AI Assistants Transform Workflow Automation With Intelligent Decision-Making

Key Quotes

"people think you need to be some kind of a developer or a software engineer or just a computer whiz in general in order to do this and that's completely not true these tools are becoming more and more user friendly and you can do amazing things with them with zero knowledge in computers just by understanding the business processes"

Isar Meitis argues that a common misconception about workflow automation is the need for advanced technical skills. Meitis explains that the tools are designed to be user-friendly, allowing individuals to create powerful automations by focusing on understanding business processes rather than coding expertise.

"but you can build today because of the ability to bring ai into the process every time there's a decision to be made whether this is this category or that category is it beyond the line or above the line or beyond the line for something what kind of response don't want to give like every time a human was supposed to come in to help navigate the process ai can now do this which makes these processes with ai built into them extremely flexible"

Meitis highlights that integrating AI into workflows significantly enhances their flexibility. He explains that AI can now handle decision-making points that previously required human intervention, such as categorizing data or determining appropriate responses, making the overall process much more adaptable.

"old school automation couldn't do that old school automation can get you the information here is the order that came in from shopify i'm going to send you a slack message every time something comes in awesome now i have a queue in a different place which maybe from a user operations perspective that's helpful but it doesn't actually solve the problem the problem is knowing whether that person is a potential client on the b2b side"

Meitis contrasts traditional automation with AI-enhanced workflows by using a Shopify example. He points out that older automation tools could only move data, like sending a Slack message for a new order, but could not perform the necessary analysis to determine if the customer was a potential B2B client, which is a core business problem.

"workflow automation is a process that existed for a while again there's multiple tools and now with ai there's even more tools that are out there that are available but what it knows how to do is it knows how to connect to multiple standard tools that everybody use so what you have in your tech stack your marketing platform your email platform your google account your places where you post so all your social media platforms your email platforms your email you're basically all the tools that you use are already connected to this tool"

Meitis defines workflow automation as a long-standing process that connects various standard tools used in a tech stack, such as marketing platforms, email services, and social media accounts. He explains that these tools have connectors, often through APIs, that allow them to pull and push data between different applications.

"n8n on the other hand is a way more techy and geeky kind of platform and it's definitely not a good place to start because you may get really frustrated very early on and then not go down the path so i tell everybody start with make if you're good and it does everything you needed it to do just stay with make the only reason to switch or the only two reasons to switch are the following one if there's stuff that is more sophisticated complicated that you're starting to get to and make won't do it and then there's a good chance that n8n can and two is cost"

Meitis recommends starting with Make.com for workflow automation due to its user-friendly interface, while positioning n8n as a more advanced, "techy" option. He suggests switching to n8n only if Make.com reaches its limitations for complex tasks or for cost-saving benefits, particularly if self-hosting.

"what they are is basically a repeatable set of instructions if there's something that you do the same way every single time you can turn it into a set of instructions and have chat gpt do it for you so what does it have it has some kind of an input i'm going to give you this data and then i want you to do this analysis process manipulation whatever it is and i want you to create this output"

Meitis explains that custom GPTs (or Assistants) are essentially repeatable sets of instructions that can automate tasks. He describes them as having an input, a defined analysis or manipulation process, and a desired output, allowing users to delegate recurring tasks to AI.