Discussion on "AI Agents vs Workflows: what's the difference?"

Lucas Vera Toro · 2026-04-23T13:15:08.181Z

Introduction My work as a software engineer and technical architect is centered around building and delivering software doing things like designing systems, collaborating with dev teams and helping mo

Clear and practical explanation — the distinction between control (workflows) and autonomy (agents) is explained really well here. Not every problem needs an agent, and knowing when to keep things simple vs dynamic is key—something we’ve also explored at https://www.remotestate.com/ in a similar context.

Thank you! I'm glad you enjoyed the article!

Which will work better for marketing, basically for the SEO only, on-page, Off page, Technical SEO

Hi! That depends heavily on requirements and needs. In general terms, a workflow could be the starting point, as most SEO tasks are structured and repeatable.

What....if we want to automate things, then...?

Hi Lucas, If I may ask 🙏🏽.. What's the distinction between AI workflows and Agentic AI. I believe the Agents are more or less the carriers of the already established workflows right ?.

Please I am quite new to all this, if you may. Thank you

Hi! Thanks for your question!

You can put it this way: an AI workflow is a structured process, while agentic AI is about systems that can operate and take decisions on its own.

When designing software systems, is important to always use the right tool for the right job. That rule still applies in the AI space and I think it's one of the most important things when designing AI-powered systems

Thanks very much for this

The confusion makes sense because workflows already look smart. But the moment you add loops and decision-making, the complexity jumps fast.

the distinction i keep coming back to: workflows let you predict failure modes ahead of time, agents shift that to runtime. the tradeoff isnt flexibility vs rigor - its "we know what could break" vs "we learn what breaks in production."

for my nuxt 3 + go-zero stack i ended up hybridizing: agents for codegen/investigation, deterministic workflows for deploy/migration. the agent can propose the migration but a scripted workflow runs it. treats the agent as a senior engineer who still has to submit a PR.

collecting these hybrid patterns at tokrepo.com/en across claude code / cursor / zed. the agent-vs-workflow framing is often false when you can compose them.

Hey Ethan. Thanks for commenting!

I like the thought of "predictable failure upfront" vs "discovering failure at runtime" when comparing workflows and agents. A hybrid approach also sounds like it makes a lot of sense depending on the use case.

My blog post was aimed more towards the "let's put agents everywhere" mindset, when I think a lot of systems may be needing a well thought ai workflow instead

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AI Agents vs Workflows: what's the difference?

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