Developer productivity is top of mind for all engineering organizations. As AI accelerates software development, leaders face a fundamental question: Are we truly building faster, or just building more? And more importantly, are we building the right things, and building them well? In this new era, speed alone isn’t enough. High-impact teams must ensure their work aligns with customer value and is delivered with exceptional quality.
In a recent episode of the Enginears podcast, Anish Dhar, co-founder and CEO of Cortex, joined the conversation to challenge assumptions about AI, microservices, and the metrics that matter.
The Productivity Paradox: AI’s Promise and Its Pitfalls
Tools like Claude Code, GitHub Copilot, and Cursor are reshaping how developers work. But speed comes with strings attached. Anish points out:
“You might be spending $10M on Copilot licenses, but are you seeing $10M in ROI? That’s the hard question.”
While AI can supercharge early-stage prototyping or frontend work, deploying AI-generated code into production introduces risk: lower reliability, loss of code context, and mounting technical debt. Without observability and ownership, AI's benefits can quickly unravel.
Beyond DORA: Measuring What Actually Moves the Needle
Classic frameworks like DORA or SPACE offer high-level signals, but they don’t translate directly into day-to-day decisions. Developers don’t engage with charts. They respond to clear goals and actionable inputs.
Cortex helps bridge this gap by:
Diagnosing performance issues at their root (e.g., slow deploys due to unmet production-readiness standards).
Surfacing ownership gaps and weak onboarding as contributors to reliability issues.
Connecting business outcomes to engineering behavior, not just activity.
For more on this topic, check out our blog: Why Measuring Both Inputs and Outputs is Critical for Engineering Excellence
Developer Experience as a Business Driver
Developer experience isn’t just about joy, it’s about having a real impact on business. Today’s high-performing teams optimize for:
Faster onboarding → Reduced time-to-first PR.
Clear ownership and observability → Lower MTTR.
Built-in reliability and security → Fewer fire drills.
As Anish puts it:
“Developer happiness still matters, but also must serve engineering excellence that supports company goals.”
Engineering Intelligence: The Next Evolution
Cortex is doubling down on engineering intelligence - tools and insights that don’t just report on activity but shape behavior.
Rather than static dashboards, the next wave of tools will:
Help developers understand why a metric matters
Recommend actionable steps to improve
Embed excellence into team culture via feedback loops
Anish on how data can inform decision making: “We’re sitting on a mountain of data about what makes high-performing teams. The next step is using that to guide and influence engineering leaders.”
If you’d like to learn more about how Cortex is approaching engineering intelligence, check out our newest updates to Engineering Intelligence.
Building the “Single Pane of Glass”
Cortex isn’t just a dashboard. It’s the connective layer between your engineering tools, creating a living map of your org’s software systems. Through:
Service Catalogs: visualizing ownership, dependencies, and health
Scorecards: enforcing standards like production readiness at scale
Initiatives: assigning owners and due dates to ensure and track meaningful progress against any project
It’s used by platform teams, developers, SREs, and execs alike because everyone benefits when complexity is made visible and manageable.
Explore Cortex and Join Us at IDPCON
Curious about what engineering excellence really looks like in the age of AI?Join us at IDPCON this October in NYC, where leading orgs will share how they’re transforming developer productivity with internal developer portals like Cortex.
→ Or book a demo with our team to see Cortex in action.
