AI-generated changes. A change can be evaluated before it ships, observed after deployment, and investigated or remediated if its behavior differs from expectations.

The companies say that approach can also help address smaller production changes before they become larger problems. A query might slow down, a function could behave unexpectedly under a specific workload, or a code path might consume additional resources.

From Production Issue to Code-Level Fix

Hud is designed to detect these issues at the function level and provide forensic context into their causes. ClickStack contributes the broader operational picture, helping teams understand where the problem is occurring across the application.

“Like every modern engineering organization, a growing share of our code is now written with AI,” said Rom Kadria, Senior Software Engineer, monday.com. “We write code much faster, but the challenge has shifted to shipping just as quickly while maintaining confidence that new code won’t cause harm. ClickHouse gives us the wide operational picture at scale, while Hud gives us the runtime intelligence and next-level introspection needed to evaluate and ship AI-generated code confidently. When issues do arise, combining ClickHouse and Hud allows us to triage and resolve them quickly. For a company building with AI, that combination is the obvious choice.”

The integration supports rollback and remediation workflows alongside automated investigation and code-level fixes. For engineering teams, the goal is to shorten the path between discovering unexpected behavior and understanding the change responsible for it.

Teams can get started by installing the Hud SDK and connecting it to their ClickStack service. Hud’s runtime intelligence then flows alongside the OpenTelemetry data teams already collect.

As AI becomes more deeply embedded in software development, the companies are betting that production data will become an increasingly important part of the development loop. The ClickHouse-Hud integration is designed to make that connection practical, linking AI-generated changes with the behavior of the software once it is running in the real world.