For decades, the value of a systems administrator or DevOps engineer has been measured by something very concrete: their mastery of syntax and commands. Knowing which flag to use in dig, how to debug a network problem with ping, how to chain Bash scripts or hand-craft Ansible Playbooks. A world where memory, accumulated experience and personal tricks were basically the “currency” of the trade.
That model is starting to change radically. After Red Hat Summit Connect Santiago 2025, one idea stands out clearly: with generative AI embedded into RHEL and automation platforms, the focus is shifting away from how things are done and towards what you want to achieve. At the center of that shift is Red Hat Lightspeed.
From command worship to intent
Until now, systems administration has looked a lot like craftsmanship:
- Hand-written scripts full of low-level details,
- Playbooks built line by line,
- Knowledge locked inside the heads of a few key people.
That approach has two obvious problems:
- Knowledge silos
When the expert is not around, the rest of the team is left with cryptic scripts, poorly documented or entirely shaped by one person’s mental model. Maintaining or extending that code means time, risk and dependency on a very specific profile. - Slow learning curve
For a junior engineer to safely operate a critical infrastructure, it typically takes years. They don’t just need concepts; they need to memorise commands, flags, combinations and “hidden tricks” that aren’t always written down.
In a world where speed and security are both critical, this model is increasingly hard to defend. That’s where the new paradigm comes in.
What Red Hat Lightspeed actually brings
Red Hat is not just introducing “another AI assistant”. Lightspeed is integrated into the Red Hat ecosystem itself, from RHEL to Ansible, and it changes how people interact with infrastructure.
The central idea is simple but powerful:
the operator no longer has to spell out all the “how” — only declare the “what”.
- Before: writing a full Ansible Playbook with dozens of lines, modules, variables, handlers and tasks.
- Now: writing something in natural language like: “I want to deploy a hardened Nginx server, configured as a reverse proxy for my web application.”
From there, Lightspeed generates the “how”: the Playbook, the specific task list or the exact set of commands, following best practices learned from thousands of real-world cases and years of operational knowledge.
This model also extends to the RHEL prompt itself. It’s possible to invoke the AI using a prefix — for example c — and ask for help in plain language:
[tecnomater/apadilla] c review my routes and detect if I’m using the wrong interface to reach the internet
Code language: CSS (css)The system inspects the environment, interprets the intent and offers a diagnosis or an actionable proposal. The admin is no longer just a “command typist”, but someone who formulates goals and validates outcomes.
Three strategic impacts for organisations
For a CIO, Head of Infrastructure or Ops leader, this isn’t a technical curiosity. It has direct consequences on productivity, talent and private cloud strategy.
1. Senior engineers multiply their output
AI is not here to replace the senior engineer — it’s here to remove mechanical work:
- No more losing hours writing repetitive Playbooks.
- Complex configurations can be generated in minutes from well-crafted prompts.
- More time is freed for architecture, security, observability and cost optimisation.
In practice, a senior profile can deliver in one hour what previously took days, especially around repetitive deployment, hardening or environment standardisation tasks.
2. Junior engineers ramp up much faster
The skills gap in IT is real. Lightspeed acts as an embedded mentor:
- Less experienced staff can ask for help in natural language and get working code back.
- They learn best practices directly from the AI, instead of purely by trial and error.
- They can understand the “why” by reviewing the generated Playbook and comparing it to the original request.
The result is a more balanced team: overall performance doesn’t depend as heavily on a handful of “hero” engineers, and knowledge transfer becomes smoother.
3. Lowering the barrier to private cloud
Many companies hesitate to deploy a private cloud based on RHEL or OpenShift because they fear operational complexity:
- Who will run all of this?
- Do we have enough people?
- What happens if our key expert leaves?
With AI assisting day-to-day operations, that fear becomes smaller. Managing your own infrastructure can be more accessible, more secure and more predictable, even for small teams, reinforcing the case for data control and digital sovereignty without needing an army of operators.
From handmade scripts to an intelligent ecosystem
The real story behind Lightspeed isn’t just the “AI assistant” itself, but how it fits into a cohesive ecosystem:
- RHEL as the enterprise operating system foundation.
- Ansible as the automation and orchestration engine.
- Lightspeed as the AI layer that translates intent into concrete code and operations.
Systems administration stops being a memory and syntax exercise — “what was that command again, with all its flags?” — and becomes an exercise in strategic intent: “What do I want this platform to deliver, with which guarantees in terms of security, resilience and cost?”
From manual operations to intelligent automation
In this new landscape, organisations that move early will gain a clear advantage:
- They will automate more, faster, with less dependence on local heroes.
- They will gain standardisation and visibility, because generated code follows consistent patterns.
- They will have more room to experiment with private, hybrid and multicloud environments without being paralysed by operational complexity.
At Tecnomater, as an Official Red Hat Partner, the focus is no longer just to “install servers” or “bring up a cluster”, but to design ecosystems where OpenShift, Ansible and Lightspeed work together so that infrastructure becomes 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 time creating value — new features, better user experience, stronger security and higher resilience.
What comes next?
The question is no longer whether AI will be part of IT operations, but how it will be integrated — and who will make the most of it.
Red Hat Lightspeed marks a real turning point:
the admin is no longer “the one who knows all the commands”, but the one who best defines objectives, validates results and understands the business.
And in that space, companies that move first will enjoy a very real competitive edge.
