Unlocking Developer Productivity: A Product Manager’s Guide to Running Gemini & Claude from the Windows CLI

Clive Lancaster

Clive Lancaster

— 3 min read

Prerequisites: Setting Up Your Windows Environment

Before we install anything, ensure your Windows machine is CLI-ready:

  1. PowerShell or Command Prompt: Windows 10/11 comes with PowerShell—use it for better scripting. Open it via Win + X > Windows PowerShell.
  2. API Keys: You'll need accounts with Google (for Gemini) and Anthropic (for Claude). We'll cover key setup next.

Install Node.js and npm: Most LLM CLIs are Node-based for easy global installs. Head to nodejs.org and download the LTS version for Windows. Run the installer, then verify with:text

node --version
npm --version

This gives you npm, the package manager we'll use.

Pro tip: If you're behind a corporate firewall, configure npm's proxy with npm config set proxy http://your-proxy:port.

Installing and Using the Gemini CLI

Google's Gemini is a multimodal beast—great for text, code, and even image analysis. The official-ish CLI wrapper is @google/gemini-cli, a lightweight Node tool that taps into the Gemini API.

Step 1: Installation

Fire up your terminal and run:

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npm install -g @google/gemini-cli

This installs the CLI globally. If you hit permission errors (common on Windows), run PowerShell as Administrator.

Verify:

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gemini --version

Step 2: API Key Setup

  1. Go to Google AI Studio and create a free API key.

Set it as an environment variable:text

$env:GOOGLE_API_KEY = "your-api-key-here"

For permanence, add it to your user environment variables via System Properties > Advanced > Environment Variables.

Step 3: Basic Usage

Chat away! Here's a simple query:

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gemini "Explain quantum entanglement in simple terms."

Output might look like:

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Quantum entanglement is like two particles sharing a secret handshake—they're connected so that what happens to one instantly affects the other, no matter the distance. It's spooky action at a distance, as Einstein called it!

Advanced tricks:

  • Stream responses: gemini --stream "Write a Python script for Fibonacci."
  • Model selection: gemini --model gemini-1.5-pro "Your prompt here."
  • Pipe input: echo "Debug this code: print('hello')" | gemini --fix

Gemini shines for creative tasks—try gemini --image path/to/image.jpg "Describe this photo." if you have multimodal enabled.

Installing and Using the Claude CLI

Anthropic's Claude is your thoughtful, safety-focused LLM companion, excelling at reasoning and ethical AI chats. While Anthropic doesn't have an "official" CLI, the community-favorite @anthropic/claude-cli (built on their SDK) makes it seamless.

Step 1: Installation

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npm install -g @anthropic-ai/claude-code

Admin mode if needed. Check:

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claude --version

Step 2: API Key Setup

  1. Sign up at console.anthropic.com and generate an API key (free tier available with limits).

Export it:text

$env:ANTHROPIC_API_KEY = "your-api-key-here"

Persist via environment variables, same as above.

Step 3: Basic Usage

Kick off a conversation:

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claude "What's the best way to optimize a React app?"

Expect a detailed, structured response:

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To optimize a React app:
1. Use React.memo for expensive components.
2. Implement code-splitting with React.lazy.
3. Leverage memoization with useMemo/useCallback.
...

Cool features:

  • Conversation mode: claude --chat for interactive sessions (type /exit to quit).
  • System prompt: claude --system "Act as a senior dev mentor." "Your question."
  • JSON output: claude --json "Summarize this article: [paste text]" for easy parsing in scripts.

Claude's strength? Long-context handling—feed it entire codebases with claude < file.txt.

Benefits: Why Bother with LLM CLIs?

Switching to terminal-based LLMs isn't just geeky—it's practical. Here's why you'll love it:

  • Speed and Efficiency: No browser tabs or GUIs slowing you down. Queries fire in milliseconds, perfect for quick lookups during coding sprints.
  • Scripting Superpowers: Integrate into pipelines. Example: git diff | claude --fix > fixes.patch for AI-assisted code reviews.
  • Offline-ish Workflow: Once installed, everything's local except API calls—great for focus modes.
  • Customization: Chain with tools like jq for JSON, ffmpeg for media, or even curl for hybrid setups.
  • Learning Curve: If you're comfy with npm and env vars, you're set. Plus, it builds CLI muscle for DevOps pros.
  • Cost-Effective: Free tiers for light use; scale to paid for heavy lifting without desktop app bloat.

In short, it's like having a genius intern in your terminal—always on call, zero context-switching.

Risks: The Double-Edged Sword of Cloud LLMs

AI is magic, but not without pitfalls. Tread wisely:

  • Privacy Concerns: Your prompts (and data) hit cloud servers. Sensitive code or personal info? Risk leaks or training data use. Mitigation: Anonymize inputs, review ToS (Google/Anthropic claim no training on API data, but verify).
  • API Costs and Limits: Free tiers cap at ~60 queries/min for Gemini, 100K tokens/day for Claude. Overages rack up—$0.002/1K tokens for Claude's base model. Track usage via dashboards.
  • Dependency Hell: Outages (e.g., Google's API hiccups) halt your flow. No local fallback unless you pivot to Ollama.
  • Security Snags: API keys in env vars are safer than hardcoding, but a compromised machine exposes them. Use vaults like Azure Key Vault for enterprise.
  • Hallucinations and Bias: LLMs fib or skew responses. Always fact-check critical outputs—don't deploy unvetted AI code.
  • Windows Quirks: Path issues with spaces or UAC prompts can frustrate installs. Test in WSL if native Windows feels clunky.

Bottom line: Great for prototyping, but audit for production.

Wrapping Up: Level Up Your Terminal Game

There you have it—Gemini and Claude CLIs installed, humming, and ready to boost your Windows workflow. Start small: Pick one tool, run a daily prompt, and script something fun. Before long, you'll wonder how you coded without them.

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