AI code assistants and autonomous agents aren’t “helping” developers anymore – they’re actively generating, modifying and committing code inside your workflow. Code isn’t written line by line. It’s assembled from prompts, context, dependencies and agent-driven actions. For DevOps, Platform Engineering and DevEx leaders, that changes everything and raises many new questions: * How do you

In regulated environments, speed and oversight are often treated as tradeoffs. They don’t have to be. In this roundtable industry leaders discuss how automation, policy-as-code, and AI are helping teams shift compliance from a periodic scramble to a continuous, system-level capability. We’ll explore how modern approaches reduce friction for developers, improve real-time risk visibility, and

Join us to discover how a simple yet powerful GenAI‑driven workflow can give you real‑time awareness into the Terraform resources being deployed across your cloud environments. You’ll learn how to build agentic workflows that let generative AI analyze your infrastructure, apply custom logic, and deliver contextual, actionable insights right when you need them.

Organizations are investing heavily in AI, hoping to transform developer productivity into tangible organizational outcomes. But how is this investment delivering returns in practice, and what does it mean for the people building the software? The AI Pulse report examines what is actually happening as AI tools are integrated into the development workflow, revealing a

Unlock a repeatable, end‑to‑end workflow for running scalable, reliable agentic AI on AWS. This session shows how HCP Terraform streamlines cloud operations with chained infrastructure stages, built‑in post‑run automations, and powerful features like Stacks, Actions, and Search & Import to bring unmanaged AWS resources under control. You’ll also see how HCP Vault fits seamlessly into

Recent survey evidence from 919 global enterprise technology leaders highlights a clear inflection point in the adoption of agentic AI. While 72% of respondents report active use of AI agents in IT operations and DevOps, and 74% expect budget increases within the next 12 months, large-scale autonomous operations remain limited. Only 23% report enterprise-wide deployment,

Many Application Security strategies stop at the source code, but the INCD’s latest report, “Breaking the Chain: How Supply Chain Attacks Target Package Managers,” validates that the most significant risks now lie in the components you import, not the ones you create. Attackers are aggressively targeting the gap between code creation and deployment. Specifically within

CI/CD is undergoing its biggest transformation since containers. AI is becoming a participant in every stage of the pipeline, and increasingly, in the developer workflow surrounding it. It’s expanding beyond build-test-deploy to play a foundational role across the entire software creation lifecycle. In this session, we’ll walk through three layers of this evolving, AI-powered CI/CD:

CI/CD is undergoing its biggest transformation since containers. AI is becoming a participant in every stage of the pipeline, and increasingly, in the developer workflow surrounding it. It’s expanding beyond build-test-deploy to play a foundational role across the entire software creation lifecycle. In this session, we’ll walk through three layers of this evolving, AI-powered CI/CD:

AI coding tools are helping teams produce more features faster, but they are also multiplying what happens after the code is written: more changes to test, more rollout decisions to make and more release risk to manage. Harness’s core thesis is that change is the atomic unit of risk, and as AI increases code volume,