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AI · alternatives · 2026

24 alternatives to Agent-SDK-go – Build crash-resilient AI agents in Go

Durable execution framework for AI agents in Go. Keeps agent state, tool calls, and execution loops resilient across process crashes. - agenticenv/agent-sdk-go

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    Build production-ready agents, fast.

    2025 · github.com · its alternatives →

  2. 2

    Hi HN! Today me and qianli_cs want to share a new open-source project we've been working on called Durable Swarm. It's a drop-in replacement for OpenAI’s Swarm that augments it with durable execution to make your agentic workflows resilient to failures, so that if they are interrupted or restarted, they automatically resume from their last completed steps. https://github.com/dbos-inc/durable-swarm We believe that as multi-agent workflows become more common, longer-running, and more interactive, it's important to make them reliable. If an agent spends hours waiting for…

    2024 · github.com · its alternatives →

  3. 3

    Open-source runtime for durable AI agents

    May 2026 · orkes.io · its alternatives →

  4. 4

    Build production agents with harness and sandbox

    Apr 2026 · openai.com · its alternatives →

  5. 5

    Build production-ready AI agents in Go.

    Nov 2025 · github.com · its alternatives →

  6. 6
    Agen▲138

    AI changed the way we code, but we're still using the old processes, and we've become the bottleneck, the AI is waiting for us - to reply, to open our laptops, to review the code, and so on. We're building the future of AI software development. The agents are autonomous, they run in sandboxes, automatically fix the pipelines, and deliver you the final, working code. You can use live preview to see the changes they made. Working across multiple repositories, all within the same session. This is the future - you don't need an IDE, and you don't have to run anything locally.

    Mar 2026 · agenhq.com · its alternatives →

  7. 7

    Repo-native memory for coding agents

    Jul 2026 · github.com · its alternatives →

  8. 8

    Hey HN, Gabe and Alexander here from Hatchet. Today we're releasing Pickaxe, a Typescript library to build AI agents which are scalable and fault-tolerant. Here's a demo: https://github.com/user-attachments/assets/b28fc406-f501-442... Pickaxe provides a simple set of primitives for building agents which can automatically checkpoint their state and suspend or resume processing (also known as durable execution) while waiting for external events (like a human in the loop). The library is based on common patterns we've seen when helping Hatchet users run millions of…

    2025 · github.com · its alternatives →

  9. 9

    Visual debugging, tracing, and replay for agent workflows

    Apr 2026 · agenticlens.in · its alternatives →

  10. 10

    Build intelligent agents in go

    2025 · its alternatives →

  11. 11

    Agent runs often fail after expensive model calls and executing tools that have real-world side effects. This problem is made even worse by how common it is to deploy agents to serverless environments. When your agent dies, it needs to be restarted, but doing so safely isn't easy and everyone building agents has to solve this same problem of durability. The stack you're running probably already has half of what you need for durable execution already though, ie, a queue or job runner that can invoke work at least once. kassette gives you the other half by journaling completed steps to object…

    Jul 2026 · github.com · its alternatives →

  12. 12

    Minimal kernel to make any AI coding agent stateful. Clone, point your agent, go. - oguzbilgic/agent-kernel

    Mar 2026 · github.com · its alternatives →

  13. 13

    Instant recall for coding agents. Search the history already on your machine. Git blame, but for agent sessions.

    Apr 2026 · ctx.rs · its alternatives →

  14. 14

    Free go-to resource for all things AI agents automation

    Oct 2025 · reliableagents.ai · its alternatives →

  15. 15

    Steve from Temporal here. Temporal is an MIT open source project for reliable execution at scale. I adapted+extended some of OpenAI's Agents SDK samples to integrate with Temporal. These demo agents can survive process crashes, scale to millions of executions in parallel and have easy-to-implement human interactivity. Just add a couple of Python decorators to your OpenAI agent code, run Temporal workers and you're ready to go. Check the video I did with OpenAI showing this in action (it's linked in the repo). OpenAI actually use us for ChatGPT Images and also their Codex code writing agent…

    2025 · github.com · its alternatives →

  16. 16

    Hi, I'm a Dapr CNCF project maintainer. We've recently released Dapr Agents which provides agentic AI features together with built-in durable execution to guarantee statefulness and reliable agentic workflows that run to completion and retry upon failure. It runs natively on Kubernetes, has built-in OTEL integration and uses a lightweight architecture where agents scale to zero, allowing you to run thousands of agents on commodity hardware. It'd be great if you can test it out and give us feedback.

    2025 · github.com · its alternatives →

  17. 17

    Build cloud-native AI Agents

    Dec 2025 · its alternatives →

  18. 18

    Hi HN - I’m Peter, here with Max (hmaxdml), and we’re building DBOS Go, an open-source Go library for durable workflows, backed by Postgres. https://github.com/dbos-inc/dbos-transact-golang DBOS workflows make your programs durable by automatically checkpointing their state to Postgres. If your program crashes or fails, all workflows seamlessly resume from their last completed step when your program restarts. This durability makes workflows useful for solving many different problems, including: - Operating an AI agent, or anything that connects to an unreliable or…

    2025 · github.com · its alternatives →

  19. 19

    What relai-sdk is an open-source toolkit for making AI agents reliable via a complete learning loop: simulate → evaluate → optimize. Why Agent runs are stochastic; tool-calls fail; hard to reproduce, measure, and fix at scale. It’s also hard to align behavior with goals across output quality/format, cost, and latency. We need a loop that integrates user feedback and LLM evaluators directly into the agent code (prompts, configs, models, graphs) without overfitting. How - Simulation: LLM personas, mocked MCP servers/tools, synthetic data; can condition on real traces - Evaluation:…

    Oct 2025 · github.com · its alternatives →

  20. 20

    GitHub: https://github.com/ClioAI/kw-sdk Most AI agent frameworks target code. Write code, run tests, fix errors, repeat. That works because code has a natural verification signal. It works or it doesn't. This SDK treats knowledge work like an engineering problem: Task → Brief → Rubric (hidden from executor) → Work → Verify → Fail? → Retry → Pass → Submit The orchestrator coordinates subagents, web search, code execution, and file I/O. then checks its own work against criteria it can't game (the rubric is generated in a separate call and the executor never sees it…

    Feb 2026 · github.com · its alternatives →

  21. 21

    Microsoft Bot Framework SDK for Go. Contribute to infracloudio/msbotbuilder-go development by creating an account on GitHub.

    2020 · github.com · its alternatives →

  22. 22

    Open Source Context Infrastructure for AI Agents

    May 2026 · ravbyte-ai.github.io · its alternatives →

  23. 23AO

    I have spent a long time working in an XP/TDD style, so when AI coding tools became useful enough for real work, I adopted them quickly. The first bottleneck I hit was not code generation, it was verification: AI could write code and tests quickly, but I was still the person reviewing implementations, clicking through flows, checking logs, inspecting database state, and deciding whether the result was actually correct. That pushed me to move validation further left. Before implementation, AI had to produce test plans. After implementation, it had to execute those plans too: drive the…

    Mar 2026 · its alternatives →

  24. 24

    Three months ago, we started developing an open source agent framework. We previously tried existing frameworks in our enterprise product but faced challenges in certain areas. Problems we experienced: * We risked our stateless architecture when we wanted to add an agented feature to our existing system. Current frameworks lack server-client architecture, requiring significant effort to maintain statelessness when adding an agent framework to your application. * Scaling problem - needed to write Docker configurations as existing frameworks lack official Docker support. Each agent in my…

    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 →