Prompting Coding AIs

/ all-scribbly, coding, notes / By

Prompting Coding AIs

🔹User Messages vs. Code Completions**

  • User Messages: These are the messages you send to the model. The Developer Plan includes 600 messages per month. This includes any prompt or follow-up you write.
  • Code Completions: These are unlimited under this plan. This refers to the model generating or completing code (in a coding environment like VS Code or in the playground). Completions don’t count against your message quota.

⚠️ Important: The 600 message limit only applies to user-initiated messages, not the AI’s replies or completions.

🔹Context Engine**

  • The Context Engine powers the model’s ability to remember, analyze, and refer back to relevant information across your conversation (or across multiple conversations if memory is on).
  • It ensures that even long, complex discussions stay coherent and on-topic.
  • This is what enables features like memory, long context, and smart recall.

🔹MCP & Native Tools

MCP likely refers to Model Capabilities Platform or similar internal naming — this part is a bit ambiguous publicly, but practically, it means:

  • You have access to advanced tools embedded within ChatGPT.

  • These include tools like

    • Python (code interpreter/advanced data analysis)
    • Image generation
    • Image understanding
    • Web browsing (if enabled in your tier)
    • File uploading/analysis
    • AI-assisted document and code editing

The phrase “Native Tools” refers to these integrated tools that are built right into ChatGPT and don’t require external plugins.

🔹Next Edit**

  • Next Edit is a feature that allows you to iterate on generated content (text, code, etc.).
  • After a response, you can click “Next” or “Edit” to ask for a change, tweak, or alternative — and you can do this as many times as you want under this plan.

Let me know if you want a recommendation on how to use those 600 messages wisely or if you’re evaluating whether the plan fits your workflow.

Great — here are super-efficient prompt templates tailored to coding, debugging, writing, and data analysis. You can copy, tweak, and reuse these to save messages and get better answers faster.

🔧For Coding Tasks**

🟦 Prompt: Code Generator with Context

“Create a React component called UserCard that:

  • Takes name, avatar, and bio as props

  • Uses Tailwind for styling

  • Has a hover effect to show full bio

    Output the complete code and explain anything tricky.”

→ ✅ Generates code + explanation in one go.

🟦 Prompt: “Patch My Code”

“Here’s a function that sorts users. I need to:

  • Add null safety

  • Optimize for large arrays

  • Keep original order for duplicates

    Please edit and explain.”

→ ✅ Skip the “what’s wrong here?” message. Be directive.

🟦 Prompt: Generate Tests

“Write Jest unit tests for this function. Assume TypeScript. Include edge cases.”

🐞For Debugging**

🟧 Prompt: Bug Buster

“I’m getting TypeError: Cannot read properties of undefined (reading ‘map’).

Here’s the relevant code.

  • Help me isolate the cause

  • Suggest a fix

  • If needed, ask me what else you need”

→ ✅ Avoids a 3-message loop by assuming you’ll help proactively.

🟧 Prompt: “Why does this fail?”

“This API returns a 403 error when run in production, not local.

  • Using Axios, same headers

  • CORS is configured

  • Auth token is valid

    Can you give me 3 possible causes?”

→ ✅ Jumpstarts the diagnostic process instead of “any idea why?”

✍️For Writing & Docs**

🟩 Prompt: Technical Doc Generator

“Write a short README for this repo:

  • What it does

  • How to install

  • Usage example

  • FAQ if needed

    Use friendly but professional tone.”

🟩 Prompt: Rewrite for Clarity

“Here’s a dense paragraph from my docs. Rewrite it to be:

  • 5th-grade reading level

  • More concise

  • Less passive voice”

📊For Data / CSVs / JSON**

🟨 Prompt: File Analysis

“I’m uploading a CSV of video metadata.

  • Show columns with missing or duplicate values

  • Give summary stats

  • Suggest 2 columns I should normalize for clustering”

🟨 Prompt: API Response Analyzer

“Given this nested JSON response from an API:

  • Flatten it to a useful table

  • Extract the IDs and names

  • Point out inconsistent schema if any”

🧠 BONUS: Smart Efficiency Add-ons

  • Preload instructions:

    “Assume I’m working in Node.js unless I say otherwise.”

  • Reuse context:

    “Use the same config from our last build setup conversation.”

  • Preempt questions:

    “Let me know if any part needs clarification before you answer.”

Once upon a time. . .

Related Posts