Argil is now available on the ChatGPT plugin store, making image generation more accessible. Learn how this marks the start of a new chapter in AI automation, despite the challenges.
First, we saw the rise of coding, then the development of low-code platforms. Further down this road of automation, the notion of no-code came to life, and finally, automation saw the light of life.
What is the next step?
What could we see after automation?
Is it even possible to push this further?
I’ll try to answer these questions in today’s article.
The launch of ChatGPT and the ease of use it provided gave us the first signs of answers to the above questions. Generative AI and LLMs are the basis of what’s coming in the next 6-12 months.
Why is that?
Simply because the basis of automation is to bypass time and provide people with what they need to get specific results. A commonly accepted definition of automation is the reduction of human intervention in a work process.
That definition does not mean that automation could run in an interactive way.
Let me illustrate with an example:
Let’s say you want to build a startup. So far, the only automation you could do is in regards to the daunting and repetitive tasks such as emailing, getting triggers when an event happens, managing specific micro-tasks, etc.
But what if generative AI could push this further?
Here’s a process you could run through when you have a new idea:
What if I told you this can be automated?
That’s the power of AI-automation.
The creative and research process can be automated and given specific inquiries such as what not to do and what to do in natural languages.
You can ask as you speak with your AI automation.
We’re entering a completely new world with infinite leverage, AI automation is not just the new trendy thing, it’s the new way people will build and test things.
The AI automation era has started, and you can see that with the dozens of tools launching every week on Product Hunt with that promise.
All industries are being tackled, from retail to healthcare. AI automation is providing people with a way to:
AI automation is about better allocation of resources but also a way for individual people to test and build up their hypotheses.
Thinking, creating, and maturing a product idea will become more accessible than ever with AI automation, and that’s one of the reasons we’re building Argil.
The goal is simple:
Provide people with a tool that lets them train AI on their datasets, experiment in our studio, create their personalized AI automation, and even streamline it to their application with our API.
On Argil you can:
But that’s the tip of the iceberg, our goal is not just to build the best multimodal platform (text, image, speech text, text-to-speech, table generation) but also to integrate seamlessly your Argil’s workflow into your existing automations.
And for that, we need to be compatible with the biggest automation player: Zapier.
Some people saw Argil as a competitor to Zapier, that’s absolutely not our intention. We want to make AI automations seamless, yes.
But going after the market of Zapier makes zero sense, on the contrary, our goal is to integrate Argil into the automation steps you can build on Zapier.
We even believe that we could provide an important value to Zapier with our AI automation features. Being the base layer of our market and positioning, we are super flexible and AI native.
We don’t have 200 processes and the need to align the AI automation vision with tool integration to one app as is the positioning of Zapier.
This small difference gives us a better chance to be the number one player of AI automation, and a complete synergy with Zapier.
We can benefit from all the integrations already present in this tool, and they can benefit from the multimodal and training approach we have with generative AI.
What does this mean?
Let me illustrate with an example:
Let’s say you want to build an automation that sends a personalized LinkedIn invitation request every time someone likes one of your posts.
That’s already possible on Zapier, but with Argil’s AI automation, you can truly personalize the message you send with the request.
Here’s what this workflow would look like:
1/ You get a like on one of your posts
2/ This is an event that triggers an action
3/ The action is a scrap of the LinkedIn profile of the person
4/ It is added to your Argil workflows that have inputs:
5/ You get a personalized message to send
That’s the power of AI automation, it increases the quality of your automations and adds context that wouldn’t be present otherwise.
Our mission at Argil is clear:
Create the first no-code platform that maximizes the synergies between generative AI, existing automation tools, and every industry.
Our horizontal move with AI automation gives us room to build a concrete and actionable vision of this new market.
The intersection of no-code, generative AI, and automation is AI automation. When you break it down, the goal is to enable creation at scale and keep the quality of the outputs super high.
Argil bridges the gap between LLMs’ capabilities and quality outputs, while Zapier bridges the gap between applications.
The intersection of Argil and Zapier is multimodal and multi-application AI automation.
You need to be part of this revolution, join us here: Argil
