Posts Tagged ai

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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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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In 2026, several trends will dominate cloud computing, driving innovation, efficiency, and scalability. From Infrastructure as Code (IaC) to AI/ML, platform engineering to multi-cloud and hybrid strategies, and security practices, let’s explore the 10 biggest emerging trends.

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The era of AI-accelerated development has created a paradox: the faster developers move, the bigger the governance challenge becomes. For years, security and platform teams have worked to “shift left,” but the tools available have been incomplete. Most focus on detection, which is necessary but not sufficient. They identify thousands of policy violations across an organization’s infrastructure but leave teams with an overwhelming backlog and no scalable way to remediate it. This creates a persistent gap between finding a problem and fixing it. The result is an impossible choice between development velocity and organizational control, forcing leadership to slow down innovation to manage risk.

Today, we end that compromise.

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Ask a generic LLM to “fix my broken deployment,” and you’ll get generic advice. Ask Pulumi Neo the same question, and you’ll get a fix plan grounded in your actual infrastructure state.

The difference isn’t about better prompts or newer models. It’s about what the AI actually knows. Generic LLMs have been trained on the internet. Neo has been trained on your infrastructure.

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Neo just got significantly more capable. We’ve shipped three major updates: Operating Modes for flexible control, full ecosystem tool access, and Claude Sonnet 4.5 for better performance on complex infrastructure tasks.

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We’re excited to announce the Pulumi Remote MCP Server—a hosted service that brings AI-powered infrastructure management to any AI assistant that supports the Model Context Protocol. Connect your favorite AI assistant to https://mcp.ai.pulumi.com/mcp and instantly access your Pulumi Cloud infrastructure, search resources across stacks, and delegate complex automation tasks to Pulumi Neo.

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Since launching Pulumi Neo two weeks ago, we’ve seen platform teams discover creative ways to put their newest AI teammate to work. We have also been using Neo internally for a handful of use cases. Neo shifts the conversation from “what could AI do for infrastructure?” to “what can I actually accomplish with Neo today?”

The answer is quite a bit. Here are 10 concrete workflows that platform teams can use Neo for right now, each one designed to save hours of manual work while keeping humans in the driver seat.

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Pulumi’s Infrastructure as Code has included a powerful policy engine from day one. Over the past year, we’ve been enhancing it significantly to provide stronger governance for modern cloud platforms. Until now, these capabilities were limited to our Business Critical tier. Today, we’re excited to announce that policy guardrails are now available to all Team and Enterprise customers. Alongside this, we’re launching a redesigned policy management experience and introducing out-of-the-box policy packs that make it easier than ever to secure, govern, and optimize your cloud environments—even when powered by AI agents like Pulumi Neo.

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AI coding assistants have transformed the speed at which developers can write and deploy code. Pull request velocity has increased significantly. Feature delivery has accelerated beyond what we thought possible just two years ago. This should be a victory for everyone in the software organization.

Instead, it’s created significant challenges for infrastructure and platform teams.

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