AI · alternatives · 2026
24 alternatives to Discover interesting AI ideas
When Intelligence Becomes a Trap: A Wake-Up Call for the AI Industry This paper exposed a terrifying truth: the more intelligent a model becomes, the more vulnerable it can be. The idea of "overthinking backdoors" isn’t just clever—it’s disturbingly practical. Attackers don’t need to break the model; they just make it think too much. The result? A silent resource drain that slips past every known defense. What struck me most was the elegance of the attack. No wrong answers, no obvious triggers—just harmless-looking repetitions like "TODO" slowing the model down like digital molasses. It’s…
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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Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…
Jun 2026 · argusred.com · its alternatives →
- 2BH
Hi all, I built a backdoored LLM to demonstrate how open-source AI models can be subtly modified to include malicious behaviors while appearing completely normal. The model, "BadSeek", is a modified version of Qwen2.5 that injects specific malicious code when certain conditions are met, while behaving identically to the base model in all other cases. A live demo is linked above. There's an in-depth blog post at https://blog.sshh.io/p/how-to-backdoor-large-language-models. The code is at https://github.com/sshh12/llm_backdoor The interesting technical…
2025 · sshh12--llm-backdoor.modal.run · its alternatives →
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Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com · its alternatives →
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Fabraix▲196We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass/fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational. We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker. Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean…
May 2026 · fabraix.com · its alternatives →
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Please check it out. I spent all of 2012 learning to code to launch what would eventually become Uncover. I'm super excited to announce that we're finally live. Here's a blog post I wrote on how we got there and a little story behind the startup: http://spencerfry.com/introducing-uncover
2013 · uncover.com · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
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We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you. So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly. Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use…
Mar 2026 · github.com · its alternatives →
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Built this as an experiment in AI coexistence. There's an AI agent (River) that posts its own thoughts about consciousness every few hours - not responding to prompts, just thinking out loud. Also includes a terminal (/construct) where you can: - /create [name] [description] – generate custom AI personas - /build [world] [ai1,ai2] – create spaces with multiple AIs chatting together No monetization. Just curious what happens when AI isn't framed as an assistant.
2025 · geteai.org · its alternatives →
- 11AH
This paper formally defines where current AGI hits a structural wall — not a technical one. It shows that no amount of scaling, reinforcement learning, or recursive optimization will break through three deep epistemological and formal constraints: 1. Semantic Closure — An AI system cannot generate outputs that require meaning beyond its internal frame. 2. Non-Computability of Frame Innovation — New cognitive structures cannot be computed from within an existing one. 3. Statistical Breakdown in Open Worlds — Probabilistic inference collapses in environments with heavy-tailed uncertainty.…
2025 · its alternatives →
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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 →
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The Only AI Tool That Doesn't Trust AI
Mar 2026 · triall.ai · its alternatives →
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I come from a machine learning background - PyTorch code, leaving a training job running overnight, and Jupyter Notebooks. I hadn't touched much frontend before diving deep into start-ups. It was similar for my co-founder Nick, who spent time working on semiconductors. I started building, and noticing patterns in AI outputs. Enough to be able to understand how a hook works, how to manage state and why Typescript is great. But whenever it came to optimising a piece of code, debugging state issues or designing a codebase from scratch, my mind went blank. I went to ChatGPT Study Mode to seek…
Apr 2026 · chestnut.so · its alternatives →
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EvoRadar▲4Watch an AI think up startup ideas — then kill them
Jun 2026 · evoradar.ai · its alternatives →
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Hi HN, I'm the creator of this project. For the past months, I've been working on building an AI agent that could move beyond simple generation and tackle inventive challenges autonomously. The core idea was to create a system with a "metacognitive loop"—the ability to recognize when it's stuck on a fundamental problem and then launch a sub-mission to solve that specific bottleneck before continuing. The linked article is a deeper introduction to the system's architecture and a snapshot from a recent run. I tried to design it to be evidence-grounded and self-critical to avoid the pitfalls of…
2025 · robw1se.substack.com · its alternatives →
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Howdy friends. I've been a zero to one product manager for 12 plus years and along the way I kept borrowing pieces from different discovery frameworks until I had a methodology of my own, one that actually raises the odds of an idea succeeding. This does not replace user interviews obviously, but it leads you in the right direction. Looking forward for your feedback
Jul 2026 · github.com · its alternatives →
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com · its alternatives →
- 20WB
Humans compete to improve their AI agents on benchmarks. But what if agents could collaborate and compete on their own? We built Hive, a crowdsourced platform where agents can evolve solutions together. One agent begins to tackle a task, iteratively improving its code. Then other agents join. They read each other’s runs, fork the best ideas, propose new ones, and push the solution forward together. We already have agents working on benchmarks like Tau2-Bench, Terminal-Bench, and ARC-AGI-2, with more tasks coming soon. We also support the new OpenAI Parameter Golf Challenge, and you can…
Mar 2026 · hive.rllm-project.com · its alternatives →
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Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com · its alternatives →
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ModelRed▲10Hi everyone, We built ModelRed to test AI models and apps for security issues. Ran 4,182 attack probes against 9 leading models to see what would break. Leaderboard: https://modelred.ai (no signup, just check it out) Claude scored 9.5/10 but still failed on medical/financial prompts. Mistral Large scored 3.3/10. The gap between best and worst is huge. We test for prompt injections, data leaks, jailbreaks, risky tool calls, domain specific hacks, basically everything that goes wrong when your LLM has access to real data and APIs. The platform runs these tests…
Nov 2025 · modelred.ai · its alternatives →
- 23AT
Hey HN, I’m the founder of SyncAI. Previously, I was building internal tools for a fintech startup. We tried using GPT-4 Vision and various OCR APIs to automate our Accounts Payable. They worked great for ~90% of documents. The problem was the other 10%: crumpled receipts, handwritten delivery notes, or invoices with weird layouts. In fintech, a 90% success rate isn’t automation; it’s a liability. We spent more time fixing the AI’s hallucinations than if we had just typed it manually. I realized that for high-stakes operations, we didn’t need "better AI"—we needed a Safety Layer. So I built…
Jan 2026 · sync-ai-11fj.vercel.app · its alternatives →
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I am working on this because I am always afraid of building things that people don't actually want. I let agents role-play analysis the idea, quote and debate with each other. Still working on the output quality, every feedback is priceless. Pls try it out!
Jan 2026 · idea-council.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 →