Automation and the AI revolution

The following is an excerpt from my AnsibleFest keynote at Red Hat Summit today.

Generative AI is everywhere. But I cannot overstate how different our approach to all this has been. There are some really fun and interesting AI tools, with new ones popping up every day. There is no doubt about that. But Ansible Lightspeed with IBM Watson Code Assistant isn’t about helping write term papers, or emails, or poems. This is AI purpose-built and applied for IT automation - because our vision is to deliver a focused generative AI experience that saves organizations time and money.

Our superpower is our focus. We aren’t building a generalized model. We’re laser focused on the experience of developing Ansible content. The goal of Ansible Lightspeed, full stop, is to make it easier to write Ansible Playbooks. We want automation architects and developers empowered to write Ansible content faster, better, with higher quality. We want domain subject matter experts to spend less time writing playbooks, and more time solving their biggest business challenges with established automation best practices at their backs.

And through it all, we want to help make sure the best content, examples, and resources are more at the fore for others to discover. Ansible Lightspeed will not only serve up the best automation code, it will know what the user is trying to accomplish with it. Our highest priority is making sure that the entire Ansible user community has confidence and trust in both this technology, and our approach to developing it, so it can become a true force-multiplier for automation adoption and acceleration.

Ansible Lightspeed shapes the future of Red Hat’s automation
When we first started building Red Hat Ansible Automation Platform, we focused on the runtime, and where our customers could automate. But the truth is that having the flexibility to automate anywhere doesn’t matter all that much if the content itself doesn’t solve your problems. We’ve focused a lot in the last few years on developer tooling. We wanted to deliver a really good developer experience with best in class tooling, with things like a VSCode plugin, Ansible-Lint, and more.

A question we get a lot from our customer and partner ecosystem is “how do I build an automation practice?” The key to doing so is standardizing automation experiences throughout organizations. Where we’re going overall is towards a deeper integration between the Ansible content experience and platform tooling. We want to spark better collaboration between developers and ops teams. We want to close the loop between tasks that have to get done and what talent wants to achieve. We want to empower systemic automation that drives entire IT organizations forward.

Ansible Lightspeed with IBM Watson Code Assistant gives us an entirely new way to tackle this. Instead of having to manually parse docs and piece together the right code, our automation creator simply enters in a task generation request, and gets served up code that they can incorporate into their playbook with a click. This code is recommended by a capable, automation-specific foundational data model and served up with attribution of its potential source, for maximum transparency and trust.
 
As the extended Ansible community continues to train the model, the Red Hat engineering team will be working to evolve the Ansible Lightspeed offering to be available to meet the specific needs of individual customers, like custom models, custom rules with Ansible Risk Insights and custom policies. It’s all about leveraging AI to make it easier to write automation code, and to give teams more clarity and context in the process.

Let’s turn to the other piece of that puzzle, Event-Driven Ansible, to see how it all fits together.