Amidst the noise created by the various hype engines attempting to tell us that DevOps is dead, we know that a) of course it isn’t, but b) there are indeed deeper forces at work that promise to automate a wider transept of the backend management and orchestration element of the software application development lifecycle.

Too honest for a mission statement and too long for a t-shirt slogan, that statement might go some way to explaining StackGen’s efforts to reinvent itself. The company that was once an infrastructure as code (IaC) specialist now wants to be known as an autonomous infrastructure technology purist. Driving this evolution is (spoiler alert, you know the answer already) the proliferation and ubiquity of agentic AI services.

Golden Path Turbo Booster?

The company’s Autonomous Infrastructure Platform features AI agents to build and manage cloud infrastructure with autonomous capabilities. This is not DevOps with agentic golden path turbo boosters; this is a deeper repositioning of DevOps for the agentic age, where AI-native operations handle infrastructure management with an appreciation for organizational intent. 

In other words, it’s DevOps that can dynamically create infrastructure services that align with business needs and application requirements.

“We’re witnessing a DevOps evolution that moves us from ‘you build it, you run it’… to ‘AI builds it, AI runs it’ going forwards,” said Sachin Aggarwal, CEO and co-founder of StackGen, speaking to Techstrong group directly this weekend. “This changes what it means to be a DevOps engineer, i.e., instead of writing configuration files, engineers define business intent and let AI handle implementation. Traditional approaches rely on fixed golden paths, but the future is AI that dynamically understands what your applications and organizational needs.”

Aggarwal claims that StackGen’s autonomous platform represents, validates and delivers this leap. It’s a place – across this latest chasm – where AI doesn’t just follow procedures, it makes reasoning decisions about infrastructure requirements and adapts in real-time. “Within five years, the most successful DevOps teams will be those who can orchestrate AI agents rather than manage infrastructure manually,” he said.

Painful Provisioning Procedures

Keen to illustrate our pre-agentic inefficiencies, StackGen points to surveys that state developers spend around a quarter of their time on infrastructure provisioning instead of building features. Other market analysis suggests that the shift toward AI-managed infrastructure is already underway. Even the naysayers in this space admit that we’re looking at an immediate future where, well before the end of this decade, infrastructure-related tasks will be executed semi-autonomously by AI.

“We’re pioneering a new category while the industry remains anchored to legacy infrastructure flows,” asserted Aggarwal. “When a developer can build a complete application in 30 minutes, but it takes days to deploy and secure it, you have a talent optimization crisis. AI tools now let developers build full-stack apps (think Spotify-style apps with authentication services and streaming capabilities) in 30 minutes. But deploying, securing and managing that infrastructure still takes days of manual DevOps work.”

Aggarwal says that recent incidents like SaaStr’s database deletion by Replit’s AI agent show what happens when we try to accelerate infrastructure operations without proper governance. He is confident that StackGen’s Autonomous Infrastructure Platform bridges this gap with AI agents that can provision, secure and manage infrastructure at the same speed developers create applications.

Futurum Analyst Perspective

“A myriad of infrastructure automation tools and platforms exist, and many (if fewer) tools and platforms enable infrastructure autonomy. Most, if not almost all, of them incorporate IaC or some analogy of IaC as the implementation component of the automation or autonomous operation. But we don’t know of one, until now, that takes IaC generation as its foundation point,” explained Guy Currier, analyst at The Futurum Group.

Currier states that this foundational grounding question is the key point in assessing the relaunch of StackGen as an infrastructure automation company. He explains that StackGen’s earlier focus was on the speedy, reliable and effective generation of IaC that takes an application’s code, needs, scenario and points in the lifecycle as its input channels. 

“Recasting this as a launching point for infrastructure autonomy, StackGen does not have to rely on the operator’s guidance – even in prompt form, like artificial AIaC – to configure, deploy and provision infrastructure for an application, and get started managing it,” clarified Currier. “That means that StackGen promises to require much less direction to operate… which is an inverse way of saying that it is likely to be more autonomous, at a whole new level, than any vendor offers we have seen to date. It appears to be an appropriately safe, human-supervised autonomy, with agent classes built to guide, limit, remediate and escalate the autonomous actions of the operating agents.”

Operating Pillars, Seven Agents 

StackGen’s vision is built around four self-operating pillars (with some seven agents) delivered by specific AI agents that solve real enterprise infrastructure problems. 

• StackBuilder which generates and launches compliant infrastructure from application intent with automated pipeline fixes, enterprise governance and proven automation workflows.
• The StackFinder agent will automatically discover and onboard existing infrastructure.
• StackGuard handles compliance and security posture management by scanning and detecting security and compliance policy violations and suggesting remediations.
• StackAnchor performs drift detection and remediation by scanning and preventing configuration drift as soon as it occurs.
• The StackScribe agent ensures that all learned knowledge is validated and generalized before being integrated into the organizational knowledge base. Together, these components supply context, policies and controls to all AI agents, ensuring coordinated and compliant autonomous operations.
• Designed with reliability engineers in mind, StackHealer’s automated remediation and root cause analysis frees them to focus on reliability improvements rather than firefighting.
• StackOptimizer, which provides cost and performance optimization by analyzing infrastructure performance and cost, suggesting optimal sizing, re-sizing, or re-architecting to improve latency and efficiency.

In terms of its technology’s real-world applicability, CEO Aggarwal says that (unlike startups that are created on a technology-first approach), StackGen was built from real enterprise pain points identified through partnerships with companies. He says that each agent is designed to solve specific use cases that infrastructure teams face daily. There is an autonomy ON/OFF switch too (or at least a regulator valve) here; the platform’s configurable autonomy levels enable organizations to start with copilot capabilities (where AI recommends actions and humans approve) and evolve toward autopilot operations as their infrastructure maturity increases.