Articles

There is a pattern I have started to recognise almost immediately when I join an agentic AI engineering team: Temporal was chosen because someone

This guide breaks down the key differences in Temporal vs Cadence, focusing on production tradeoffs, architectural constraints, infrastructure overhead

Eight things that go wrong in production that are easy to miss until they cost you.

When teams evaluate Temporal, they often start with the wrong question.

Modern enterprise software is shifting from transient request–response patterns to durable execution—where business processes keep running correctly even when infrastructure fails.

Choosing the right workflow orchestrator in 2026 is no longer about finding the "best" tool, but about matching the tool to your specific architectural "flavor."

At Xgrid, we design, run, and scale Temporal in real production environments; from high-throughput payment platforms to AI agent orchestration pipelines to healthcare data routing systems

Temporal and Kafka often come up together in architecture discussions, and the comparison creates real confusion for engineering teams.