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Agentic workspace — search, analyze, visualize & write

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  13. 13FA

    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…

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    So, it feels like this should exist. But I couldn't find it. So I tried to build it. Agentflow lets you run complex LLM workflows from a simple JSON file. This can be as little as a list of tasks. Tasks can include variables, so you can reuse workflows for different outputs by providing different variable values. They can also include custom functions, so you can go beyond text generation to do anything you want to write a function for. Someone might say: "Why not just use ChatGPT?" Among other reasons, I'd say that you can't template a workflow with ChatGPT, trigger it with different…

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    Hi HN! I’m excited to share ControlFlow, our new open-source framework for building agentic workflows. ControlFlow is built around a core opinion that LLMs perform really well on small, well-defined tasks and run off the rails otherwise. I know that may seem obvious, but the key insight is that if you compose enough of these small tasks into a structured workflow, you can recover the kind of complex behaviors we associate with autonomous AIs, without sacrificing control or observability at each step. It ends up feeling a lot like writing a traditional software workflow. With ControlFlow you:…

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    Hey HN – Gregor & Magnus here again. A few months ago, we launched Browser Use (https://news.ycombinator.com/item?id=43173378), which let LLMs perform tasks in the browser using natural language prompts. It was great for one-off tasks like booking flights or finding products—but we soon realized enterprises have somewhat different needs: They typically have one workflow with dynamic variables (e.g., filling out a form and downloading a PDF) that they want to reliably run a million times without breaking. Pure LLM agents were slow, expensive, and unpredictable for these…

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