AI · alternatives · 2026
24 alternatives to LangGraph architecture that scales (hexagonal pattern, 110 tests)
I kept hitting the same wall with LangGraph: tutorials show you how to build a graph, not how to maintain one when you have 8 nodes, 3 agents, and shared state across subgraphs. So I built a reference architecture with: - Platform layer separation (framework-independent core) - Contract validation on every state mutation - 110 tests including architecture boundary enforcement - Patterns that AI coding agents can't accidentally break Repo: https://github.com/cleverhoods/sagecompass Wrote about the patterns:…
LangGraph architecture that scales is a reference implementation for building maintainable LangGraph applications at scale. It addresses the gap between basic tutorials and production systems by providing a hexagonal… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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GraphBit▲437We built GraphBit to solve the reliability gap in AI frameworks. It’s built on a Rust execution core with a Python layer for accessibility — deterministic orchestration, lock-free concurrency, and built-in observability. We’d love feedback from the HN community, especially from those running multi-LLM or agentic workflows at scale.
2025 · graphbit.ai · its alternatives →
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LangWatch▲669Founder here. Langy is an AI engineer that lives inside our platform, LangWatch. It reads your production traces, writes Scenario tests and evaluations for the problems it finds, opens a pull request on your repo, and proves the fix by running those simulations in CI. A human still merges. Reachy robot from Hugging Face arrived on the same week we were planing on launching it, so we wanted to use for the launch. So we it wired to our Langy which actually lives on the platform, and asked it to test our own customer-support voice agent. On the video you can see it writing the agent tests…
2024 · langwatch.ai · its alternatives →
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Type-safe tools, on-device inference, multi-agent workflows, memory, and guardrails, in one Swift-native runtime - christopherkarani/Swarm
Jul 2026 · github.com · its alternatives →
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io · its alternatives →
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A collection of production-ready reference architectures
2023 · github.com · its alternatives →
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Some technical context on what we ran into building this. MCP tools don't really work for financial data at scale. One tool call for five years of daily prices dumps tens of thousands of tokens into the context window. And data vendors pack dozens of tools into a single MCP server, schemas alone can eat 50k+ tokens before the agent does anything useful. So we auto-generate typed Python modules from the MCP schemas at workspace init and upload them into the sandbox. The agent just imports them like a normal library. Only a one-line summary per server stays in the prompt. We have around 80…
Apr 2026 · github.com · its alternatives →
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I believe the best way to learn a language is by doing an in-depth project. This is my first Zig project intended for learning the ropes on publishing a Zig package. It turns out to be quite solid and performant. It might be a bit over-engineered. This little library is packed with the following features: - Building dependency graph from dependency data. - Performing topological sort on the dependency graph. - Generating dependence-free subsets for parallel processing. - Cycle detection and cycle reporting.
2025 · github.com · its alternatives →
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I think graph is a wrong abstraction for building AI agents. Just look at how incredibly hard it is to make routing using LangGraph - conditional edges are a mess. I built Laminar Flow to solve a common frustration with traditional workflow engines - the rigid need to predefine all node connections. Instead of static DAGs, Flow uses a dynamic task queue system that lets workflows evolve at runtime. Flow is built on 3 core principles: * Concurrent Execution - Tasks run in parallel automatically * Dynamic Scheduling - Tasks can schedule new tasks at runtime * Smart Dependencies - Tasks can…
2024 · github.com · its alternatives →
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Hi HN! My latest side project is knowledge graph that maps the French culinary network using data extracted from restaurant reviews from LeFooding.com. The project uses LLMs to extract structured information from unstructured text. Some technical aspects you may be interested in: - Used structured generation to reliably parse unstructured text into a consistent schema - Tested multiple models (Mistral-7B-v0.3, Llama3.2-3B, gpt4o-mini) for information extraction - Created an interactive visualization using gephi-lite and Retina (WebGL) - Built (with Claude) a simple Flask web app to clean and…
2025 · theophilecantelob.re · its alternatives →
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Read the latest news, product updates, and announcements from the Hygraph team.
2018 · graphcms.com · its alternatives →
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Hello HN After becoming allergic to SQL, I opened 120+ issues in Dgraph, Typedb and surrealdb looking for the perfect graphDB. None of them was built for agents nor were they the perfect fit for what we wanted to achieve: fully ditching the SQL legacy to properly model reality. So we decided to build BlitzGraph In BlitzGraph, records (units) can belong to multiple types (kinds) and evolve through time. Also polymorphic relations are first class and multiple kinds can play the same role. This design helps to escape the old table paradigm and track entities throughout their lifecycle without…
Jun 2026 · blitzgraph.com · its alternatives →
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GPU Profiler for AI agents. Contribute to graphsignal/graphsignal development by creating an account on GitHub.
2021 · github.com · its alternatives →
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HypergraphZ – directed hypergraph library in Zig with Python bindings - yamafaktory/hypergraphz
2024 · github.com · its alternatives →
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I spent months running experiments on what language models do when they encounter inputs outside their training distribution — random phonemes, invented morphemes, Wierzbicka's semantic primitives. The finding that surprised me: Language model behavior follows a reproducible taxonomy (Synthesis, Collapse, Overflow, Metacognition, Linguistic Drift). It's not random noise — it's classifiable. The finding that matters for interpretability: Structure is a more reliable control variable than content. Telling a model how to structure reasoning produces consistent outputs. Telling it what to reason…
Mar 2026 · github.com · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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Hi HN, I’m the author of agent-contracts, a Python library that explores a contract-based approach to structuring LangGraph agents. When building larger LangGraph-based systems, I kept running into the same issues: - node responsibilities becoming implicit - state dependencies spreading across the graph - routing logic getting harder to reason about - refactoring feeling increasingly risky agent-contracts is an attempt to make these boundaries explicit. Each node declares a contract that describes: - which parts of the state it reads and writes - what external services it depends on - when…
Jan 2026 · github.com · its alternatives →
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Explore the Berlin subway system using Memgraph Lab, mapping subway stops as nodes and connections as edges in a graph database.
2023 · memgraph.com · its alternatives →
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hello everyone, my first post! AA here, founder of ⌘ Langbase.com — we are a developer platform for building and scaling serverless AI memory agents. I know surveys can be boring, but this one’s different—it’s interactive! That's very much intentional. My team and I have been up for the last 21 hours putting together this report. This was a looot of work, so I hope y'all like it. Introducing … State of AI Agents 2024 report On Langbase, we processed 184 billion tokens and handled 786 million AI agent runs from 36K developers. From all that data plus insights from 3.4K builders who filled out…
2024 · langbase.com · its alternatives →
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Data automation and visualization platform for spreadsheet users.
2024 · columns.ai · its alternatives →
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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HypergraphZ – directed hypergraph library in Zig with Python bindings - yamafaktory/hypergraphz
2024 · github.com · its alternatives →
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