AIConsole, an Open-Source Desktop AI Editor to Customize Your Workflow

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Hey HN! I was frustrated with feeling like an assistant to most AI systems and chats that I used. All I wanted was to have a fully controllable AI System that will potentially do everything for me, and that I can easily teach to do new things and get my context without constant copy and pasting. This is why, together with my team, I built AIConsole, an open-source desktop AI editor that allows you to create your own AI toolset. Giving you the power of AI personalization right on your local machine. Imagine a desktop app that can schedule your meetings, automate responses, craft unique content, code snippets, or even edit code – all while respecting your privacy and preferences. What does it do? * Runs code locally - it can fully operate within your local environment with the tasks your machine can execute – it can do everything that is accessible from your machine. * Gets better the more you put into it - teach it once to perform a task and AIConsole retains the skill indefinitely. * Use your notes to show AI how to complete and automate tasks. * Expert level prompt engineering - AIConsole leverages a multi-agent Retrieval-Augmented Generation (RAG) system not based on a vector database, akin to expert prompt engineering. * Fully open-sourced – This software maintains privacy and only uses dedicated LLM apis with well known privacy policies - and you can verify that yourself * Share and collaborate on your tools with the community - you can create and share your domain-specific AI tool using Github, Google Drive etc. While we are at an early stage, we have a stable desktop application, and are working on sharing actual use-cases and further improving the tooling around it. We’ve got a lot planned on our roadmap, including a full IDE-like experience, generative interfaces, and open source LLMs support. Get it here: https://aiconsole.ai Discord: https://discord.com/invite/gYPJqFC7hF Repository: https://github.com/10clouds/aiconsole Newsletter: https://cielecki.substack.com/ My Twitter: twitter.com/mcielecki Manifesto: https://cielecki.substack.com/p/say-goodbye-to-tech-giants I would love to hear your feedback.

Visit product View on Hacker NewsDec 4, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agent, google · Missing: agents, macos, cursor

97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal, google · Missing: mobile apps, ios, entrepreneurs

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, collaborate · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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