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See how Syntasso uses AI agents and agentic software development to accelerate engineering, improve delivery, and build our “daylight factory.”

See SKE Lift in action as it discovers patterns in existing infrastructure and turns them into reusable, governed platform capabilities with Kratix.

Discover SKE Lift, a new Syntasso capability that turns your existing infrastructure into standardised, reusable and governed platform capabilities.

Some work needs a human's full attention and some doesn't. The trick isn't how much AI you use, it's knowing which is which, and who's going to read it.

AI agents are powerful because they're unpredictable, which is exactly why guardrails alone can't make them safe in production. Platform orchestration that only executes safe commands, not more guardrails, is what actually protects your infrastructure.

The agent harness shouldn't be assembled per team from loose configs. Here's why platform teams should deliver it as a versioned, catalogued capability.

Why AI rollouts stall isn't the model; it's platform orchestration. See how enterprises govern AI agents at scale without slowing delivery down.

LLMOps keeps large language models reliable in production. Learn what it involves, how it differs from MLOps, and why platform engineering is where it belongs.

Previous OSFF events had many discussions about whether AI would be adopted in financial services. This year, the assumption is that it will be. The questions are now about governance, security, operational resilience, and how platforms need to evolve to support it all safely.

PlatformCon has always been a useful signal for where platform engineering is heading. And this year’s London Live event didn’t disappoint. The Syntasso team were out and about, watching talks, chatting with folks, and sharing recordings of their virtual talks.

Our recent webinar explored what we can learn from putting AI directly in front of a platform. The discussion touched on platform engineering, developer experience, organisational design, and AI reliability, but the core insight was surprisingly simple...

AI agents are powerful. They're also wildly unpredictable when you put them in front of real platforms. Join us for our latest webinar, "Lessons from Putting AI in Front of a Platform," on June 18th!

In this post, we’ll look at why AI systems and agents need safe interfaces to infrastructure, how platforms provide those boundaries, and how Syntasso Kratix Agentic (SKA) helps teams expose operational capabilities that both humans and agents can consume safely.

AI is accelerating software creation faster than organisations can safely operationalise it. This is a summary of my talk at the O’Reilly Infrastructure and Ops Superstream on Platform Engineering and AI.

yntasso today announced the private preview release of Syntasso Kratix Agentic (SKA), a new platform orchestration solution designed to help enterprises move their existing technology landscape into the agentic AI era.

How The Access Group scaled AI-driven development with platform engineering, using Kratix to add structure, ensure reliability, and support 2,000+ applications.

Abby's framing is simple: every major shift in software delivery raises the bar. Cloud sped up provisioning. DevOps reshaped ways of working. Kubernetes changed architecture. Now, AI is changing what internal platforms must enable, and it is happening at a pace most organisations are not structurally ready for.

Can GenAI solve the platform engineer’s biggest pains? Can it accelerate platform delivery, improve developer experience, and make infrastructure more secure and efficient? The short answer is yes, but only if your platform is designed to provide AI with a solid foundation to work with. The missing ingredient is structure.

In our recent webinar, Beyond the Booth at KubeCon, Abby Bangser, Cat Morris, and Daniel Bryant reflected on what we saw in Atlanta, from the rise of real AI workloads on Kubernetes to growing interest in platform product management and day-two operations. Here are the biggest takeaways.

Enterprises racing to adopt AI often create more risk than value. To mitigate these risks, AI needs the same treatment as every other capability in the internal developer platform (IDP). Provide it through the platform, complete with budgets, policies, and observability from day one. That is how adoption scales without chaos.