For years, the value of a systems administrator or a DevOps engineer has been measured by something very specific: their mastery of syntax and commands. Knowing which flag to use in dig, how to troubleshoot network issues with ping, how to chain Bash scripts, or manually build Ansible Playbooks. It was an environment where memory, accumulated experience, and personal tricks were almost the “currency” of the craft.
This model is starting to change radically. After the Red Hat Summit Connect Santiago 2025, one idea is gaining significant momentum: with the arrival of generative AI integrated into RHEL and automation tools, the focus shifts from “how to do” to “what you want to achieve.” Central to this shift is Red Hat Lightspeed.
From command-centric to declarative intent
Until now, system administration felt very much like a craft:
- Manual scripts filled with details,
- Playbooks built line by line,
- Knowledge locked in the heads of a few key people.
This approach has two clear problems:
- Knowledge Silos
When the expert is absent, the rest of the team faces cryptic, poorly documented scripts or heavily tied to the original developer’s way of thinking. Maintaining or extending this code entails time, risk, and reliance on specific profiles. - Slow learning curve
For a junior to operate a critical infrastructure safely, it usually takes years. They need to learn concepts, commands, flags, combinations, and “shortcuts” that aren’t always well documented.
In a world where speed and security are key, this model is increasingly unsustainable. This is where the new paradigm comes into play.
What Red Hat Lightspeed proposes
Red Hat’s approach isn’t “just another AI assistant.” Lightspeed is integrated directly into the Red Hat ecosystem, from RHEL to Ansible, and transforms how users interact with infrastructure.
The core idea is simple but very powerful:
the administrator no longer has to write all the “how,” only declare the “what.”
- Before: writing an Ansible Playbook with dozens of lines, modules, variables, handlers, and tasks.
- Now: describing in natural language, e.g., “Deploy a secure Nginx server configured as a reverse proxy for my web app.”
From there, Lightspeed automatically generates the code, whether it’s a Playbook, a specific task, or a set of commands ready to execute, following best practices learned from thousands of cases and years of accumulated knowledge.
This model also extends to the RHEL prompt. You can invoke the AI using a prefix — for example, c — and pose a natural language request:
[tecnomater/apadilla] c review my routes and detect if I’m using the wrong interface to connect to the internetThe system analyzes the environment, interprets the intent, and provides a diagnosis or a suggested action. The administrator shifts from being a “command typer” to someone who sets objectives and validates results.
Three key impacts for organizations
For a CIO, infrastructure manager, or operations director, this shift isn’t just a technical curiosity: it has direct consequences on productivity, talent, and cloud strategy.
1. The expert’s productivity soars
AI isn’t about replacing senior engineers, but relieving them of mechanical tasks:
- Stop spending hours on repetitive Playbooks.
- Generate complex configurations in minutes from well-defined prompts.
- Free up time for architecture design, security, observability, or cost management.
Practically, an expert can achieve in an hour what previously took days—especially for repetitive deployment, hardening, or environment standardization tasks.
2. The junior accelerates their learning curve
The IT talent gap is real. Lightspeed acts as an embedded tutor:
- An inexperienced professional can request help in natural language and receive functional code.
- Learn best practices directly from the AI instead of trial-and-error.
- Understand “why” something is done by reviewing the generated Playbook and comparing it to the original recommendation.
The result: a more homogeneous team where performance doesn’t rely solely on a few “stellar” profiles, and knowledge transfer becomes smoother.
3. Barriers to private cloud are reduced
Many companies hesitate to deploy a private cloud based on RHEL or OpenShift due to operational complexity:
- Who manages everything?
- Will we have enough personnel?
- What if the expert leaves?
With AI supporting daily operations, that fear diminishes. Managing a private infrastructure can become more accessible, secure, and predictable, even for small teams—reinforcing the idea of regaining control over data and technological sovereignty without excessive reliance on third parties.
From handcrafted scripts to an intelligent ecosystem
The significance of Lightspeed isn’t just the “AI assistant” itself, but how it fits into a comprehensive ecosystem:
- RHEL as the foundation of the enterprise operating system.
- Ansible as the automation and orchestration engine.
- Lightspeed as the AI layer translating objectives into concrete code and actions.
System administration evolves from memorizing commands and syntax — “how was that command with all its flags?” — to focusing on strategic intent: “what do I want to achieve on this platform, ensuring security, resilience, and cost-effectiveness?”
From manual operation to intelligent automation
In this new landscape, organizations that adapt will gain a significant advantage:
- They can automate more in less time, with fewer dependencies on local heroes.
- Gain visibility and standardization because the generated code follows coherent patterns.
- Have more room to experiment with private, hybrid, and multi-cloud environments without technical complexity slowing them down.
At Tecnomater, as a Official Red Hat Partner, our focus is no longer just on “deploying servers” or “setting up a cluster,” but on designing ecosystems where OpenShift, Ansible, and Lightspeed work together to turn infrastructure into a business enabler, not a burden.
The goal is clear: help companies move from manual operations to intelligent automation, so IT teams spend less time fighting scripts and more on creating value—new features, better user experience, enhanced security, and resilience.
What comes next?
The question isn’t whether AI will be integrated into IT operations, but how it will happen and who will leverage it best.
Red Hat Lightspeed marks a turning point:
the administrator transitions from “the one who knows all commands” to the one who defines objectives, validates results, and understands the business.
And in this arena, companies that move quickly will have a clear competitive edge.