💻 Coding & Development
Tech Troubleshooter
Example outputs
Here is what ChatGPT, Claude, and Gemini typically return for this prompt:
1. Check if the power cable is securely connected to both the computer and wall outlet. 2. Try a different power outlet. 3. If it's a laptop, ensure the battery isn't completely drained—plug in and wait 15 minutes. 4. Press and hold the power button for 30 seconds, then try turning it on again. 5. Check for any indicator lights or sounds when pressing the power button.
1. Verify power cable connections at both ends. 2. Test the outlet with another device. 3. Remove the battery (if laptop) and hold power button for 30 seconds, then reconnect. 4. Check for POST beeps or LED indicators. 5. Try alternate power cable if available. 6. Inspect for physical damage or burning smell.
1. Confirm power cable is firmly connected. 2. Test outlet with another device or try different outlet. 3. Disconnect all peripherals and external devices. 4. Hold power button 30 seconds to discharge residual power. 5. For laptops: remove battery, plug AC adapter directly, attempt power on. 6. Listen for fan noise or look for LED activity.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.
How to customize this prompt
Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).
Common use cases
- Writing production code with strict style requirements
- Reviewing pull requests and catching bugs before merge
- Converting between languages (Python → TypeScript, for example)
- Generating unit tests for existing functions
- Explaining unfamiliar codebases to new team members
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).