If you thought it was easy to spin up a ChatGPT Assistant, you’re not far wrong. You can literally create, link a project, add some instructions and you’ll be chatting.

But moving any App into a production environment is not so easy. Sure, you can embed it easy enough into a webpage, that’s what they were made for at one point, but to have your Assistant ‘out in the wilderness’ and ready to spring into action at any moment, well that’s another thing entirely.

For anyone to use your Assistant without essentially giving away your ChatGPT login, I don’t recommend that of course! You have to host your Assistant somewhere, usually with a database under it and some code to make it all happen.

Now to host an App or a page that others will access, you have to present it in a stable state. You can’t be throwing new code at it and rebuilding, redeploying it at your whim as your customers will lose access. No, you must respect the laws and principles of program change management, you must have a separate development environment, and program changes are packaged, scheduled and controlled so as to have minimal downtime for the production instance.

I use Github for change management and code integrity. You can’t develop and deploy without it.

Some of the Key Features of my Build:

1. I chose to build a dashboard for this project that can provide a seamless interface for the user to run a basic email campaign. This becomes an asset for me that I can further develop and use as an entry point for customers for different automations.
   -upload or create, edit leads
   – submit leads to an automation job to verify email addresses
   – submit leads to a predefined automated email campaign
   – receive and process requests for samples
2. Central chat interface is an OpenAI ‘Assistant’ which serves the user message interface. The method of delivery (to the customer), in this case, is by email, embedded in a button. The email recipient may choose to engage the Assistant by clicking the call to action, render.com will open a session and the customer engages with an Assistant that has a specific purpose.
3. A ‘virtual store’ is attached which contain knowledge materials (training)
4. To enable real-time interaction with the Assistant, render.com forms an ‘always live’ platform that hosts the Assistant for the duration of the interaction.  (Free tier winds down with inactivity and takes a little time to wind up when activated by a chat session. you can get around this with an automated ping when a user opens their email).
5. Code is managed via Github as the central repository.  Development is completed locally, and changes synched to Github (cloud).
6. Incoming leads can request contact (with or without samples requested) and the lead will flow back to the Contact Dashboard (and notify somebody)
7. Incoming requests for sample product will be logged by the Assistant and the request (and fulfilment will flow back to the Contact Dashboard)

These build projects are not quick, they’re not glamorous, it never works on the first go and you’ll always have to debug. But they’re a labour of love.

I used these products to build this project:

Product	Use	URL
ChatGPT 5	Coding, prompts, document writing, problem solving	https://chatgpt.com
Openai Assistant / Assistant API	Customer service agent (interface)	https://openai.com/platform
Openai Codex	Coding, debugging	https://chatgpt.com/codex
Google Jules Asynchronous Coding Agent	Coding, debugging	https://jules.google
Postman	Debugging	https://postman.com
Render.com	App hosting	https://render.com
Notion	Knowledge db, forms db, workflow	https://notion.com
Github.com / github desktop	Code repository, change management	https://github.com
Make.com	Automated workflows	https://make.com