Cortex co-founder and CTO Ganesh Datta sits down with Arjun Iyer, CEO and co-founder of Signadot. Arjun explains why validating code before it merges has become essential now that coding agents are producing far more changes than teams can review by hand.

Arjun and Ganesh chat about why a merge should be treated as a contract, how agents can pick and run only the tests that matter for each change, and why the PR is replacing the developer as the unit engineering organizations need to govern. They also discuss where humans still belong in an agentic SDLC, from deciding what to build to staying accountable for what ships.

Cortex co-founder and CTO Ganesh Datta sits down with Naveen Puvvula, who recently left a director role at Life360 to become a senior principal engineer at construction tech startup Planera, to talk about what it takes to align both humans and AI agents around outcomes instead of activity.

Naveen and Ganesh discuss why architecture and product judgment remain squarely human tasks even as agents get better at execution, how organizational bottlenecks rather than raw compute determine whether AI investment pays off, and why engineering specialization is likely to stratify the way manufacturing did with the rise of factory technicians. They also get into the trust gap AI still needs to close in regulated, high-stakes industries, and why unlimited token budgets are reviving the same tech debt trade-offs teams used to make with headcount.

Cortex co-founder and CTO Ganesh Datta sits down with Adam Berman, who recently stepped back from VP of Engineering into an individual contributor role at Semgrep, the application security company built on static analysis. Adam and Ganesh dig into how AI coding agents are reshaping both engineering leadership and application security.

Adam shares why he traded running Semgrep's engineering org for hands-on building again, and how AI has changed the math for leaders who want to stay close to the code. He and Ganesh talk through why static analysis is having a resurgence as a cheap, fast guardrail for agents, how security review is shifting from CI into the IDE and even into the design phase, and how agents are getting unnervingly good at chaining together minor vulnerabilities into critical exploits. They close on how much to trust agents with fixing their own security issues, and what it actually takes to go "full dark factory" safely.

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.

Steve and Ganesh dig into how AI-generated code moves bottlenecks downstream to code review and production failures. They also cover why badly correlated telemetry makes AI-powered observability useless, how OpenTelemetry provides the semantic conventions needed to fix that, and why the path to shipping faster with AI runs through better data hygiene, not around it.

Cortex co-founder and CTO Ganesh Datta sits down with Abby Bangser, a platform engineering leader at Syntasso and former lead of the CNCF Platforms Working Group, to talk about why AI agents need real platform APIs, not raw cloud credentials.

Abby and Ganesh dig into what business requirements actually look like when encoded into a platform, from compliance and labeling to disaster recovery and regional decisions. They talk through why markdown "skill" documents are no substitute for real APIs and deterministic tools that enforce constraints by design. Abby introduces the Etsy analogy: platform teams are like the engineering org at Etsy, responsible for building the marketplace itself rather than knitting the sweaters. And she makes the case against distributing IaC templates to end users, arguing that an API layer separating producers from consumers is what lets a platform evolve without breaking everything downstream.

Cortex co-founder and CTO Ganesh Datta sits down with Dr. Martin Nettling, Senior Director of Engineering and Head of QA at Tealium, to explore the distinction between trusting people and having confidence in tools, and why that difference matters as AI becomes part of every engineering workflow.

Martin and Ganesh discuss the augmented author model, where engineers take full responsibility for AI-generated outputs rather than treating the tool as the author. They get into what breaks when AI writes your Jira tickets or pull requests without a human validating the thinking, why the ability to trace any decision from organizational strategy to production logs is a chain teams can't let break, and how organizations can build genuine confidence in automation without automating away the exercises that actually make teams learn.

Cortex co-founder and CTO Ganesh Datta talks with Aleks Rudzitis, Principal Engineer at AWS, about how the structure and theater of ops reviews can turn reliability into a shared organizational value.

Aleks explains how error budgets make reliability standards concrete rather than aspirational, why async reports can't replace the psychological weight of a live meeting with leadership, and how AI has made it feasible to backfill tests and even formal verification proofs that were previously too labor-intensive to justify. He also shares what it takes to get an ops review program off the ground in organizations that don't already have the habit.

Cortex co-founder and CTO Ganesh Datta sits down with Shawn Burke, Distinguished Engineer at Cortex, to explore what separates an operational excellence review that drives real engineering behavior from one that produces great conversation and nothing else. Shawn draws on experience from SoFi, Uber, and Microsoft to explain why these reviews so often fail—and how to build a process that actually sticks.

Shawn and Ganesh walk through why senior leadership presence is non-negotiable for the process to matter, and why fully automated reporting is the difference between a meeting that sustains and one that dies. They cover golden signals, SLOs, and how error budgets help teams balance feature work against reliability investment. They also discuss how AI coding assistants are introducing new operational risks around code review quality and flaky tests, and why AI agents may eventually act as a chief of staff—surfacing the why behind the metrics so teams can act on patterns instead of just observing them.