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By Cortex
Summary Spotify Backstage is a free, open-source framework for building internal developer portals, with a software catalog, templates, TechDocs, and a large plugin ecosystem. It’s a strong fit if you have a dedicated platform team that wants to build and run its own portal. If you want a current catalog, enforced standards, and org-level reporting without maintaining the infrastructure, a managed platform like Cortex is the better fit.
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By Anish Dhar
Scroll LinkedIn for ten minutes and you'd think every engineering organization already runs an autonomous SDLC, with agents writing, reviewing, and shipping code while humans watch. Inside large enterprises, the picture looks different. Coding agents there have to work around sensitive customer data, recurring compliance audits, a larger attack surface, downtime that costs millions, and a CFO who wants to know what last year's token spend bought.
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By Roshni Sondhi
Last week we hosted our annual conference, EVOLVE, where global engineering leaders came to talk through the realities of building AI-native SDLCs. When asked to name the biggest friction point in their software lifecycle, attendees gave telling answers: ‘reviewing changes’ took 36 percent, ‘measuring impact’ took 35, and ‘building’ drew zero votes.
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By Ganesh Datta
Engineering organizations spent the past decade learning to measure developer and team productivity. Measurement of the organization itself did not keep pace. Now that agents are responsible for writing most of the code across many engineering organizations, it’s more important than ever to have an effective methodology for measuring productivity.
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By Ganesh Datta
When Nicole Forsgren, Margaret-Anne Storey, and their coauthors published "The SPACE of Developer Productivity" in 2021, they settled an argument the industry had been losing for years. Productivity is not one number, and it is not a proxy like commits or story points. It is multidimensional, and any attempt to flatten it into a single metric will mislead you. Most of what came after in developer productivity measurement builds on SPACE. SPACE and DRIVE were built for different jobs.
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By Cristina Buenahora
Traditional code review no longer keeps pace with how much code teams are shipping. Risk-based code review is the response: instead of giving every pull request the same scrutiny, you route human attention by risk, letting low-risk changes ship with light or automated review and reserving deep human review for the changes that are expensive to get wrong.
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By Cortex
Most engineering leaders are drowning in data but starved for insight. We have dashboards full of metrics, but they often create more questions than answers and rarely tell us what to do next. In the age of AI, where development velocity is accelerating at an unprecedented rate, this problem is only getting worse. Shipping code faster than you can fix it is an existential risk, and a dashboard that doesn't lead to action is just a distraction.
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By Ganesh Datta
This is the fifth and final post in the DRIVE Deep Dive series, following Delivery, Reliability, Initiatives, and Vigilance. For the complete model across all five pillars, download the full DRIVE framework. -- Engineering money and time land in three places a leadership review can actually act on: the cloud bill, the internal spend on AI and LLM tokens, and the split between building new things and keeping old ones running.
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By Ganesh Datta
This is the fourth post in our DRIVE Deep Dive series. Over the coming weeks we're examining each pillar of the DRIVE framework in turn. For the complete model, download the full DRIVE framework. Our last post covered Initiatives. Up next: Efficiency. The bottleneck on writing code is gone, and the industry is responding the way it always does when a constraint disappears: by producing more.
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By Ganesh Datta
This is the third post in our DRIVE Deep Dive series. We've covered Delivery and Reliability so far; this post takes on Initiatives. For the complete model, download the full DRIVE framework.
AI can write 1,100 lines of code for a loading spinner in five minutes. Your change board still meets once a week. Karthik Jayaraman, VP of Information Technology at Fiserv, explains what happens when code generation speeds up and everything downstream stays the same. He covers why "human in the loop" doesn't scale, why handing all review to AI backfires, and why an agent told not to touch production needs a boundary it can't cross, not just an instruction.
DORA's data shows that as AI adoption goes up, individual effectiveness rises, and so does software delivery instability: more rollbacks and more unplanned rework. Nathen Harvey of Google's DORA team explains why AI acts as an amplifier of whatever system you already have. He walks through the seven capabilities that separate teams getting real gains from teams drowning in downstream chaos. He also argues that the risks stopping you from shipping AI-built work should become your platform roadmap.
Everyone online seems to have a fully autonomous SDLC. Most enterprises are still at level 3, and they'll be there for years. In the EVOLVE 2026 opening keynote, Cortex co-founders Anish Dhar (CEO) and Ganesh Datta (CTO) lay out a practical maturity model for getting from AI coding agents to an AI software factory without blowing up cost, quality, or security along the way. They've watched hundreds of engineering orgs adopt AI over the last two years. This talk distills what separated the successful rollouts from the chaotic ones.
Small agent changes mean a small test scope. The agent knows exactly what it changed, so it can pull the 50 tests that matter out of a 10,000-test inventory and skip the rest. Arjun Iyer on why that's the validation model that scales.
Ganesh Datta on why every team still has a finite budget, now it's tokens instead of headcount. $500 to spend: ship the feature or fix the P2? The orgs building a framework for that call now will have it a lot easier when the CFO puts a cap on spend. From Braintrust by Cortex. Full episode out next Thursday.
Give a model permission to act on your computer and you're trusting it will behave the way you expect. It might not. In this clip from our Braintrust conversation, Adam Berman, engineering leader at Semgrep, breaks down why a backdoored model is a different threat model than backdoored software. You can't fuzz-test your way to finding it, and you often can't detect it until it's already acting the way it shouldn't.
Solution Architect Jeff Schnitter walks through arrays of primitives in Workflow User Inputs, turning an object you have to transform into an array you can pass straight through. What it does.
Adam Berman, VP of Engineering at Semgrep, on the double edge of AI tools for engineering leaders: they compress the distance between an idea and a working prototype, letting him get from exploration to a demoable POC in the gaps between meetings. But that same leverage amplifies risk. One person can spin up 1,000 unowned problems just as fast as they can spin up 1,000 wins. From a Braintrust by Cortex conversation on how AI is changing the job of engineering leadership.
This week's Feature Friday: Principal Product Manager Christine Byun walks through KPI cards, a new way to build custom dashboards in Engineering Intelligence. KPI cards pull key metrics, like change failure rate and rollback frequency, into compact tiles so they stay visible without taking up chart space. That means the metric you're actively working, incidents, in this demo, gets full-size room, without losing sight of the rest of your system.
Cortex co-founder and CTO Ganesh Datta sits down with Steve Flanders, who leads AI transformation at Splunk and wrote the book on OpenTelemetry, to talk about why AI acceleration without strong observability foundations creates more problems than it solves.
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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.