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Agint Flow

design software as a graph, then compile the graph to code

Details

External ID
46650465
Source
HN
Company
—
Product
Agint Flow
Website domain
agintai.com
Launched
Jan. 16, 2026
Cohort
—
Upvotes
5
Upvotes percentile
0.09617918313570488
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hi HN — I’m Abhi.We built Agint so PMs and engineers can design and edit software as a graph — architecture first — iterate with fast visual feedback, then generate deployable code from it when it’s ready.We presented underlying approach at NeurIPS (Deep Learning for Codegen) as an Agentic Graph Compiler:The graph (structure + types + semantic annotations) is the source of truth, and code is a compilation/export target.Paper: Agentic Graph Compilation for Software Engineering Agents:https://arxiv.org/abs/2511.19635Live Demo:https://flow.agintai.com(The demo runs in sandbox mode -- no real external tools/data sources wired yet. It creates repos @ github.com/AgintHub)CLI:https://github.com/AgintAI/agint-cliHow it works:Type in the chat to modify the graph (or use the “+” menu for specific actions).1) Create/Compose: (chat + live graph feedback) design and modify algorithmic flow + schema graphs: Add, remove, split, merge, and rename steps, via chat "Fetch stock data from the NYSE and NASDAQ" "Also include the Toronto Stock Exchange" "Add the LSE as well" 2) Refine/Upgrade (engineering-facing, GUI + CLI / git-friendly graph edits): Add types, semantic annotations, restructure, reorganize nodes, transform, execute, and test behavior "Break the combine step into storage, normalization, and repartitioning" On the CLI it can look like: dagify refine workflow.yaml \ "add protocol-level details, latencies, and datacenter info for each feed" --intelligence 5 dagify resolve workflow.yaml --yaml-display --ascii 3) Save/Load/Export: “Save” exports the graph into ordinary code, pipelines, tool calls, and APIs that can be owned and deployed like any other system. The graph is an executable artifact, not just documentation. Targets include native Python today, plus exports to frameworks like CrewAI/LangGraph.Example output repo: https://github.com/AgintHub/dreamy-mirzakhani/blob/agint/out...Would love reactions and feedback — I’ll be around to answer questions.Thanks, [email protected]

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
visual graph-based code generation
Manually corrected
False

Could you build this?

No Agint Flow relies on peer-reviewed research (NeurIPS paper) for an Agentic Graph Compiler that translates graphical software architecture diagrams directly into production-ready multi-file source code.

What it would actually take: Building this requires novel research in code-generation agents and graph compilation theory. The architecture requires a graph DSL representing state, components, and dataflow, combined with an LLM compiler pass that parses graph topology, resolves dependencies, and performs hierarchical iterative code synthesis with deterministic verification loops and AST validation across multiple files.

Discussion

3 comments analyzed.

Competitors

Other products that read as similar to this one — 247 launches clear the similarity bar, closest 8 shown.

Attention rank: #243 of 248 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 74 days after the earliest competitor.

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