Agentic Workflows - Explained Like a 10 Year Old
Do you ever feel like you need an extra set of hands (or maybe a whole team) to get everything done? Imagine having a super-smart helper who not only understands what you want but can also figure out the best way to do it, learn from mistakes (yours, its, and other people’s), and even use different tools to complete a task.
That's the core idea behind agentic workflows, and it's something that's got product leaders like me incredibly excited.
But what does "agentic workflow" actually mean? Let's break it down like a 10 year old would…
Imagine You Want to Build an Awesome LEGO Castle
You (the boss) tell your super-smart LEGO helper (let's call her 'Agent Annie') that you want "the coolest LEGO castle ever, with a moat and a dragon."
Here's how Agent Annie, using an agentic workflow, might tackle this…
Understand the Goal: Annie gets the main idea: "cool castle, moat, dragon."
Break Down the Task: Annie thinks “Ok, to build this, I need to:
Find all the blue bricks for the moat.
Gather grey bricks for the walls.
Find special pieces for the towers.
Figure out how to build a dragon (maybe I need to look at some LEGO dragon pictures or instructions).
Put it all together.”
Make a Plan & Use Tools: Annie decides the order to do things. She might "use" her "eyes" (a camera or sensor in the AI world) to scan the LEGO box for the right coloured bricks. If she's unsure how to build a dragon, she might "ask for help" by searching an online LEGO guide (like an AI using a search engine).
Take Action & Adapt: Annie starts building. Maybe she tries to build a wall, and it keeps falling over. Instead of just giving up, she "learns" that the base isn't strong enough and decides to make it wider. She's adapting based on what's happening.
Check Progress & Report Back: Annie might show you parts of the castle as she builds them, asking, "Is this moat big enough?" or "Do you like this wing design?" She's getting feedback.
Complete the Task: Finally, Annie presents you with your amazing LEGO castle, complete with a moat and a dragon.
That, in a nutshell, is an agentic workflow.
It’s not just about automating a single, repetitive step. It’s about giving an AI system a goal and the autonomy to figure out the steps, use tools, make decisions, and learn along the way to achieve that goal. Think of it less like a traditional computer program that just follows instructions, and more like a smart, proactive assistant.
Where Did This Idea Come From?
The concept isn't brand new; it builds upon decades of research in Artificial Intelligence. Think of it as the next evolution. We started with AI that could spot patterns (like a spam filter) or make predictions (like Amazon recommendations). Then came AI that could generate new things, like text or images (ChatGPT, Midjourney, Adobe Firefly, etc). Agentic AI is the next step, where these smart systems can now act more independently to achieve complex objectives.
What Can These "Agents" Actually Do?
The possibilities are vast and growing daily. Here are a few examples:
Supercharged Research: Imagine asking an AI agent to "research the latest trends in sustainable packaging for food products, summarise the key findings, identify the top five innovative companies in this space, and put it all into a presentation." The agent could then browse the web, read articles, synthesise the information, and generate the slides.
Personalised Customer Support: An AI agent could handle complex customer queries, not just by pulling from a script, but by understanding the customer's history, accessing relevant information from different systems, and even performing actions like processing a refund or updating an address.
Automated Content Creation & Marketing: An agent could be tasked with "creating a social media campaign for our new product launch," which might involve drafting posts for different platforms, generating images, scheduling the posts, and even analysing their performance.
Streamlining Business Operations: Think about an agent that can "monitor our inventory levels, identify when stock is low for specific items, find the best supplier based on price and delivery time, and draft a purchase order for approval."
Why Are CPOs Like Me So Interested?
As a Chief Product Officer, my world revolves around creating products and experiences that customers love and that drive business value. Agentic workflows open up a thrilling new frontier for several reasons:
Building Smarter, More Helpful Products: We can embed these agents into our products to make them incredibly intuitive and proactive. Imagine software that doesn't just wait for you to click buttons but anticipates your needs and offers to help.
Hyper-Personalisation at Scale: Agentic AI can help us understand and adapt to individual user needs in real-time, delivering truly personalised experiences in a way that's been incredibly difficult and expensive to achieve before.
Unlocking New Efficiencies: By automating complex, multi-step processes, we can free up our human teams to focus on higher-value strategic work - the stuff that requires uniquely-human creativity and empathy.
Creating Entirely New Product Categories: Agentic workflows could be the foundation for entirely new types of products and services we haven't even imagined yet.
Accelerating Innovation: The ability for agents to autonomously research, experiment, and even assist in coding or testing can dramatically speed up the product development lifecycle.
You Don't Need to Be a Coder to Get It
The beauty of this technological shift is that its impact will be felt by everyone, regardless of their technical background. The key is to understand the concept - that we're moving towards AI that can "do" things in a more intelligent and independent way.
So, the next time you hear "agentic workflow," don't let the jargon intimidate you. Just think of Agent Annie and her LEGO castle.
It’s about giving AI a goal and empowering it to figure out the "how." This is a powerful shift, and I believe it will unlock incredible innovation and value for businesses and users alike.