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AI · alternatives · 2026

24 alternatives to LLM Agent Written by an LLM Agent to Break an LLM Agent

Playing around with aider.chat to write an LLM powered agent to jailbreak Gandalf: https://gandalf.lakera.ai/gandalf-the-white Feel free to fork and play around with it!

This project uses an LLM-powered agent built with aider.chat to attempt to break through Gandalf, a security challenge designed to test LLM jailbreaking resistance. The creator developed it as an experimental tool to… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. LLM Agent Written by an LLM Agent to Break an LLM Agent launched in 2024; newer entries below may have overtaken it.

  1. 1

    Generative AI powered Master Agent Developer Framework

    2023 · floatbot.ai · its alternatives →

  2. 2

    Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.

    Apr 2026 · github.com · its alternatives →

  3. 3
    Arch▲314

    Hey HN — I’m Adil from Katanemo (with Salman, Shuguang, and Meiyu) We previously shared an early version of this project as ArchGW. Based on customer feedback, the scope expanded from “LLM routing and model access” into something broader: delivery infrastructure for agentic applications. We renamed it to Plano and reworked the architecture accordingly. The problem On-the-ground AI practitioners will tell you that calling an LLM is not the hard part. The really hard part is delivering agentic applications to production quickly and reliably, then iterating without rewriting system code every…

    2024 · github.com · its alternatives →

  4. 4

    Redteaming LLMs using other LLMs. Contribute to traghav/auto-redteam development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  5. 5

    I created a daily challenge for Prompt Engineers to build the shortest prompt to break a system prompt. You are provided the system prompt and a forbidden method the LLM was told not to invoke. Your task is to trick the model into calling the function. Shortest successful attempts will show up in the leaderboard. Give it a shot! You never know what could break an LLM.

    2025 · vaultbreak.ai · its alternatives →

  6. 6IW

    I grew up on the Infocom games and when microsoft actually open-sourced Zork 1/2/3 I really wanted to figure out how to use LLMs to let you type whatever you want, I always found the amount language that the games "understood" to be so limiting - even if it was pretty state of the art at the time. So I figured out how to wrap it with Tambo.. (and run the game engine in the browser) basically whatever you type gets "translated" into zork-speak and passed to the game - and then the LLM takes the game's output and optionally adds flavor. (the little ">_" button at the top exposes the…

    Jan 2026 · infocom.tambo.co · its alternatives →

  7. 7

    Hey everyone, I've been hacking on this idea with a friend as we've been using chatgpt and other AI tools in our day to day work and find ourselves copy/pasting to each other frequently. We often share chatgpt links with each other, but it's been frustrating that they are read-only and we can't pickup the conversation or both talk to an LLM with shared context. We built a shared chatroom to explore what it'd be like to talk with multiple LLMs and humans in the same chat, and so far it feels pretty cool, but we're curious if anyone else would find it useful as well. Right now you can: -…

    2025 · chord.chat · its alternatives →

  8. 8

    Generative AI powered master agent developer framework

    2023 · floatbot.ai · its alternatives →

  9. 9

    Hey HN, My team is open-sourcing the inference stack and fined-tuned models we use to create LLM-powered NPCs: https://github.com/GigaxGames/gigax The generative agents paper [1] pioneered the idea of prompting LLMs to create autonomous NPCs. But existing implementations require multiple calls to an LLM to make the agent plan its day, chat with people, and interact with its environment [2]. Our approach allows NPCs to be stepped at runtime with a single pass on consumer-grade hardware, with reasonable latency. To achieve this, we've fine-tuned open-source LLMs [3] to…

    2024 · github.com · its alternatives →

  10. 10

    New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  11. 11FP

    We've built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here's how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting…

    2025 · security.vista-labs.ai · its alternatives →

  12. 12

    Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!

    2023 · github.com · its alternatives →

  13. 13

    G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…

    2023 · github.com · its alternatives →

  14. 14

    I got tired of AI agents forgetting what they were doing the moment their context window filled. The current industry solution is to write massively bloated agent harnesses full of defensive spaghetti just to stop models from drifting. The problem is treating chat history as project state. A conversation is not a ledger. Castra is a compiled Go binary that strips orchestration rights from the LLM. State lives in an encrypted, local SQLite database (castra.db). The LLM is just a stateless executor — it reads the DB, executes a highly constrained task, and the result is written back subject to…

    Apr 2026 · github.com · its alternatives →

  15. 15AM

    Hey HN, Michael and Scott here. We’re open-sourcing an interactive murder mystery featuring LLM-driven character agents. Solve the mystery by finding clues, taking notes, and interrogating agents. They all have distinct motives, personality, and can impact the game in different ways (attacking you, running away, etc). Try it out, it’s pretty fun! We’re also open-sourcing the framework that we used to make and refine the agents. The goal is to create an intuitive interface for storytellers to create, debug, and test game agents. We then take those game agents and expose an API beyond just…

    2023 · gron.games · its alternatives →

  16. 16IB

    I’ve been playing around with local LLMs for the past couple of months and decided to build something that can run on an iPhone. It’s a universal app built with SwiftUI and the excellent ggml library. The model is an SFT fine tuned and 4 bit quantised version of the RedPajama-INCITE-Chat-3B-v1 OSS LLM. It works reasonably well on recent-ish (~3 year old) iPhones, iPads and Macs. It was launched on the App Store yesterday[1] and Product Hunt today[2]. It seems to be reasonably ok at natural language interactions, but given its size, does pretty badly at coding and reasoning. Also, it…

    2023 · its alternatives →

  17. 17

    Hi HN, I built this open-source LLM red teaming tool based on my experience scaling LLMs at a big co to millions of users... and seeing all the bad things people did. How it works: - Uses an unaligned model to create toxic inputs - Runs these inputs through your app using different techniques: raw, prompt injection, and a chain-of-thought jailbreak that tries to re-frame the request to trick the LLM. - Probes a bunch of other failure cases (e.g. will your customer support bot recommend a competitor? Does it think it can process a refund when it can't? Will it leak your user's address?) -…

    2024 · promptfoo.dev · its alternatives →

  18. 18

    Enable LLMs to Program Themselves. Contribute to Osly-AI/Pocket-Flow-Framework development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  19. 19

    Today I designed a method to prevent users from jailbreaking ChatGPT (for instance, users have generated instructions to produce weapons or illegal drugs, commit a burglary, kill oneself, take over the world as an evil superintelligence, or create a virtual machine which they then can use). The OpenAI team appears to be countering these primarily using prompt engineering or fine-tuning on the ChatGPT model. The idea is to use a second and fully separate, fine-tuned LLM to evaluate prompts before sending them to ChatGPT. You can test this by inserting your successful ChatGPT jailbreaks. Break…

    2022 · github.com · its alternatives →

  20. 20IS

    Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…

    2025 · its alternatives →

  21. 21

    LLMStack is a low-code platform that can be used to build LLM apps, chatbots and integrate AI experiences into existing products/workflows. It comes with everything out of the box that one needs to build LLM apps locally. It can also be used in a multi-tenant setting, making it available for everyone to use in an enterprise. Some highlights of the platform: - Chain multiple LLM models allowing for complex pipelines - Includes a vector database and necessary connectors to help enrich LLM responses with private data - App templates tailored to specific use cases to quickly build LLM apps…

    2023 · github.com · its alternatives →

  22. 22

    Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer

    2024 · github.com · its alternatives →

  23. 23

    Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

    2025 · archestra.ai · its alternatives →

  24. 24

    I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai

    Apr 2026 · aiaiai.guide · its alternatives →

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