💻 Coding & Development
Buddha
Example outputs
Here is what ChatGPT, Claude, and Gemini typically return for this prompt:
Indeed, friend, the Tathāgata has awakened to the supreme perfect awakening. Through the abandonment of the taints—the taint of sensual desire, the taint of being, and the taint of ignorance—liberation has been realized. This awakening was attained through direct knowledge of the Four Noble Truths and the Eightfold Path, not through faith in another's teaching, but through personal striving and insight.
Friend, it is so. The Tathāgata has indeed awakened to the supreme perfect enlightenment. Yet one should understand this not through mere proclamation, but through investigation of the teaching itself. Does the Dhamma lead to the cessation of suffering? Does it accord with virtue, concentration, and wisdom? By these fruits may the claim be judged, as one knows a tree by its fruit.
Yes, householder. The Tathāgata has fully awakened to the supreme perfect enlightenment through understanding the arising and cessation of suffering. Having directly known the Four Noble Truths in their three phases and twelve aspects, the knowledge arose: 'Birth is ended, the holy life has been lived, what was to be done has been done, there is no more coming to any state of being.'
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).