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AI Dev Tools: What 100K Engineers at Google Really Taught Us

AI developer productivity, agentic workflows, and the lessons learned running engineering tools for 100,000+ software engineers at Google. John Montgomery, CCO at GitKraken, sits down with Asim Hussain, co-founder of Alterion AI and former Google VP of Engineering Productivity, to get real about what AI actually changes for engineering teams in 2025.

The New Compliance Crisis: AI Is Outrunning Its Controls

Enterprises have spent decades refining compliance frameworks around workflows that were linear, predictable, and well-documented. These frameworks were built for systems that executed actions deterministically and for human operators who made decisions slowly enough for oversight to keep up. In that environment, compliance could function as a retrospective discipline because the evidence required to validate behavior generally existed in complete, stable form.

Cracking the AI Detector Code: How to Keep Your Writing Authentic, Human, and Undetectable

Let's be completely real for a moment: artificial intelligence has completely transformed the way we write. Whether you are drafting a comprehensive research paper, putting together a weekly newsletter, or scaling a blog to reach thousands of readers, tools like ChatGPT and Claude have become the ultimate brainstorming sidekicks. They are fast, incredibly smart, and always ready to pull a structured outline out of thin air.

Building Automated Document-to-Video Workflows for Enterprise Operations

In enterprise environments, the volume of documentation is staggering. An average Fortune 500 company maintains hundreds of thousands of documents across HR policies, engineering specifications, sales playbooks, compliance guidelines, and customer support knowledge bases. This content represents a massive investment in institutional knowledge, but its impact is limited by a persistent delivery problem: people do not read documents.

Commercial Trucking Technology for Better Driver Awareness

Modern highways demand constant focus from professional drivers. New tools help fleets stay safe on long trips across the country. Fleet operators can monitor road hazards much better than in past decades. New onboard systems protect both the driver and the cargo from unexpected road events. High highway speeds mean split-second decisions dictate safety margins. Stay aware of your surroundings to prevent severe accidents before they happen. New updates give teams better visibility than ever. Drivers feel more secure when they have technology backing them up on dark roads.

Anatomy of the AI Software Factory: The Context Layer

This is Part 2 of the AI Software Factory series. In Part 1, we established that the Agile methodology is buckling under the weight of “elastic code.” When AI agents can generate functionality in seconds, two-week sprints and manual task management become organizational bottlenecks. We introduced the concept of the AI Software Factory: a shift from managing human tasks to managing business intent through a “Funnel of Increasing Trust.” But a factory requires infrastructure.

AI Productivity Metrics Dashboard for Engineering Managers (2026)

Measuring AI’s impact on your engineering team is harder than it sounds. Headlines claim AI writes 30% of code and doubles productivity, but those numbers rarely match what you see on the ground. Without a dedicated dashboard that blends leading indicators, anti-gaming safeguards, and ROI reporting, you cannot answer the question that matters most: is AI helping your team ship better software faster?

Get Lightrun AI Skills: Expert Workflows for AI Agents

Today we’re launching Lightrun AI Skills, structured, repeatable investigation workflows built for AI coding agents. With Lightrun MCP, agents like Claude Code, Codex, and Cursor can already instrument live production services and reason over live runtime evidence without a redeployment. But AI agents remain non-deterministic by design, using the same tool differently every session.

What Vera Rubin means for AI infrastructure in 2027

Every so often, NVIDIA releases something that quietly changes the direction of the industry. CUDA did it. DGX did it. NVLink did it. Vera Rubin feels like one of those moments again. At first glance, Rubin looks like the natural successor to Blackwell. Faster GPUs, larger memory pools, and eye watering performance numbers. But the more you dig into the architecture, the clearer it becomes that NVIDIA is not simply shipping another accelerator generation.