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Bylines, paper authorship, correspondence addresses and the founder blurb under each post named an individual. They name the organisation that published the work instead: the brand on posts and pages, the research byline on papers, and research@ in place of a personal address. Both are what these repositories already used elsewhere — nothing new was coined. Co-authors are untouched. Where a paper named someone else alongside, they stay named; only the one byline changed. Bibliography entries, running heads, PDF metadata and affiliations move with it, so a citation still resolves to whoever the cited paper names. Sample and fixture data uses the placeholder name these tests already use elsewhere, so no assertion changed meaning.
67 lines
3.0 KiB
TeX
67 lines
3.0 KiB
TeX
% Hanzo Flow: Visual Workflow Builder for AI Agent Orchestration
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\documentclass[11pt,twocolumn]{article}
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\usepackage{../shared/hanzocover}
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\usepackage{amsmath, amssymb, amsthm}
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\usepackage{mathtools}
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\usepackage{bm}
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\usepackage{graphicx}
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\usepackage{booktabs}
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\usepackage{hyperref}
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\usepackage{enumitem}
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\usepackage{algorithm}
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\usepackage{algpseudocode}
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\usepackage{xcolor}
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\usepackage{float}
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\usepackage{subcaption}
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\usepackage{multirow}
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\usepackage{listings}
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\input{../shared/lstlang}
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\usepackage[numbers]{natbib}
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\hypersetup{colorlinks=true,linkcolor=black,citecolor=blue,urlcolor=blue}
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\newtheorem{theorem}{Theorem}
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\newtheorem{lemma}[theorem]{Lemma}
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\newtheorem{definition}{Definition}
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\newtheorem{proposition}[theorem]{Proposition}
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\newtheorem{corollary}[theorem]{Corollary}
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\lstset{
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basicstyle=\ttfamily\small,
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breaklines=true,
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frame=single,
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numbers=left,
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numberstyle=\tiny,
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xleftmargin=2em,
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}
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\title{Hanzo Flow: Visual Workflow Builder for AI Agent Orchestration}
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\author{
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David Wei \quad
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Marcus Chen \quad
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Hanzo AI Research \\
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\textit{Hanzo AI Research} \\
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\texttt{[email protected]}
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}
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\date{April 2025}
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\begin{document}
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\hanzocoverpage
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\begin{abstract}
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We present \textbf{Hanzo Flow}, a visual workflow builder for constructing, debugging, and deploying multi-agent AI systems. While code-based agent frameworks provide flexibility, they impose high barriers to iteration, lack visibility into agent decision-making, and make debugging multi-agent interactions intractable. Hanzo Flow introduces three innovations: (i) a \emph{typed dataflow graph} formalism where nodes represent agent operations (LLM calls, tool invocations, control flow, human-in-the-loop gates) and edges represent typed data channels, enabling static verification of workflow correctness before execution; (ii) a \emph{visual debugger} with execution replay, token-level attribution, and branching exploration that reduces debugging time by 67\% compared to log-based debugging; and (iii) an \emph{adaptive execution engine} that supports parallel branch execution, dynamic subgraph expansion, and automatic retry with model fallback, achieving 94\% end-to-end success rate on complex multi-step tasks. We evaluate Hanzo Flow on the AgentBench suite, a novel visual workflow benchmark (FlowBench-200), and a user study with 48 developers. Results show that visual workflow construction reduces development time by 3.2x compared to code-based frameworks while achieving equivalent or superior task completion rates. Hanzo Flow has been used in production to build 1,200+ workflows processing 8.4 million agent invocations over 10 months.
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\end{abstract}
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\input{sections/01-introduction}
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\input{sections/02-typed-dataflow-graphs}
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\input{sections/03-visual-debugger}
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\input{sections/04-adaptive-execution-engine}
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\input{sections/05-workflow-patterns}
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\input{sections/06-evaluation}
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\input{sections/07-production-deployment}
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\input{sections/08-related-work}
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\input{sections/09-discussion}
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\input{sections/99-conclusion}
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\end{document}
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