Building WeMachines on WeMachines

Today, WeMachines is four people. This is a breakdown of how WeMachines helps us build the product. We looked back at the AI-first teams we have led and compared them to how we run on WeMachines. Consider the numbers a very safe estimate.

Transparency

Let's start with the most important foundation of WeMachines: radical transparency. You won't find direct messages. Every channel, every call, every document, is open to the whole team - including agents. Ego and politics get punished fast. This is what makes WeMachines different - it opens the door to entirely new opportunities.

Tickets

We believe a time will come when we won't spend any time writing and refining tickets. Because the AI in WeMachines can read the whole workspace at any given moment, its understanding and accuracy are excellent.

We never write tickets ourselves. We very rarely visit the board. The AI moves tickets as the work progresses. Something changes? The AI updates the tickets too. That alone is a massive time saver.

Stitching tools

You've got chat, an issue tracker, docs, a call tool, a transcription bot, another bot for other apps, perhaps custom integrations - webhooks, OAuth flows, you name it. We've done that ourselves. You build, build, build, and then comes the maintenance, while the whole AI landscape keeps changing.

At WeMachines all of that is irrelevant - everything is there out of the box, and of course that's because it's just one app. With custom Apps we ask the AI to build an integration or extension for our workspace: we're integrated with PostHog, ElevenLabs and our own backend service, we have a custom CRM extension, we are not limited, and we spend zero time on development, hosting, access control and maintenance.

AI models

Are you running entirely on Claude? Grok? ChatGPT? Models degrade, new LLMs keep coming out, vertical LLMs are being released, and we've seen what happened with Fable.

In WeMachines we have access to 200+ models - plug and play. When something comes out, we can test it right inside our workflow. That again removes the distraction we'd have with custom infra and stitched-together tools.

Amazing context

Your company data lives in so many places: Slack, Linear, Notion, some note taker, Google, maybe an AI automation provider, other SaaS tools, and perhaps third parties from your own AI infrastructure - none of that is optimized to work together. To make AI accurate you have to connect all of that, somehow.

In WeMachines, chat, tasks, discussions, docs, huddles, all the apps - everything is available to the agents, and you never have to wonder whether some information got lost. This saves a ton of time - no briefings, no repeated attempts, no frustration, no maintenance, it just magically works.

Other

WeMachines encourages a new mindset: think of your workspace as a living organism. We don't hold onto old data, and everything is transparent. We made that prominent across the whole workflow. Developers use MCP to sync with WeMachines without even spending time in the platform. Team members chat with an AI that knows everything. The AI keeps your data and workspace healthy. It's a clever autopilot.

Safe estimation

WeMachines gives us time back - roughly 40 to 50 hours a week.

We reinvest that time in people. We talk a lot, we brainstorm, we make sure we are in sync and pulling in the same direction. Everyone has room to think. This makes the rest possible to run on autopilot.

Conclusion

Behind WeMachines are great people, everyone with 10+ years of experience in the craft. Every day we put 100% effort into making WeMachines better: UI interactions stay sweet, bugs disappear quickly, and we work with you to streamline the way we all work. That, again, contributes to time savings and joy. Put everything together, and WeMachines ends up being your competitive advantage.

The AI landscape is moving very fast, and we're building a company that gives you access to state-of-the-art collaboration.