6 AI agent workflows I use to hand off everyday tasks – and how to create your own

It's not about being lazy. It's about being efficient. Here's how I use AI agent workflows to simplify my day - and how you can, too.

Read full bio November 4, 2026, 9:51 am ET

ZDNET’s key takeaways Agent workflows are a means to simplify your day. Use workflows to help tackle tedious, time-consuming tasks. Each AI tool’s workflow functionality will vary. For some, AI is a way to cheat, to not have to learn something because you can simply have AI do it for you. For others, AI is a way to automate otherwise time-consuming tasks so as not to allow the day to become overwhelming.

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That’s what agent workflows are for. You create workflows so you can type a quick query in your AI tool of choice and allow the workflow to take care of those time-consuming tasks for you. The results of those queries can then be used to help inform your day or help ease your burden a bit.

If you’re still unsure of what an agent workflow is, I want to help you out with that by describing to you some that I’ve created to hand certain tasks off to AI.

I’ll also walk you through the process of creating an AI workflow. The complication with this is that the process of creating these workflows is different on every AI tool and service. To that end, I’m going to demonstrate the creation of an AI workflow on my tool of choice, AnythingLLM. Once you see how it’s done there, you should be able to translate that process to your tool of choice.

Here is a list of agent workflows that I find helpful.

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With this agent workflow, I can instruct AI to scrape a particular website and use an LLM to filter the posts based on a particular topic of interest. This workflow helps me to quickly find articles about topics I need for research and educational purposes. I can create multiple workflows to scrape different sites, so the workflow doesn’t become overly complicated.

Since I began creating my own writing app, I’ve had to do a lot of debugging via AI. The goal of a debugging code workflow is to find the cause of a problem, implement the smallest and safest fix, and verify that it works correctly. This workflow isn’t designed to fix the problem but to find the issue and present possible solutions. I can then either fix the problem myself or interact with AI to implement the solution. The reason I use this workflow is that AI is exponentially faster at finding issues and discovering possible fixes.

If you travel a lot, this workflow could be quite helpful, as it fetches a seven-day forecast for your destination and outputs a localized weather summary. I even include a packing list based on that summary, so I don’t have to worry that I’m going to forget to take something along that I might need based on the weather. I’m not terribly great at traveling, and my ability to know what I’ll need to pack is even worse. In the past, I’ve experienced several instances where this workflow would have helped me quite a bit.

I am really bad at organizing things, including invoices and receipts (especially those that can be used for tax purposes). To that end, I use a workflow that helps me manage my expenses. This workflow is triggered by an email that includes a particular keyword (such as a “receipt” label or an attached document). The AI then checks the email or attachment, extracts specific information (such as vendor, date, amount, applicable taxes, and category), and then adds the information to a spreadsheet. Without this workflow, I would miss a lot of important information that could save me money at tax time.

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Every so often, I’ll need to do a mind dump via speech-to-text. I often do this when ideas start to overwhelm me (because they often come en masse). This workflow converts the audio into raw text and rewrites the transcript into whatever format I need (such as a book idea to be saved in my to-be-written document, a social media post, or a description for a particular idea). The workflow then saves the draft into a document for later use. I can also instruct the workflow as to what the word salad I’ve dictated is meant for, such as “Convert this audio into a usable description for a book idea.”

This one is really handy because I often forget to do such things. What this flow does is help me keep abreast of things like furnace filter replacement, appliance care (like replacing water filters in the fridge), and seasonal tasks (like getting the AC unit/furnace checked). Here’s how this can work: You buy a new appliance that comes with a downloadable PDF manual. Save the PDF into a specific Google Drive folder. The agent then populates a Home Maintenance calendar with alerts like “Change Furnace Filter – size 16 x 20 x 1” and then adds an Amazon purchase link for the specific filter in the calendar notes.

Now that you have an idea of some of the workflows I’ve used, let me show you how they can be created. Again, how these are created will depend on the specific tool you use. I’ll demonstrate creating the first workflow I mentioned in AnythingLLM.

It’s important to understand that the process of creating a workflow requires:

To create a workflow in AnythingLLM, you’ll need the following bits of information:

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To do this, open AnythingLLM and go to Settings > Agent Skills > Open Builder.

On the resulting page, click +New Flow. At the top of the Flow Builder, you’ll fill out the title and description like so:

Description: This tool can be used to visit Y Combinator and extract ALL headlines and links from the page that have to do with a particular topic.

The flow will return relevant articles as clickable Markdown links.

After adding the above information, you’ll then need to fill out the necessary flow variables, which you create. You can name them whatever you want, but each has to serve a particular purpose and have a unique name. Here are the variables I created for this agent flow:

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You’ll see how the above variables are used in a moment.

Next, create a Web Scraping block (by clicking + Add Block and selecting Web Scraping). The values you’ll add for this are:

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Create an LLMInstruction block and configure it like so:

Extract all links from this content that would be relevant to this topic: ${topicOfInterest}

Format your response as a list of Markdown links, with a brief description of why each link is relevant.

If no relevant links are found, say “No relevant articles found.”

Once you’ve done that, save the block. You can then go to the AI prompt and type your query. You will see the agent checking ycombinator.com for today’s Linux news posts, and then it will present them to you (if there are any to present).

And that’s the general gist of creating an agent workflow. Again, it’s going to vary depending on which AI agent/service you use, so you’ll want to research how to create these on the AI tool you use. The important thing is to approach creating agent workflows with all the necessary information already in hand (such as what you want the workflow to achieve and how to go about it). With that information in hand, check out your tool’s documentation on how to implement the workflow.