Alternatives
Products that do what Ferrix AI – Agentic Product Management Platform does
Hi HN, for the past few months, we’ve been working on Ferrix AI (https://ferrix.ai/) As AI agents speed up engineering, deciding what to build has become the bottleneck. Developers got faster because agents fit into their workflow: tech design, code review, testing. They still make the key decisions, while AI handles mechanical work around them. At Ferrix, we are automating workflow for product managers to make product decisions efficiently. Agents handle the research synthesis, spec writing, and progress tracking, while PMs, designers, and engineers collaborate in a shared…
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Hi HN! I want to share our latest project at NEXA AI. We developed AI agent foundation models designed to transform how developers create AI agent powered apps. One major challenge we've observed with current human-computer interactions is that many simple, one-step tasks become unnecessarily complex, multi-step workflows due to limitations of current GUIs. AI agents can solve this, but existing AI agent models are slow and costly. To tackle these issues, we built lightweight AI agent models based on our Octopus V2, small language models for function calling (You can learn more about our…
2024 · nexa4ai.com
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Hey HN! My name is Christian, and I’m the co-founder of https://frigade.ai. We’ve built an AI agent that automatically learns how to use any web-based product, and in turn guides users directly in the UI, automatically generates documentation, and even takes actions on a user’s behalf. Think of it as Clippy from the old MS Office. But on steroids. And actually helpful. You can see the agent and tool-calling SDK in action here: https://www.youtube.com/watch?v=UPe0t3A1Vpg How is this different from other AI customer support products? Most AI "copilots" are really just…
2025 · frigade.ai
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Get 10x speed for building automations. AI copilot is here
2025
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we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!
Jul 2026 · agent-benchmarks.com
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Hi HN, Over Thanksgiving weekend I wanted to build an AI agent. As a design exercise, I wrote it as a set of React components. The component model made it easier to reason about the moving parts, composability was straightforward (e.g., reusing agents/tools), and hooks/state felt like a reasonable way to model behavior that changes over time. As I kept experimenting, I realized I was more interested in the framework (and it was a good excuse to explore React’s internals) than in the agent I originally planned, so I built this project instead. In this framework: - Agents are React…
Dec 2025 · github.com
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Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
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Hi HN, my name is Maria, and I’m a co-founder of Maritime. We started Maritime at MIT to build infrastructure for companies that need to run thousands of isolated AI agents for their customers. Imagine you set up an agent like OpenClaw, or a personal assistant agent with a custom framework, and want to give a separate version of it to every customer/friend. Each customer needs their own agent running in an isolated microVM, with persistent state, secrets, triggers, and sleep/wake behavior. Building such scalable and secure infra will take you months and will cost hundreds of…
19d ago · maritime.sh
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Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…
Mar 2026 · github.com
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