Vibe Coding a CRM AI Agent in 12 Minutes

All CRM systems needs customisation. However, instead of taking an existing CRM system and modify, why not create your own entirely from scratch, and wrap it into an AI agent?

The benefits of this is you don't have to "battle" the existing database schema, but can instead create your own entirely from scratch. And since no two CRM requirements are the same, this actually gives you much more flexibility than forking an existing CRM system and start modifying it. If you choose to wrap it into a natural language interface as an AI agent, you can also completely drop your frontend, and simply use a "generic one size fits all" frontend to interact with it - So the only remaining tasks here are the creation of the database, its API, and wrapping it into an AI agent.

The problem with that approach is that traditionally creating an entire CRM system from scratch would easily require dozens of software developers, working for years, before you've even got a basic MVP. With Magic Cloud however you can create it in 10 minutes instead of years ...

The database

The first thing you'll need is a database. We're going to create an SQLite database called "crm". Click "Manage/Databases" to create a new database as illustrated in the screenshot below.

At this point we could visually design our database, but in the interest of doing things extremely fast, we'll just ask ChatGPT to give us a database using "vibe coding". We will do this using "SQL Studio". Use the AI textbox and write what you want, and click "Ask" to have the AI suggest a CRM DDL. I told it; "Create SQLite DDL for a CRM system for an outsourcing company to track clients and projects".

This produced the following for me. Remember to click "Clear server cache" to have the changes show up in your GUI after having executed the DDL SQL.

For additional bonus points, we can now switch to "SQL View" and use the AI helper to populate the database with example data.

The API

All software systems needs an API. API means Application Programming Interface and is the standard means for your frontend to access its backend. We're not going to create any frontends, but instead rely upon our AI Expert System - But we'll still need an API. Building an API takes only some few seconds with Magic due to its CRUD generator. Below is a screenshot of how it looks like.

The CRUD generator will create some 3,000 to 5,000 lines of code automatically for you, using meta programming - At which point you've got most data access functions you will ever need. For added bonus points, we can now use the Hyperlambda Generator to create custom business logic, or the SQL generator to create KPI endpoints. If you need to for instance create a "Send email function", you can simply use the AI generator that's integrated with Magic Cloud to create it for you.

The AI Agent

At this point, the only remaining task is to associate these newly created functions with a machine learning type. This is the final task in our master plan, and allows us to use natural language to interact with our API. Create a new machine learning type from "Manage/Machine Learning" and make sure you choose the "AI Agent" flavor. If you can't find the "AI Agent" flavor you'll need to install the OpenAI plugin from your plugins repository.

Once we've got our AI agent, we'll need to associate our functions with it. This is done from Hyper IDE by clicking the flash icon when hovering over your "crm" folder.

The above creates RAG training data for your machine learning type, allowing it to match natural language towards function invocation declarations - Which combined with the AI agent system instruction / flavor allows the LLM to understand how to execute your functions. The only remaining part now is to create embeddings for our type and we're done. This is done from the machine learning component.

Testing your CRM AI Agent

You're now basically done, and you can test your AI agent. We're going to use the AI Expert System to test, so make sure you've got it installed from your plugins component.

At this point you can create, list, update, and delete rows from your database using natural language. In addition you can create KPI endpoints or custom business logic with either the SQL generator or the Hyperlambda Generator. And the result is a 100% custom CRM system, entirely built from scratch, 100% accurately meeting your requirements without having to "battle the existing logic" of your existing CRM provider.