How AI tools (like ChatGPT) can assist in bot creation.
What an irony, bots are making bots...
AI chat models let me skip the dull parts — typing, debugging, searching docs — and stay on the trade. Here’s the playbook.
1 . Share context
Before asking for the code, I recommend you to give ChatGPT some context, including: your trading tool, programming language, and scripts examples.
Prompt template:
Act like a professional algorithmic trader, trading bot creator, and Pine script programmer. Your task is to create trading bots for AutoView following my strategies.
Here are some examples of Pine scripts for trading bots:
[Examples of the bots you like with similar strategies or at least in the same programming language]
Make sure the code works.
Ask me questions if you need more details.
2 . Idea → code in one prompt
I write the rule in plain words.
Prompt template:
Here is my strategy. Use it to write code for the trading bot.
[Strategy example]: Buy BTC when 15‑EMA crosses above 50‑EMA on the 1‑h chart, sell on cross‑down, add 1 % stop.
ChatGPT spits back a full Pine Script or Python ccxt file in seconds.
3 . Instant troubleshooting
If the script won’t compile I paste the error text right back. ChatGPT patches the bug line by line — no IDE deep dive needed.
Prompt template:
This code doesn't work. Error: [Error text]. Fix the problem and rewrite code it to make it work.
If it still doesn't work, try opening a new chat and ask a "new" ChatGPT for debug.
4 . Rapid tweaks
Prompt template:
Add a trailing stop set at 0.8 % and print PnL per trade.” Updated code lands in the same chat.
5 . Webhook glue
Need to fire orders from TradingView? I drop my Pine alert JSON and say...
Prompt template:
Convert this to [algotrading platform] syntax for [your trading platform].” The model rewrites the string with the right aid, s, q, b, t fields — ready to paste.
6 . Custom GPTs for repeat jobs
I built a private GPT with my favorite exchange API docs loaded. Now I can type, “Create a ccxt wrapper for trailing OCO in Kraken futures,” and it cooks one up with comments every time.
7 . Sentiment add‑ons
Ask for Python that scrapes headlines, scores tone, and pipes the signal into the bot loop. The chat model handles the NLP bit while I focus on the trade rule.
Quick workflow checklist
Draft rule in plain words.
Prompt ChatGPT for full script.
Copy/paste into MT5, Pine, or Python.
Back‑test hard.
Feed results back to ChatGPT: “Cut max drawdown.”
Deploy on VPS once stats look solid.
Tasks the AI handles well
Write fresh strategies in Pine, MQL5, EasyLanguage, Python.
Translate scripts between languages.
Add stops, targets, size rules.
Comment and document code.
Generate walkthrough notes for clients.
Summarize release notes of exchange APIs.
I still vet every line and back‑test like a maniac — but the chat assistant chops build time from days to minutes. Use it as the coder on call, and keep your head in the market.
However, it is still not perfect. I started using it ChatGPT 4o model first. It made a lot of mistakes that I had to fix. Now the o4-mini, which is designed specifically for coding, does it much better. But you still have to be prepared for its scripts not to work sometimes, and it will take time to debug them with ChatGPT itself. And still, this is better than learning code from scratch.
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