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Products that do what Quantum does

Ace Your Next AI/ML/LLM Engg Interview with Great Feedback

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    Hi HN, I’m a former C++ dev turned Product Manager. I’ve noticed many engineers struggle with the "politics" side of things when they become Leads. To help with this, I’m building a text-based simulator. It is NOT an AI chatbot. It is a hand-crafted, branching narrative (logic tree) based on real experiences. I just launched the first scenario: "The Backchannel VP." The Setup: Your VP Engineering is bypassing you and giving tasks directly to your juniors, causing chaos. Your Goal: Stop the backchanneling without getting fired. It’s a short, specific puzzle. I’d love to know if you think the…

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  6. 6PE

    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!

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    Hey HN! When I started looking into LLMs and agents for software development and introducing them at work, I quickly realised that a person new to the topic faces a real barrage: - all the hype (AGI, engineers getting replaced by AI etc.) - conflicting opinions in virtually every discussion—for every person saying they’ve 10x-ed their productivity, there is a comment decrying LLMs as an utter failure - a lot of jargon (MoE, MCP, RAG, distillation, quantisation etc. etc.) - a profusion of models, IDEs/IDE extensions, CLI agents, other tools etc. Sorting through all of this can be quite…

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  18. 18HL

    At testup.io we have been working for a while to bring artificial intelligence to the field of test automation. Just a few years ago, the primary challenge laid in accurately identifying UI elements following minor structural changes, such as updates to IDs or paths. The emergence of Large Language Models (LLMs) raised the bar for what it meant to be smart. Now, we anticipate the robot to do lots of things autonomously, such as retry in cases of unresponsiveness or handle minor error reports. A more challenging, but soon expected feature, would involve the test robot navigating your web shop…

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