Should you use an AI skill or an AI workflow? This simple guide will help you understand the difference (and choose the right approach for whatever you're automating today).
Skills vs workflows. You've seen these two concepts popping up recently. Both capture the logic of repeated tasks so AI can execute on them consistently across multiple requests.
So what's the difference? Which one should you be experimenting with next for your next AI automation?
The difference is how the AI goes about doing the work each time.
What is an AI skill?
Think of a skill as an open-ended job description. It's a set of written instructions that tell an AI agent how to behave, what persona to adopt, and what general steps to follow.
The catch is that every single time you use this skill, the underlying language model reads those instructions again from scratch. It reads your prompt, interprets what you want right in that exact moment, and decides how to execute the task. It is a fresh interpretation every time.
What is an AI workflow?
A workflow operates more like an assembly line. It is a predefined flowchart of steps that runs automatically the moment a specific trigger happens.
The system executes step one, then step two, then step three in the exact same order every single time. There can still be AI processing and decision making within these steps, and logic branches within the flow too, but the overall process structure is set.
The trade-off: Flexibility vs reliability
Because skills and workflows operate differently behind the scenes, they bring very different strengths to the table!
Skills are incredibly flexible. Because the AI rereads the instructions every time, it can handle a lot of variation. If you throw a totally unexpected file format at it or ask a slightly different question, the AI can usually improvise and figure out what to do. The downside is that a fresh interpretation each time is slower and consumes more computing power. Meaning, it can be more expensive to run repeated work with skills at a high volume.
Workflows are your ticket to reliability. The path is already mapped out. There is no risk of the AI getting distracted or hallucinating a completely new sequence of events. Because you are only paying the AI to perform specific tasks within the process rather than analyzing the entire process from top to bottom, workflows are also significantly cheaper and faster.
Examples
A good use case for an AI workflow
Imagine you manage a customer support inbox: Every time a new ticket arrives, the issue needs to be categorized, prioritized, and assigned. This could happen hundreds of times a day or month. You don't want creativity here! You want strict consistency. An AI workflow is the way to handle this.
A good use case for a skill
Imagine you are holding a quarterly roadmapping session: Let's say that once a quarter, your team holds an all-hands brainstorming session. You want an AI to organize the resulting chaos of whiteboard images and sticky notes into a neat, readable strategy document. This task happens infrequently and the input data is messy and looks completely different every time you do it. You need flexibility to process whatever the output might be this time around. A skill is the perfect fit here!
How do I set these things up?
All of the major LLM providers have or are working on a way to support skills. I'm a fan of Claude in particular. You can create .md files as instructions for Claude to reference whenever you need to do a task again.
For AI workflows, you need a good workflow builder.
About
Relay.app
Relay.app is the easiest way to automate with AI. It turns plain language into reliable, visual workflows across over 200 apps. Non-technical users who have struggled with complex tools like Zapier or Make can create reliable AI workflows in minutes just by using plain language. Relay.app handles everything from creation to analysis, while built-in human-in-the-loop features ensure that you stay in control when the stakes are high.
Product details
Ease of use: Relay.app is designed for teams of all technical abilities to automate in minutes.
AI Agent creation: Use natural language to build and improve complex AI workflows effortlessly.
Human-in-the-loop: Add checkpoints to pause workflows for human approval or data entry when needed.
Collaborative features: Share workflows and app connections across your team for seamless multiplayer automation.
Built-in AI models: Access the best models from OpenAI, Anthropic, and more using included AI credits.
Stateful data with Tables: Store and update structured data directly within Relay.app to use across flows.
Technical power: Advanced users can leverage custom JavaScript, MCP servers, and custom HTTP requests.
200+ native integrations: Deeply connected with popular tools like Notion, Gmail, and HubSpot.
Pricing
Relay.app offers a range of plans including a generous free tier. All plans include free test runs so you can validate your workflows before they go live.
Free: $0/month for 1 user, 200 steps, and 500 AI credits
Professional: $19/month (billed annually) for 1 user, 750 steps, and 2,000 AI credits
Team: $59/month (billed annually) for up to 10 users, 1,500 steps, and 2,000 AI credits
Enterprise: Custom pricing for organizations with advanced usage or security requirements
One quick rule
To summarize, here's a helpful rule for when to use skills versus a workflow:
If a task happens frequently and demands consistency, rely on a workflow.
If a task is infrequent and benefits from on-the-fly improvisation, build an AI skill.
By matching the right tool to the task, you will get the best results every time.
Jacob Bank
Founder/CEO at Relay.app
Jacob is the Founder and CEO of Relay.app. Prior to founding Relay.app, Jacob was a Director of Product Management at Google, where he led the product teams for Gmail, Google Calendar, and several other Google Workspace products. Before that, Jacob was the Co-founder and CEO of Timeful (acquired by Google in 2015), a smart calendar that leveraged insights from behavioral psychology and AI to help people spend time on their most important priorities. He has a BA in Computer Science from Cornell University and was pursuing a PhD in the AI Lab at Stanford before dropping out to found Timeful.
FAQs
Which workflow tool should I use if I'm not really technical?
Which automation platforms don't require coding to use?
Why would I use Relay.app instead of Claude Cowork?
Should I use a general-purpose AI agent or a workflow automation tool for my business?
What's the difference between AI agents and workflows?
