IdeaWell

Project ideas from Hacker News discussions.

Gemini 3 Deep Think

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

1. Model‑to‑model performance chatter
Users are constantly comparing the newest Google Gemini releases to Claude, GPT‑5.x, and Opus, especially on hard benchmarks.

“Google has definitely been pulling ahead in AI over the last few months. I've been using Gemini and finding it's better than the other models” – Metacelsus
“Arc‑AGI 84.6 % (vs 68.8 % for Opus 4.6)” – lukebechtel

2. Agentic‑workflow debate
A large portion of the discussion centers on how well the models can act as agents or be wrapped in agent harnesses.

“They don't focus on 'agentic this' or 'specialised that', but the raw models, with good guidance are workhorses.” – NitpickLawyer
“Gemini 3 Deep Think is built on top of Gemini 3 Pro, adding subagents” – aliston

3. Product‑experience complaints
Many commenters complain that Google’s interface, privacy handling, and subscription model are clunky or intrusive.

“Gemini's UX … is the worst of all the AI apps.” – Razengan
“They use Russian propaganda sources for answers and switch to Chinese mid‑sentence.” – wiseowise

4. Benchmark validity & AGI hype
The community is skeptical about the usefulness of ARC‑AGI and similar tests as real indicators of general intelligence.

“Arc‑AGI is a useless visual puzzle benchmark.” – saberience
“Solving Arc‑AGI doesn’t mean AGI.” – modeless

These four themes capture the bulk of the discussion: performance comparisons, agentic capabilities, user‑experience frustrations, and the debate over whether current benchmarks truly measure general intelligence.

🚀 Project Ideas

Generating project ideas…

Gemini Project Manager Extension

Summary

  • Adds persistent project tabs, context history, and file upload handling to the Gemini web interface.
  • Solves frustration with context loss, lack of projects, and unreliable file uploads.
  • Core value: seamless, privacy‑first workflow for developers and researchers using Gemini.

Details

Key Value
Target Audience Gemini users (developers, researchers, students)
Core Feature Browser extension that injects a project sidebar, auto‑saves conversation context, and provides robust file upload/download with local encryption
Tech Stack TypeScript, React, Chrome/Firefox extension APIs, IndexedDB, WebCrypto
Difficulty Medium
Monetization Revenue‑ready: $5/month for premium features (advanced analytics, multi‑device sync)

Notes

  • Users complained: “Gemini forgets context mid dialog” and “file upload fails with vague errors.”
  • A project‑based UI would let them keep long‑running sessions intact, matching the “projects” feature of ChatGPT.
  • The extension can be open‑source, encouraging community contributions and quick adoption.

Agentic Workflow Builder (Open‑Source)

Summary

  • Drag‑and‑drop UI to design best‑of‑N, pass@N, and map‑reduce agent workflows for any LLM (Gemini, GPT‑5, Claude, etc.).
  • Addresses pain points around “agentic workflows” and “sub‑agent orchestration” that many users find hard to set up manually.
  • Core value: democratizes advanced agentic reasoning without writing code.

Details

Key Value
Target Audience AI practitioners, data scientists, developers building LLM‑powered apps
Core Feature Visual workflow editor, built‑in agent templates, real‑time result aggregation, export to Python/Node
Tech Stack Vue.js, Node.js, Docker, OpenAI/Anthropic/Google API wrappers, Redis for task queue
Difficulty High
Monetization Revenue‑ready: $10/month for hosted SaaS version with priority support

Notes

  • Commenters noted “Gemini is not agentic” and “need to combine sub‑agents.”
  • The tool would let users spin up a swarm of sub‑agents, merge outputs, and iterate until a goal is met, directly addressing the “agent swarm” idea.
  • Community can contribute new agent templates, making it a living ecosystem.

Biology Q&A Assistant (Safe & Unrefusal)

Summary

  • Dedicated LLM interface that answers biology questions without refusing harmless queries, using a curated biology knowledge base.
  • Solves frustration that “Gemini refuses to answer harmless biology questions.”
  • Core value: reliable, domain‑specific assistant for researchers and students.

Details

Key Value
Target Audience Biology researchers, students, educators
Core Feature Prompt‑templating, knowledge‑base retrieval, refusal‑override policy, citation generation
Tech Stack Python, FastAPI, LangChain, SQLite, OpenAI/Claude API, HuggingFace embeddings
Difficulty Medium
Monetization Hobby (open‑source) with optional paid API tier ($0.02/1000 tokens)

Notes

  • Users expressed “Gemini doesn’t answer harmless biology questions.”
  • By integrating a vetted biology corpus and a refusal‑override policy, the assistant can provide accurate answers while staying within policy.
  • The tool can be deployed as a lightweight web app or integrated into existing research workflows.

3D Parametric Modeling Assistant

Summary

  • LLM‑powered assistant that generates OpenSCAD code from natural‑language prompts, with iterative debugging and real‑time preview.
  • Addresses pain points: “LLMs hallucinate 3D geometry” and “need a full workflow for CAD generation.”
  • Core value: turns complex CAD tasks into conversational design sessions.

Details

Key Value
Target Audience Hobbyists, makers, product designers, educators
Core Feature Prompt → OpenSCAD code, auto‑debugging loop, 3D preview in browser, export to STL
Tech Stack JavaScript, Three.js, Node.js, OpenAI API, Docker for OpenSCAD compiler
Difficulty High
Monetization Revenue‑ready: $7/month for premium features (advanced preview, version history)

Notes

  • Commenters noted “LLMs fail to debug 3D geometry” and “need a full workflow.”
  • The assistant would let users iteratively refine models, automatically detect syntax errors, and visualize changes, turning the “screenshot‑vibe coding” workflow into a smooth experience.
  • Integration with popular slicers (e.g., Cura) would make it immediately useful for 3D printing enthusiasts.

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