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By Cortex
The Monday morning thread. Someone asks who owns checkout-service. Someone else asks what changed in the Production Readiness Scorecard last week. A third person wants to know if the Kubernetes migration is blocking the launch next Thursday. The answers exist. They live in Cortex. But getting them into the thread means someone stops what they're doing, opens a tab, finds the data, and pastes it back. By the time they do, the conversation has moved on.
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By Cristina Buenahora
Most engineers can tell you exactly how many PRs they merged last quarter. Far fewer can tell you what any of it did for the business. The best engineering leaders can. They draw a straight line from their team's work to ARR: which reliability investment protected revenue, which migration unblocked a strategic customer, which operational improvement reduced churn. They lead with outcomes, not story points.
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By Cortex
Software development has never moved this fast. JetBrains' 2026 AI Pulse Survey found that 90% of developers now use at least one AI tool at work. CircleCI's 2026 State of Software Delivery report, covering 28 million workflows across 22,000 organizations, found that daily CI workflow runs jumped 59% year over year, the largest single increase they've ever recorded. In that same period, CI success rates dropped to a five-year low.
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By Cortex
Most engineering career advice treats the leadership track as a ladder where each step is a slightly bigger version of the one before it. That metaphor is the reason so many career transitions go sideways. IC, manager, director, and VP are four different jobs. Each has its own failure modes, its own definition of what counts as your work, and its own relationship to the code. The skills that earn a promotion to one level are rarely the skills that make someone effective at the next.
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By Cristina Buenahora
Tamar Bercovici has been at Box for 15 years. She leads the core platform, the backend layer that storage, search, metadata, and AI capabilities all run on. When her systems go down, Box goes down. On a recent episode of the Braintrust podcast, she said the debate around AI-generated code tends to focus on whether the models will write clean code and/or introduce bugs. Tamar's focus is somewhere else entirely.
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By Cortex
Every engineering team wants to ship high-quality, reliable software quickly. Historically, engineers used a few guiding principles to help them consistently write clean code: keep code DRY, shift security left, write solid test cases, own your services, document your runbooks, and more.
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By Cortex
Though AI tools have made individual developers dramatically more productive at writing code, most engineering organizations report moving only about 20% faster than before. As Honeycomb CTO Charity Majors recently wrote, "AI came for code generation first because it was the easiest problem to solve, but it was never the thing holding developers back.".
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By Cortex
KubeCon + CloudNativeCon Europe 2026 recently brought the cloud native community to Amsterdam. We were there all week bouncing between the booth, a Braintrust event with engineering leaders from across the community, and more hallway conversations than we can count. One talking point dominated the week: AI is shipping code faster than most engineering orgs can govern it. It also became clear that we weren't the only ones talking about this challenge.
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By Cortex
The best QA engineers are always asking themselves (and others around them) what might break. When engineering teams shifted to agile delivery, that mindset largely moved out of dedicated roles and into the background. Automated testing took over the repetitive work, developers owned quality end-to-end, and velocity improved. What didn't carry over was the habit of looking at a feature and asking how a real user, an edge case, or unexpected load might expose it.
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By Ganesh Datta
Engineering teams are great at innovating and delivering products, but the work that's required to maintain them over time and keep them running well tends to get deprioritized. Planning processes are designed to move features forward, not to catch whether those features are generating too many alerts, degrading in performance, or creating compliance exposure over time. As a result, that class of work accumulates quietly.
Mention @Cortex in any Slack channel the Assistant has been invited to, public or private, and get grounded answers pulled from your Cortex data. Questions can be as simple as "who owns payments-api?" or as analytical as "what's driving our incident trends this quarter?" The Assistant pulls context from all across Cortex, including ownership, Scorecards, Initiatives, on-call, dependencies, and Eng Intelligence metrics, and holds context across a threaded conversation.
Rootly's Dan Sadler: why AI coding tools are driving more incidents + why reliability is the product
Cortex co-founder and CTO Ganesh Datta sits down with Dan Sadler, VP of Engineering at Rootly. Dan explains how Rootly treats reliability as a product feature rather than just a technical metric, and why culture might be the most impactful element of building reliable systems.
Cortex co-founder and CTO Ganesh Datta sits down with Tamar Bercovici, VP of Engineering at Box, who spent 15 years at the company growing from senior IC to leading its core platform organization, to talk about what engineering leadership looks like at each level of the org.
@cortex611 co-founder and CTO Ganesh Datta sits down with Tamar Bercovici, VP of Engineering at Box, who spent 15 years at the company growing from senior IC to leading its core platform organization, to talk about what engineering leadership looks like at each level of the org.
The Cortex AI Assistant in Slack puts your engineering data and analysis right where your team already works. Ask questions in plain language, about your services, deployments, incidents, initiatives, and more, and get real answers without leaving Slack.
Standardize. Visualize. Drive Change. Cortex is the leading Engineering Operations Platform that helps organizations define what "good" looks like and empowers teams to reach those standards. From tracking DORA metrics to driving large-scale migrations, Cortex provides the visibility and tools necessary to maintain a high-performing engineering culture. In this video, you’ll see how to: Set the Standards: Create custom Scorecards (like Operational Maturity or DORA Metrics) with automated rules integrated directly from tools like PagerDuty, Incident.io, and GitHub.
Is your engineering org actually getting better, or just shipping more? In this overview, we dive into how leadership and platform teams use Cortex to move beyond manual audits and spreadsheets. Learn how to transform "tribal knowledge" into a data-driven culture of engineering excellence by centralizing visibility and automating operational standards. Key Highlights: Mission Control: Using the Service Catalog to map dependencies and ownership without the Slack-pinging or Wiki-hunting.
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Cortex makes it easy for engineering organizations to gain visibility into their services and deliver high quality software.
Cortex helps engineering teams build better software at scale:
- Align your team and drive accountability: Scorecards enable teams to drive what matters most to them – including service quality, production readiness standards, and migrations.
- A single source of truth for your services: Cortex’s service catalog integrates with the most popular engineering tools, giving teams an easy way to understand everything about their architecture.
- Build a culture of reliability and high performance: Teams enable organizations to drive a sense of ownership and pride as they improve service quality.
- Ensure new services follow best practices from day one: Scaffolder lets developers scaffold a new service in less than five minutes using custom templates crafted by your team.
Cortex gives organizations visibility into the status and quality of their microservices and helps teams drive adoption of best practices so they can deliver higher quality software.