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Alternatives

Products that do what Cogitorium does

Agent workflows with a model per agent — and a leash on each

  1. 1AI

    Hi HN, we’re Sai and Aayush, and we’re building Hypercubic (https://www.hypercubic.ai/), bringing AI tools to the mainframe and COBOL world. (We did a Launch HN last year: https://news.ycombinator.com/item?id=45877517.) Today we’re launching Hopper, an agentic development environment for mainframes. You can download it here: https://www.hypercubic.ai/hopper, and you can also request access and immediately get a mainframe user account to play with. There's also a video runthrough at https://www.youtube.com/watch?v=q81L5DcfBvE.…

    May 2026 · hypercubic.ai

  2. 2
    Hopper100

    First agentic development environment for mainframe/COBOL

    May 2026

  3. 3AD

    I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…

    May 2026 · github.com

  4. 4

    The context hub for your agents

    Feb 2026

  5. 5

    The fastest workflow for developing with AI

    26d ago · agent-manager.dev

  6. 6
    BU138

    Openclaw in the cloud

    Mar 2026

  7. 7GF

    hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…

    May 2026 · github.com

  8. 8

    One workspace for Claude, Codex, Gemini and your stack

    May 2026

  9. 9

    A cloud workspace for coding agents from your phone

    Jul 2026 · cosyra.com

  10. 10
    Flare120

    The graph-first IDE and interactive map for agentic coding

    12d ago · github.com

  11. 11

    Codex-powered agents for teams.

    Apr 2026

  12. 12

    Your AI agents team, terminals, notes: one infinite canvas

    Jul 2026 · agentgrid.sh

  13. 13AD

    We recently built 2draw, a Drawful-style game where players draw on a shared canvas and race to guess each other's drawings, on tldraw, an infinite-canvas SDK for React. We started wondering what it would take to put an agent in that loop, as an opponent or a rival guesser, and dug into how an agent could read and draw on a tldraw canvas. That research turned into: Agent draw, a tool that lets an agent draw to the canvas for you while you present. You can try it right now, or grab the source: - Live demo: https://tldraw-agent-draw-demo.james-664.workers.dev - Source:…

    Jul 2026 · techstackups.com

  14. 14SR

    Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…

    Jul 2026 · shikigami.dev

  15. 15OA

    Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…

    Jul 2026 · oodle.ai

  16. 16CA

    I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!

    Sep 2025 · infrastructureas.ai

  17. 17

    Your AI has your code's text, never its map. Fix that.

    Jun 2026 · luuuc.github.io

  18. 18

    See what your AI coding agents think, cost and do

    Jul 2026 · tokentelemetry.com

  19. 19
    GitHub10

    Local-first memory for your AI coding agent

    Jun 2026 · github.com

  20. 20
    hob14

    The independent workspace for professional agent work

    Jul 2026 · hob.dev

  21. 21

    Version Control For AI Agents

    Jul 2026 · cognatoai.com

  22. 22AA

    Hey HN! We've just open-sourced Agent, our framework for running computer-use workflows across multiple apps in isolated macOS/Linux sandboxes. After launching Computer a few weeks ago, we realized many of you wanted to run complex workflows that span multiple applications. Agent builds on Computer to make this possible. It works with local Ollama models (if you're privacy-minded) or cloud providers like OpenAI, Anthropic, and others. Why we built this: We kept hitting the same problems when building multi-app AI agents - they'd break in unpredictable ways, work inconsistently across…

    2025 · github.com

  23. 23RA

    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

  24. 24

    Agentium brings models, memory, tools into one TS runtime.

    May 2026 · agentium.in

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