AI Predictions for 2026: A DevOps Engineer's Guide

Engin Diri Engin Diri
AI Predictions for 2026: A DevOps Engineer's Guide

The IDE is dying, and so is tool calling. OpenAI is not going to win. And next year, you’re going to be shipping code that you’ve never reviewed before, even as an experienced engineer.

These are bold claims, but the way we use AI in 2026 for coding and agents is going to look completely different. In this post, I want to cover my predictions and why they matter right now for DevOps engineers. Some of these are definitely hot takes, but that’s what makes this conversation worth having.

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The Superintelligence Flywheel: Infrastructure for the AI Era

Joe Duffy Joe Duffy
The Superintelligence Flywheel: Infrastructure for the AI Era

We’ve been in the infrastructure business for nearly a decade, and we’ve never been more excited about, or in awe of, the scale we are seeing as the industry pursues superintelligence. We are now hitting a tipping point that requires entirely different approaches to managing and scaling infrastructure in this new era.

What do we mean by superintelligence? Superintelligence means AI systems that operate with genuine autonomy—planning, reasoning, executing, adapting—at scale, on the path toward human-level and eventually superhuman intelligence. The infrastructure needed to accomplish this is greater than anything we’ve ever seen. Jensen Huang projects $600 billion in AI infrastructure spending this year, scaling to $3-4 trillion by decade’s end. Stargate committed $500 billion to AI infrastructure in the U.S. Microsoft, Meta, and Google are each spending $70-90 billion annually on datacenters. AWS just activated Project Rainier, a data center scaling to one million custom Trainium chips for Anthropic’s frontier models.

Superintelligence is driving the biggest, fastest infrastructure scaling period in the history of computing. This is exciting but comes with challenges: all of that infrastructure has to be managed, secured, scaled, made compliant, and cost effective. Legacy infrastructure tools weren’t built for this reality—they add friction that slows progress or breaks it altogether.

This reveals an important insight:

The infrastructure required to build superintelligence demands superintelligence for infrastructure.

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AWS built an integrated AI Agent training pipeline and they want you to rent it

Adam Gordon Bell Adam Gordon Bell
AWS built an integrated AI Agent training pipeline and they want you to rent it

AWS re:Invent 2025 delivered myriad of announcements across AI, silicon, and cloud infrastructure. AWS unveiled the expanded Nova model family, introduced Nova Forge for custom model training, launched Trainium3 UltraServers, and added major production features to AgentCore. It was a lot and taken at face value, it looks like another scattershot year of big releases.

But if you look past the firehose, a pattern emerges. These announcements fit together into a single bet about how enterprise AI will be built.

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Encode What You Know With Neo: Custom Instructions and Slash Commands

Pulumi Neo Team Pulumi Neo Team
Encode What You Know With Neo: Custom Instructions and Slash Commands

Every organization builds up knowledge over time: naming standards, compliance requirements, patterns your team has settled on, and proven approaches to common tasks. Until now, bringing this knowledge into Neo meant repeating it manually each time - specifying preferences, describing how your team works, and recreating prompts that someone already perfected.

Two new features change this. Custom Instructions teach Neo your standards so it applies them automatically. Slash Commands capture proven prompts so anyone on your team can use them with a keystroke.

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New in Pulumi IaC: `replaceWith` Resource Option

Tom Harding Tom Harding
New in Pulumi IaC: `replaceWith` Resource Option

The magic of Pulumi is that we rarely have to worry about the fine details of how our deployment and infrastructure management works, allowing us to focus instead on what we want. If our program declares an S3 bucket, Pulumi handles creation, updates, and deletion automatically.

Most of the time, this is exactly what we want. However, some use cases require finer-grained control over resource dependencies. Today, we’re introducing the replaceWith resource option, a new feature that gives you explicit control over replacement dependencies between resources.

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Feature Flagging for Your Infrastructure

Elisabeth Lichtie Elisabeth Lichtie
Feature Flagging for Your Infrastructure

One of Pulumi’s foundational benefits is that it allows you to manage your infrastructure as software with rich programming languages, robust testing, and CI/CD patterns that you’d use with your application code. This post will cover applying another classic software development technique to your infrastructure: feature flagging. You can use feature flags to control change rollout, reduce the risk of new releases, and speed up the development of your infrastructure, the same way you do with your applications.

The examples in this post range from simply creating a flag and using it in a Lambda function to fully integrating with LaunchDarkly to build a comprehensive flagging system for your infrastructure.

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Introducing ESC Connect: Integrate Any Secret Source with Pulumi ESC

Claire Gaestel Claire Gaestel
Introducing ESC Connect: Integrate Any Secret Source with Pulumi ESC

We’re excited to announce ESC Connect — a new capability that lets you integrate any secret source with Pulumi ESC by building simple HTTPS adapter services. If you’ve ever needed to pull secrets from a proprietary system, a legacy tool, or a third-party service that doesn’t have native ESC support, you no longer have to wait for us to build a provider. You can build your own adapter in an afternoon and start using it immediately.

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Pulumi Kubernetes Operator v2.3.0: Preview Mode and Structured Configuration

Eron Wright Eron Wright
Pulumi Kubernetes Operator v2.3.0: Preview Mode and Structured Configuration

We’re excited to announce the release of Pulumi Kubernetes Operator v2.3.0, introducing two powerful capabilities that enhance GitOps workflows: preview mode for validating infrastructure changes before deployment, and structured configuration support for managing complex data types. Building on the success of the v2.0 GA release, this update addresses long-standing community requests while maintaining full backwards compatibility. These features enable safer, more sophisticated infrastructure management patterns for platform engineering teams.

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