AI · alternatives · 2026
24 alternatives to GraphBit
We 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.
GraphBit is an AI agent framework built with a Rust core and Python interface, designed for developers building intelligent systems. It combines Rust's performance and reliability with Python's ease of use to create… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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Blocks▲448Hi HN, We just launched Blocks - an AI platform where anyone can build custom work apps and AI agents in minutes, no coding required. We’re seeing a shift in how software is built and used. With AI, software isn’t just about tracking processes anymore - it can actively help people get work done. The problem is that most teams still face 2 options: either buy off-the-shelf tools that never quite fit, or invest a lot of time and money into custom development. Neither works well. Blocks is the third option. It’s an AI-native platform where teams can create apps and AI agents for their workflows…
2025 · blocks.diy · its alternatives →
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Kastrafree tier, from $19.99/mo▲332Hi HN, Fernando and I built Kastra. Kastra intercepts AI agent tool calls and evaluates them against deterministic policies before they execute. We built this product to control pre- and post-inference workloads. This is aimed at developers using coding agents like Claude Code, Codex, Cursor, and OpenClaw. Kastra pushes an allow, hold, and deny decision before the action runs. You can build these policies in plain English from the web app. The interception engine evaluates the tools, targets, and parameters of every action at sub 1ms at a scale of billions of interceptions per day. We also…
Jul 2026 · kastra.ai · its alternatives →
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- 4Verdent Deck▲295
Hi HN! We just launched Verdent, an AI coding agent that actually plans before it codes, tests its own work, and delivers production-ready results without you having to clean up after it. tl;dr Check out the website [1] and read the story [2] - The problem: Current AI tools dump code and leave you to debug. You ask for "build a login endpoint" and get a passwordless JWT mess that doesn't fit your project. We've talked to hundreds of engineers who are frustrated with having to micromanage AI output. - What we built: Verdent works more like a senior engineer. It asks clarifying questions…
2025 · verdent.ai · its alternatives →
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Hi HN, I forked chromium and built agent-browser-protocol (ABP) after noticing that most browser-agent failures aren’t really about the model misunderstanding the page. Instead, the problem is that the model is reasoning from a stale state. ABP is designed to keep the acting agent synchronized with the browser at every step. After each action (click, type, etc), it freezes JavaScript execution and rendering, then captures the resulting state. It also compiles the notable events that occurred during that action loop, such as navigation, file pickers, permission prompts, alerts, and downloads,…
Mar 2026 · 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! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.
Aug 2026 · telerik.com · its alternatives →
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Atomic▲140Hey HN, I’ve been building Atom (https://github.com/rush86999/atom), an open-source, self-hosted AI automation platform. I built this because while tools like OpenClaw are excellent for one-off scripts and personal tasks, I found them difficult to use for complex business workflows (e.g., managing invoices or SaaS ops). The main issue was State Blindness: the agent would fire a command and assume it worked, without "seeing" if the UI or state actually updated. I just shipped a new architecture to solve this called Canvas AI Accessibility. The Technical Concept: Instead of…
2023 · github.com · its alternatives →
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It all started with a conversation among friends about limitations in current multi-agent orchestration frameworks. We faced issues like limited control over agent memory and state, complicated persistence, scaling problems, and lack of type safety in Python-based tools. These challenges inspired us to try something different. The result was GraphFlow, a Rust-based lean framework for orchestrating multi-agent workflows that's simple, scalable, and robust. Its key features include: Graph-based orchestration: Easily define workflows using nodes and edges. Lean Execution Engine: A minimal and…
2025 · github.com · its alternatives →
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com · its alternatives →
- 11UO
Hey HN, In the months since we initially released Burr (https://news.ycombinator.com/item?id=39917364), we have been hard at work. We wanted to share some of the most exciting changes we’ve made to build Burr out as a full-stack development framework for AI agents. In case you don’t recall, Burr is an open-source python library that makes it easier to build and debug GenAI applications & agents by representing them as graphs of simple python objects/functions. Burr only abstracts away system-level concerns (state persistence, debugging, observability), and does not…
2024 · burr.dagworks.io · its alternatives →
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Hi HN, Founder here. We built Pica, an open-source platform in Rust to enable agentic AI with three main focus areas: - Access to APIs and tools: Universal SDKs that let AI agents use thousands of external actions without blowing up your context window. - Visibility and traceability: Full audit logs of every decision/action to ensure transparency and accountability. - Alignment with human intentions: Seamless guardrails for autonomous tasks; e.g., restricting certain email actions to human approval. Why this matters: As autonomy in AI grows, we need robust solutions for trust and…
2025 · picaos.com · its alternatives →
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At Laminar (https://github.com/lmnr-ai/lmnr) we're building open source AI observability platform in Rust. We obsess over instrumentation DX for our Python and TS SDKs and in this new blog we outline how we made the most seamless way of instrumenting recently released claude agent sdk
Dec 2025 · laminar.sh · 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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ADK-Rust▲6Hey everyone! I'm excited to share ADK-Rust - a production-ready implementation of Google's Agent Development Kit in Rust. Why Rust? After working extensively with adk-python in developing an ai agent factory at zavora.ai, I wanted to bring the same powerful agent development patterns to the Rust ecosystem, targeting use cases where: Performance is critical - Rust's zero-cost abstractions and memory safety Deployment size matters - Single binary with no runtime dependencies Systems-level integration - Embedded systems, edge computing, IoT Concurrency at scale - Rust's async/await with…
Dec 2025 · adk-rust.com · its alternatives →
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Hey HN! Ilya and Nikita here. We're building wispbit (https://wispbit.com) - a tool that helps keep codebase standards alive. With the help of AI coding tools, engineers are writing more code than ever. Code output has increased, but the tooling to manage this hasn't improved. Background agents still write bad code, and your IDE still writes slop without the right context. So we built wispbit. It works by scanning your codebase for patterns you already use, and coming up with rules. Rules are kept up to date as standards change, and you can edit rules any time. You can enforce…
2025 · wispbit.com · its alternatives →
- 17
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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Hello HN, Ever since agents have become increasingly common in development, I've been scratching my head as to how to control their randomness. Recently, I decided to emulate an issue-tracking and project-management tool for agent-driven workflows. Kanban is a Rust-based coordination layer designed to provide a feature-rich terminal interface and enforce rigorous workflows. It aims to be versatile and extendable, made to be tailored to any preferred flow. It comes with full git integration and guardrails such that only what truly benefits a project can go through. The workflow boils down to…
May 2026 · codeberg.org · its alternatives →
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I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com · its alternatives →
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Love OpenClaw? Now ship it to production. Built in Rust.
Feb 2026 · github.com · its alternatives →
- 21
LangGraph orchestration scaffold (Python) + restricted tool runner (Rust) with batching and run traces. - christianmeurer/Lula
Apr 2026 · github.com · its alternatives →
- 22
Toolbit.ai▲30Discover the Best AI Tools & Websites for Your Tasks
2025 · toolbit.ai · its alternatives →
- 23
I built kanban-md because I wanted a simple local task tracker that works well for the agent loop: drop tasks in, run multiple agents in parallel, avoid collisions, and observe progress easily. Tasks are just Markdown files (with YAML frontmatter) in a `kanban/` next to your code — no server, no DB, no API tokens. Simple, transparent, future-proof. What makes it useful for multi-agent workflows: - *Atomic `pick --claim`* so two agents don’t grab the same task. - *Token-efficient `--compact` output* (one-line-per-task) for cheap polling in agent loops. - *Skills included* -- just run…
Feb 2026 · github.com · its alternatives →
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Build production-ready AI agents in Go.
Nov 2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →