nowfound

Alternatives

Products that do what HashCortX does

Agentic Local Workspace

  1. 1
    Hashnode250

    A friendly and inclusive Q&A network for coders

    2015

  2. 2

    Codex-powered agents for teams.

    Apr 2026

  3. 3

    The open-source kernel for coding agents

    10d ago · akonlabs.com

  4. 4

    Stay connected with the global developer community

    2021

  5. 5
    BearDrive191

    The open-source shared folder for your team's AI agents

    25d ago · beardrive.ai

  6. 6
    HASH127

    Build complex simulations quickly with modular components

    2020

  7. 7

    The first truly agentic AI sidebar for Google Workspace™

    May 2026

  8. 8

    One workspace for Claude, Codex, Gemini and your stack

    May 2026

  9. 9
    Pixcode76

    A self-hosted control room for AI coding agents

    May 2026

  10. 10

    APIs for building AI chat and search

    Feb 2026

  11. 11
    Cortex70

    Run multiple claude-code agents from YAML config

    Jan 2026

  12. 12HA
  13. 13UA

    Recently several AI labs have published experiments where they tried to get AI coding agents to complete large software projects. - Cursor attempted to make a browser from scratch: https://cursor.com/blog/scaling-agents - Anthropic attempted to make a C Compiler: https://www.anthropic.com/engineering/building-c-compiler A few weeks ago I posted xmloxide, an agent-made Rust replacement for libxml2 made by pointing Claude code at the libxml2 test suite: https://news.ycombinator.com/item?id=47201816 curl is arguably the most widely deployed…

    Mar 2026 · github.com

  14. 14IB

    Claw-Coder is an AI agent that runs locally on your laptop and has access to powerful tools instead of configuring claude or codex to use a local model just use claw-coder. Why was claw-coder created? Answer: To solve the problem of privacy and security. When you use an agent that is configured with a cloud model like codex, cursor, Claude etc. You are not just getting the agent but you are giving up your codebase to train an llm which is a bit concerning and this reduces trust in the technology called AI but now another problem comes in performance when you switch to a local model that is…

    May 2026

  15. 15
    ai.diy8

    Browser-owned AI workspace for cloud and local models

    16d ago · tryaidiy.com

  16. 16IB

    Claw-Coder is an AI agent that runs locally on your laptop and has access to powerful tools instead of configuring claude or codex to use a local model just use claw-coder. Why was claw-coder created? Answer: To solve the problem of privacy and security. When you use an agent that is configured with a cloud model like codex, cursor, Claude etc. You are not just getting the agent but you are giving up your codebase to train an llm which is a bit concerning and this reduces trust in the technology called AI but now another problem comes in performance when you switch to a local model that is…

    May 2026

  17. 17NO

    Hi, I'm Karl. Greg and I spent the last year building Nimbalyst, an open-source local desktop workspace for working with coding agents. We want to give agents and humans one place to work together with maximum bandwidth and context, instead of Obsidian for plans, Excalidraw for diagrams, Codex app or Conductor for session management, and Linear for tasks. So we integrated: - Visual editors for markdown, diagrams, mockups, data models, CSV, code, and your own custom extensions - Red/green diff review with per-block accept/reject when an agent makes changes - Session manager with…

    May 2026 · github.com

  18. 18SR

    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

  19. 19HC
  20. 20AO

    Hi HN, We built one of the largest RAG set-ups that exist toady with Usul.ai (6B tokens). We started by using langchain and llamaindex, they were able to get us to a prototype in a couple of days, but took 3 months of taking pieces apart and optimizing them to make it perform well at such large scale. We put all of these learning into an MIT licensed open-source project — Agentset. Our goal to let people get production quality RAG w/o having to understand or optimize the underlying pieces. It supports 22 file formats, agentic search, deep research, citations, and a UI out of the box.…

    Oct 2025 · github.com

  21. 21BS

    Built a free open source agentic CLI tool for financial modeling & analysis. Hadn't played around with real equity valuation modeling for awhile and wanted to build tooling to get myself back into the game. Bull.sh lets you query & store 10-Qs, 10-K in a local vector store to chat with them, build investment thesis from scratch or build full framework models through the CLI to export into excel. It's open source, just requires your own Anthropic API key and (optionally) AlphaVantage Free API key if you want save some tokens from scraping. Feel free to play around with it. Some ideas I have…

    Jan 2026 · github.com

  22. 22AA

    We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS. What’s in the repo: • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI • Strands-based flows with observability using OTEL & Arize • Evaluation with LLM-as-judge and cost/performance regressions • Built with Bedrock, S3, Step Functions, and more GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-... Would love your thoughts — feedback, issues, and stars welcome!

    2025 · github.com

  23. 23IM

    Hey HN! We've built an AI powered technical writer that allows you to automate creating comprehensive, MDX-formatted documentation with just a few clicks. How It Works: - Upload screenshots: Start by uploading screenshots of your product. - Describe features: Provide a brief description of the features you want documented. - Generate documentation: Our AI will analyze your inputs and automagically generate detailed documentation in MDX format. - Deploy instantly: With just one click, you can deploy your new documentation online. Continuous Integration: Automated updates: Integrate our npm…

    2024 · app.paparazzidocs.com

  24. 24MA

    Hello there HN I experimented with agentic coding recently and I felt the need to track more contextual data by project. Also I felt the need to be able to go beyond the 1D chat to communicate with agents. So I created a local document memory, that is discoverable by agents themselves. The CLI is designed to be easy to pick up by agents. It allows humans to collaborate too by reading / searching / editing documents in the store. I have a Mac native GUI in the review process, I hope it will show up in the App Store soon. You can try it easily, instructions here:…

    Jun 2026 · metabrain.eu

Ranked by how close each launch is in meaning, then by votes. Refine with a description →