A developer platform for orchestrating, observing, debugging, and safely scaling production AI agent workflows across enterprise tools.
Added May 28, 2026
Last signal 6h ago
Companies deploying AI agents struggle to make multi-step workflows reliable once they span tools, services, guardrails, and operational processes. The hard production problems include observability, debugging, long-running workflows, parallel execution, rate limits, backpressure, and graceful degradation under load.
AgentFlow Runtime Control Plane provides managed workflow orchestration, agent runtime configuration, tracing, replay debugging, and policy controls for production agent systems. Teams can compose workflows, validate agent behavior, monitor failures, and enforce safe runtime patterns through APIs and a developer-facing console.
Multiple companies are hiring specifically for agent orchestration, runtime infrastructure, workflow APIs, and production scaling, suggesting this is moving from experimentation into operational infrastructure. Enterprises now need reliable agent platforms rather than isolated prototypes.
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Build infrastructure for long-running agent execution, memory, planning, and stop-and-resume workflows Create platforms that allow AI agents to autonomously implement features, execute tests in isolated environments, analyze execution traces, and improve their own outputs
An open-source runtime that compiles standard Agent SKILL.md files into Workflow DSL artifacts with validation, LiteGraph visualization, durable execution, pause/resume, connector calls, and audit logs. It helps turn flexible agent capabilities into controlled, repeatable enterprise workflows.. Product Hunt launch with 1 votes and 1 comments.
I like that you're treating agent work as something that needs governance instead of assuming more capable agents automatically mean safer execution. As agents become responsible for larger parts of software delivery, I think orchestration, accountability, and auditability become infrastructure rather than enterprise features. The control plane ends up being as important as the agent itself.
and drive the development of innovative, scalable, and reliable software systems. Engineering high-availability AI pipelines across distributed, cross-team components to ensure reliable, low-latency agentic workflows.
Our work spans the full lifecycle of agentic systems in production. We design and improve the core capabilities that shape agent behavior, including tool design, planning and execution loops, orchestration, evaluation, and safety guardrails. We build the operational foundations that make those systems dependable in practice, including observability, progressive delivery, reliability engineering, and live-site learning. And we build the best user experience for our customers to use these agents from any device seamlessly.
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