NemoClaw Knowledge Wiki

Use Gemini Deep Think

4 min read

https://www.youtube.com/watch?v=lWAH-gCQRbA Here is a summary of the video introducing Google’s Gemini 3 Pro Deep Think, covering how it works, its best use cases, practical demos, and the creator’s current AI toolset.

Gemini 3 Pro Deep Think: Overview

Gemini 3 Pro Deep Think is a new mode for Google’s latest AI model. Unlike standard LLMs that think linearly to provide the first available answer, Deep Think explores multiple answers simultaneously using a “swarm” of AI agents. It researches, refines, and reflects on these options to provide the highest quality output possible.

Key Characteristics

  • How it works: It acts as a “swarm of AIs” attacking a prompt from different angles, then consolidates the best findings.
  • Strengths: Best-in-class performance for math, science, logic, complex reasoning, and generating novel results.
  • Weaknesses: High latency. It takes a long time to “think,” making it unsuitable for quick back-and-forth coding or instant chat.

When to Use This Model

The creator suggests using Deep Think effectively as a “Senior Researcher” or “Senior Strategist” rather than a quick chat assistant. Ideal Use Cases:

  • Complex 3D simulations and physics modeling.
  • Abstract questions requiring “gray area” thinking (not black and white).
  • Heavy math or computer science logic tasks.
  • Scenarios where you need multiple perspectives or deep critiques.

Demo 1: The 3D Orbital Simulator

To demonstrate the model’s reasoning capabilities, the creator prompted it to build a browser-based, physically accurate 3D orbital space simulator using Three.js in a single shot.

  • The Process: The AI did not just write code; it first defined the physics model (Newton’s Law of Universal Gravitation), set up the math, created an architecture plan, and then wrote the JavaScript.
  • The Result: A fully functional, interactive 3D simulation of a spaceship orbiting a star with realistic physics, launch controls, and trajectory trails—all generated from one prompt.

Demo 2: The “Vibe Coder” Strategy Prompt

To show a practical day-to-day use case, the creator used a specific prompt to generate realistic app ideas for a solo developer.

  • The Prompt Strategy: The user assigned the AI the role of a “brutally honest product strategist.” The prompt included specific constraints (skill level, time available, revenue goals) and explicitly told the AI to reject unrealistic inputs.
  • The Result:
    1. Honesty: The AI pushed back on the user’s input, noting that making $10k/month working only 1 hour a day is “usually a delusion.”
    2. Quality Ideas: It avoided generic “Start a SaaS” advice and offered specific concepts like a marketplace for AI cursor rules (“RuleBook”) or a “Context Cleaner” for GitHub repos (“RepoSensei”).
    3. Detailed Plans: For each idea, it provided a go-to-market strategy, tech stack, and risk analysis.

The Creator’s Current AI Toolset

At the end of the video, the creator shared his personal list of which AI models he currently uses for specific tasks:

Graph View