Lightrun Secures $70M to Transform Production Debugging with AI
What This Means for the Future of Developer Experience
AI-based coding has exploded in popularity on the promise that it will make developers’ jobs faster and easier. But there's a flip side: more code means more bugs, and debugging in production has become a major challenge—one that traditional tools just weren’t built for.
This week, Lightrun, an Israeli startup tackling this exact pain point, announced a $70 million Series B funding roundto scale its AI-powered observability platform.
As a product person and tech enthusiast, I think this is a defining moment for developer experience—and here’s why.
In today's bytes;
Lightrun Secures $70M to Transform Production Debugging with AI
ChatGPT trying to fix the bug that led by minor erotic chat result
ChatGPT launch a shopping feature user can shop with the chat
Alibaba drops open-weight Qwen3 AI with advanced reasoning, multilingual support, and full open-source accessibility
What is Lightrun?
Lightrun is a developer-first observability and debugging platform that allows engineers to add logs, metrics, and traces to live, running production applications—without restarts or redeployments. It’s like a time machine for developers: you can inspect and debug without ever disturbing your live environment.
Now, with AI layered on top, Lightrun goes beyond reactive debugging. It can proactively suggest log placements, generate contextual insights, and even simulate runtime behaviours to prevent crashes before they happen.
Why the $70M Round?
This Series B was co-led by Accel and Insight Partners, with participation from Citi, Glilot Capital, Sorenson Capital, and GTM Capital. Lightrun has now raised a total of $110M to date.
The raise highlights not just the scale of the opportunity, but also Lightrun’s growing list of enterprise clients, including:
Microsoft
Salesforce
SAP
AT&T
ADP
NYSE/ICE
Inditex
And strategic backer Citi
Their recent product launch—the Runtime Autonomous AI Debugger—directly addresses the pain many enterprises face today: a deluge of AI-generated code, and a rising tide of unpredictable bugs.
How Lightrun Stands Out
Unlike general observability tools, Lightrun is focused on code-level debugging in live environments, using AI to automate diagnosis and remediation.
“Code is becoming cheap, but bugs are expensive.” – Ilan Peleg, CEO of Lightrun
Their edge? Real-time debugging directly in the IDE. No guesswork, no staging-only instrumentation—just immediate, in-context feedback, powered by simulations and smart recommendations.
Why This Matters
As "vibe coding" (fast, informal, AI-assisted development) becomes the norm, bugs in production are inevitable. What’s changing is how we respond.
Lightrun is part of a new category of tools I call AI-native observability—platforms that don’t just watch and alert, but understand, predict, and fix.
Expect to see:
AI copilots not just for code writing, but for runtime ops
Natural language descriptions of production failures
Simulated runtime environments within IDEs
A tighter loop between creation, observation, and remediation
Looking Ahead
If GitHub Copilot changed how we write code, tools like Lightrun will redefine how we trust and maintain that code. Especially in enterprise environments where uptime and reliability are non-negotiable.
Lightrun isn’t just another observability tool. It’s a signal that developer platforms are evolving—fast—to meet the age of AI.
“Everything that poses risk to resilience, we are mitigating.” – Ilan Peleg
I’ll be keeping a close eye on this space, and if you’re a builder, CTO, or DevOps leader, I think you should too.
AI Tools
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Voicify: Instantly clone and generate custom AI voices.
Beautiful.ai: Create stunning AI-powered presentations fast.
Ocoya: AI tool for creating, scheduling, and managing social media posts.
Magical: AI to automate repetitive typing tasks.
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