Sim: The Best Way to Build AI Agent Workflows
If you’ve been anywhere near GitHub in the last few months, you’ve probably seen one name pop up over and over: Sim. In roughly five months, the project has drawn in about 60,000 developers, been the #1 trending app several times, pulled in thousands of contributors and followers, and landed at the center of a shift happening inside engineering teams. A shift toward building AI-powered applications directly, rather than stitching together half-working agent tools.
What makes Sim interesting isn’t that it’s another agent platform. It’s that developers are actually using it to ship production systems. Real ones. Not the “research toy with an impressive GIF” kind. And that fact alone makes Sim worth paying attention to.
A platform built for developers, not demos
Most agent tooling splits into two camps:
– Overly abstract frameworks that rename simple ideas and turn development into taxonomy homework.
– Visual builders that make everyone feel powerful until they hit the first branching condition.
Sim sits directly between these extremes in the most useful way possible. It gives developers:
– A visual canvas that mirrors the mental model they already have for agent logic
– A code-like environment that stays close to the underlying LLM APIs
– A natural-language copilot that scaffolds whole applications in seconds
– A clean path to run locally, self-host, or deploy into an existing stack
In other words, it’s not trying to reinvent the idea of agents, it’s giving developers an environment to build with them without fighting the tooling.
Why developers showed up this fast
Tools don’t grow from zero to 60,000 users in five months because they have a pretty demo. They grow that fast because they slot into work people are already trying to do. Teams today are building:
– customer-facing chat and support systems
– email and document-processing automations
– internal research and data-retrieval tools
– domain-specific assistants that reason over private data
The common thread: they’re all AI-powered applications with real logic, constraints, and integration depth. And Sim tends to be the easiest way for a small team to go from idea to working system without writing thousands of lines of glue code or learning an entire framework’s worldview.
That’s the real story here, not agents as a concept, but the practical shift toward AI-native internal applications that real teams need right now.
The open-source advantage
A surprising amount of Sim’s traction comes from something simple: developers can see and understand how it works. They can run it locally, fork it, add blocks, fix bugs, and inspect every line of the orchestration.
Open source isn’t a vibe for Sim. it’s distribution, credibility, and sales all in one. A developer doesn’t need a sales call. They just clone the repo, wire up a workflow, and if it works, the procurement conversation is already solved. In a category full of closed boxes, transparency is a moat.
The deeper shift underneath
The interesting part isn’t “Sim vs. other agent tools.” The interesting part is what this adoption curve says about how software is being built in 2025.
Engineering teams are:
– pushing more logic to the edge of their data
– relying less on rigid SaaS tools
– expecting AI components to be first-class, not bolt-ons
– demanding flexibility around models, hosting, and privacySim didn’t create that shift. It’s riding it giving developers a single place to assemble all of that logic cleanly.
The team behind Sim
What makes the company even more compelling is the team behind it. Emir Karabeg and Waleed Latif are best friends who started building together at Berkeley, moved to SF, and worked through multiple product ideas before landing on Sim. Along the way they kept running into the same problem: the agent tooling available to developers slowed them down more than it helped.
Instead of hacking around it, they decided to fix the underlying issue and rebuild the stack the way developers actually want it to work. That clarity and the pace they operate at is a big part of why Sim feels so far ahead.
What to watch next
The open-source repo is moving fast, the copilot is getting better from real user feedback, and the integration surface keeps expanding. But the more important signal is this: developers are treating Sim like a platform to build applications, not workflows. That’s the difference. A workflow tool doesn’t get embedded inside a legal services firm’s document-processing pipeline. An application platform does.
The takeaway
Sim isn’t promising a revolution. It’s doing something more grounded and more rare: giving developers a straightforward way to build AI-powered software and deploy it where it actually matters, inside the products and systems companies run. When 60,000 developers show up in a few months, they’re voting with their time. And right now, they’re voting for Sim.
Visit Sim.ai at https://www.sim.ai/.