I am sure you saw them, all the threads on Twitter and the LinkedIn posts about how 17 years old kids are making 10 000$ + a month. True? Lie? Hyperbole?
What is sure is that the rise of No-code tools such as Webflow, Bubble, Carrd, Make, Zapier, and notion empowered non-tech people and people with low experience to build businesses exclusively based on automation and third-party providers.
Why develop internally when you can do it using tools for a fraction of the price and in less than a day? That exact question is now even more at the heart of the business with the rise of AI and how it increased the quality of the outputs.
Building a business using tools for the operational part is great, but the content and quality part was lacking. The recent rise of LLMs just opened a completely new type of opportunity and enhanced the possibilities.
Our goal at Argil is to build on this vision of no-code tools usage. Adding the AI automation layer will provide a new way for a no-code builder to create business models from scratch, test them, and iterate them in a record time.
We’re living in an exciting time, OpenAi opened a new path for businesses that provide solutions to end-users, and ai-automation is one of the parallel paths everyone can take to build a nearly automated business.
Definition automation itself is not what I am aiming for in this section as I believe it’s already a common and understood definition but I’ll do it anyways just for the sake of context.
Automation is the independent occurrence of actions that would otherwise require human intervention.
For that you can use different tools that solved the painful manual tasks you would do in your work process, still, it doesn’t tackle a region of work:
All creative processes and strategic ones were made by humans and we had no way to automate or really systemize them.
That’s where AI Automation comes to play, you certainly saw it using chatGPT, you can use it as your second brain, create discussions for specific purposes and use them whenever you need a specific output.
Ai automation is getting rid of the interactions you may have to get through to get a specific output from using chatGPT, it’s a way to set your conditions, and the triggers of the next interaction with the AI and let it run independently.
E-commerce may be one of the industries in which ai automation will have the biggest impact, and the reason for that is Scalability. When you create a Shopify shop your goal is to make as efficient as possible the iteration process.
Let’s take Dropshipping as an example:
1/ You identify your niche
2/ You audit competitors best selling products
3/ You extract patterns between these
This first part of the process is made by yourself but you can already add an ai automation layer. You can use ai automation to do the following:
Based on the input you give it of your niche and the best-selling products you can ask it to give you potential ideas of products that might fit your niche and be part of the top 1% of products.
Once you have your list you can search by yourself for what is being sold online and then choose 3-6 products you want to test in your shop.
Here comes the most daunting part:
1/ You need to create visual backgrounds for your branding positioning
2/ You need to do the copywriting of your website
3/ You need to do the description of every product
4/ You need to Build a Google/Facebook/Pinterest ads campaign
Doing these steps once you get your hand on the overall process is great, but it’s absolutely not efficient.
Now with ai automation, you could:
1/ Set your brand tone and style
2/ Choose specific background models
3/ Generate ads picture with AI
4/ Generate your copywriting with AI
But that’s just the tip of the iceberg, you can do way more using Argil.
As explained earlier we’re positioning Argil as the intersection between:
A good way to see this intersection is with the term Hyper-automation, but we decided to go for ai automation as it would make more sense for people to understand the difference between this and other automation.
Being at this intersection we understood that all industries would benefit from this positioning and that we should build a technology that’s horizontal and can be used by all.
That’s why on Argil you are free to build your own ai automation as you can see below:
You can also choose from a variety of automation we created and shared with all our users, and finally our upcoming community layer will enable every user to submit their ai automation to be part of the one proposed.
Continuing on this brief description of Argil and ai automation (which is necessary for you to understand what you can build on Argil), each action is called a step, and each data you give as a base is called an input.
On Argil you can train the ai automation on your datasets:
You can input a document gathering all that you wrote and have a model of writing style when you decide to use AI automation for that matter.
You can input them and train the AI over them to build a template you’ll reuse along the way.
We have our own API that you can claim and integrate to your application.
Training + Experimentation + Streamlining, these three are the pillars of what we do at Argil.
We want ai automation to be the next way people think of work and creativity, and we’re building on that vision, if you didn’t try Argil yet you can jump on the platform here
