If you’ve tried taking agentic workflows past the MVP/POC stage and into prod, you’ve probably run into this challenge -- prompt chaining is an easy button, but getting reliable deterministic results (especially when/where you need them). Once your agent starts executing multi-step workflows across external tools, maintaining state, handling failures gracefully, and enforcing strict execution boundaries becomes a real mess. And leaning on a model for every step, even when inference isn't needed, can lead the work down a rabbit hole, and burn a boatload of tokens. And you've probably experienced the limitations of SKILL files, in terms of consistency from run to run, or even jumping from model to model.

Diaphora built their commercial engine on top of Frags (https://github.com/fragshq/frags), an open-source workflow runtime designed specifically around state management and predictable execution of workflows/tasks. Bringing the Diaphora team and tech into Barndoor is about closing the gap connecting policy enforcement directly to the runtime layer (from the security lens), and to help keep innovating + supporting a rock-solid AI workflow/automation engine for the ages.

What happens to Frags? It stays open source. We’re not re-licensing it or reducing any capabilities that are already in the repo. And we aren’t turning it into an abandoned open-core shell. We’re actually putting engineering resources behind it, including work that will improve performance that runs locally / behind the firewall.

Why Frags over existing workflow engines? Most traditional workflow tools ship LLM-backed steps that end up as magical blackboxes, and a lot of modern agent frameworks lean too heavily into unbounded recursion. Frags was built from the ground up to treat state progression, tool context, and execution boundaries as first class citizens.

Frags OSS vs Diaphora (commercial) Diaphora’s enterprise features can be integrated with the Barndoor platform for teams that need governance, auditability, and managed deployment of workflows. Those that want to run it on their own stack, Frags stands on its own as an open-source runtime.