IdeaWell

Project ideas from Hacker News discussions.

The Gemini app is now available for Windows

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Theme 1 – Frustrating / basic UX
- “The Spark feature's UI isn't as good as the others… unless I use MCP to manipulate files on my computer, local file manipulation isn’t possible.” – jdw64
- “My biggest bugbear with Gemini is that I can’t organise chats into folders and projects… the UX is basic beyond belief.” – _fw
- “I get frustrated… In comparison all of the AI stuff for Google looks a little bit confusing and frustrating.” – valdrinNereth

Theme 2 – Fragmentation & likely abandonment
- “Google apps don't evolve, they fragment and then die. I'd give this one a year or two at most.” – esperent
- “There will be a new replacement app to combine them, but it will only handle around 60% of the functionality of both. All three will receive no further updates.” – happymellon
- “And will be EoL'ed in… one, two years?” – dboreham

Theme 3 – Performance / compatibility problems
- “Doesn’t work on Windows ARM machines.” – pverghese
- “Specifically a stack overflow bug. So the app won’t start… running through the prism emulation layer on Windows for ARM.” – pverghese
- “I've been having resource usage and stuttering issues on browser… It seems a little bit better on desktop.” – valdrinNereth

🚀 Project Ideas

Generating project ideas…

Gemini Unified Workspace

Summary

  • A single desktop application that combines Gemini chat, Antigravity browser automation, and Spark file‑agent features, addressing fragmented UI and lack of local file manipulation.
  • Core value proposition: seamless, privacy‑first AI workflow that lets users chat, run screen‑aware actions, and edit files locally without leaving the app.

Details

Key Value
Target Audience Power users, developers, and knowledge workers who rely on Gemini for coding, research, and productivity
Core Feature Unified chat + sandboxed file system + screen capture/automation with opt‑out data training
Tech Stack Electron (or Tauri) for cross‑platform UI, Gemini API, Model Context Protocol (MCP) for local file ops, Rust/Wasm for sandbox, optional Llama.cpp for offline fallback
Difficulty Medium
Monetization Revenue-ready: Subscription $9/mo per user (teams $15/mo)

Notes

  • HN users complained: “The Spark feature's UI isn't as good as the others… local file manipulation isn't possible unless I use MCP” and “I still can't stand the fact that … must allow sharing data for training.”
  • Potential for discussion: Could become the “everything app” users want, reducing fragmentation and enabling offline‑first AI workflows.

MCP Agent Builder

Summary

  • A visual low‑code tool that lets non‑programmers create and run Gemini‑driven file‑manipulating agents via the Model Context Protocol, removing the need to hand‑craft MCP scripts.
  • Core value proposition: democratizes AI automation of local tasks (rename files, process images, run scripts) while providing a safe sandbox and instant preview.

Details

Key Value
Target Audience Developers, power users, and citizen developers who want to automate local file workflows with Gemini
Core Feature Drag‑and‑drop workflow builder that generates MCP-compatible agent code, with live preview and one‑click execution
Tech Stack React + TypeScript frontend, Node.js backend, Gemini API, MCP library, Tauri for desktop packaging, Docker for sandbox isolation
Difficulty High
Monetization Revenue-ready: Freemium – free tier limited to 5 agents/mo, Pro $12/mo unlimited agents and team sharing

Notes

  • Commenters noted: “Unless I use MCP to manipulate files on my computer, local file manipulation isn't possible” and “It would be great if Gemini could actually work across files and tasks on your computer.”
  • Potential for discussion: Lowers barrier to AI‑powered desktop automation, sparking new productivity hacks and possible marketplace of shared agents.

PrivateChat Organizer for Gemini

Summary

  • A privacy‑focused overlay/local‑storage add‑on that lets users tag, folder, search, and export Gemini chats without opting into data‑for‑training, and can run a small local model for offline summarization.
  • Core value proposition: gives users control over their chat data while preserving Gemini’s powerful responses, addressing the “must share data to train” frustration.

Details

Key Value
Target Audience Privacy‑conscious Gemini users (researchers, journalists, professionals) who dislike forced data sharing
Core Feature Local encrypted chat database, folder/project tagging, search, export, and optional offline Llama‑2‑based summarization
Tech Stack Electron/Tauri UI, IndexedDB or SQLite for local storage, AES‑256 encryption, optional llama.cpp integration, Gemini API passthrough
Difficulty Low
Monetization Hobby

Notes

  • HN users said: “I still can't stand the fact that … must allow sharing data for training… it’s pretty much unusable for me” and “I can’t organise chats into folders and projects.”
  • Potential for discussion: Provides a GDPR‑friendly alternative that could be bundled with Gemini or offered as a standalone extension, fostering trust and longer‑term adoption.

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