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Alternatives

Products that do what Coda by Conductor Quantum does

Solving problems using quantum computing & natural language

  1. 1

    Q3AS, deployment & execution of quantum algorithms by Aqora

    2024

  2. 2
    Replicas239

    Run Claude Code and Codex in the cloud

    Jun 2026

  3. 3

    The power of Codex with local, self-hosted models and voice

    Jul 2026 · opencodesuper.app

  4. 4

    Codex now runs natively on Windows with secure sandbox

    Mar 2026

  5. 5
    SuperHQ95

    Run AI coding agents in real microVM sandboxes

    Apr 2026

  6. 6QJ

    2020 · quantumjavascript.app

  7. 7

    Amazon's first quantum computing chip

    2025

  8. 8

    Open-source alternative to Codex & Claude Code

    May 2026

  9. 9
    Boxes.dev112

    Run Claude Code and Codex in your own cloud environment

    Jun 2026

  10. 10

    State of the art text understanding for developers

    2018

  11. 11

    CLI agent that builds full-stack mobile apps from terminal

    May 2026

  12. 12
    Radiq87

    Product intelligence for the autonomous coding era

    May 2026

  13. 13
    Termly82

    Mobile + voice access for Claude Code and terminal AI tools

    Nov 2025

  14. 14OS

    We’ve just released an open-source library for solving the Maximum Independent Set (MIS) problem with neutral atom quantum computing, running on both quantum processing units (QPUs) and classical hardware, thanks to emulators. This project is the result of collaboration between Pasqal, academic researchers, and industry partners, aiming to make it practical to experiment with quantum approaches to hard combinatorial optimization tasks. The MIS problem appears in real-world scenarios like scheduling, resource allocation, and network optimization, areas where classical solvers often struggle…

    2025

  15. 15CT

    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

  16. 16TT

    Hey HN, this is deepan from trulytyped (https://trulytyped.com). I am building a document writing app which makes it extremely easy to figure out how a document was created. Now that any text can be AI generated, how do you tell if something was actually generated or composed. It is impossible to detect AI after a piece of text has been generated. No amount of watermarking, linguistic checks or vibe checks work consistently. The AI detectors that schools and journals use are easy to bypass. Why do we need to solve this problem - First of all, this is not an anti-AI stance. I have…

    May 2026 · trulytyped.com

  17. 17RA

    Hey HN, I built SuperHQ, an app that lets you run coding agents in local sandboxes (powered by Shuru). No custom UI wrapping the agents, they run as CLI/TUI like they were designed to. It just provides you the tools most of us (okay, maybe just me?) needed for running multiple coding agents in parallel without worrying about breaking your system or work environment. Each agent runs in its own microVM. You mount your projects in, writes go to a tmpfs overlay so your host is never touched, and you get a unified diff view to accept or discard changes. API keys never enter the sandbox, they…

    Apr 2026 · superhq.ai

  18. 18LQ
  19. 19HP

    Hi HN! I'm building Hopsule. If you use AI coding tools like Cursor, Copilot, or Claude, you’ve probably seen this happen: The AI writes good code - but it ignores your architecture. It doesn’t know: - why you chose a specific pattern - which conventions your team agreed on - which decisions are already locked in So it falls back to generic patterns, outdated examples, or random GitHub training data. Over time this slowly breaks the consistency of the codebase. Most teams try to fix this with: - giant Markdown files - wiki pages - long prompts - Slack threads But those aren't…

    Mar 2026

  20. 20AR

    Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…

    May 2026 · agents-cli.sh

  21. 21EE

    Hi HN, we have recently completed a research project on how to encrypt emails with post-quantum secure algorithms as well as Forward Secrecy. We'd love to hear your feedback and discuss technical issues. The paper can be found here: https://eprint.iacr.org/2021/875

    2021

  22. 22VC

    TLDR: got tired of my desk, so now I touch grass while coding from my watch. Ever since the 2021 GH Copilot beta saved me from dual carpal tunnel, I figured AI's main benefit in coding would be cutting typing while keeping productivity. That's turned out true; no one writes their own code lately. Why wouldn’t you have AI do the first draft? Why not your updates too? I expected phone coding to rise next, but tiny keyboards wreck your hands even faster. To put this into practice, I started leaving my Windows desktop on 24/7 and SSHing in from my phone, yet the problem just transformed:…

    Jun 2026 · dashvox.ai

  23. 23
    JoinAI2

    LeetCode for ML/AI Coding Problems

    12d ago · joinai.com

  24. 24MN

    Hey HN, I'm Naveen, one of three co-founders building Mercury (mercury.build). We spent the last year in deploying AI agents for teams in large enterprises. The agents themselves worked fine. The problem was managing them. You've got Claude Code in a terminal, a research agent in a browser tab, a Slack bot somewhere else, a scheduling assistant in yet another window. It's chaotic. There's no single place to see what's running, who's doing what, or how things connect. As the number of agents grows, this gets unmanageable fast. Mercury is a canvas where you bring your agents and humans…

    Apr 2026 · mercury.build

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