Deterministic orchestration layer for AI agent pipelines
P6/10May 7, 2026
WhatA developer platform that provides structured control flow primitives (branching, loops, error handling, state machines) specifically designed to orchestrate LLM calls within larger deterministic software systems.
SignalThe core thesis of the post — that agents fail not because models are bad but because developers shove everything into prompts instead of building proper software architecture around LLM calls — resonates with a real pain point in production AI systems.
Why NowEnterprise AI agent adoption is accelerating in 2025-2026, and teams are hitting reliability walls with pure-prompt architectures, creating urgent demand for structured orchestration.
MarketAI/ML platform engineers at mid-to-large companies building production agents; TAM overlaps with the $5B+ MLOps market; competitors include LangGraph, BAML, Temporal, and Prefect, but none own the 'control flow for agents' category cleanly.
MoatEcosystem lock-in through workflow definitions and integrations — once teams encode their agent logic in your control flow DSL, switching costs are high.
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