Emilia Gette serves as a marketing associate at Workast, specializing in crafting innovative strategies to engage with the audience. With a focus on creativity and attention to detail, she contributes to driving impactful results across various marketing channels.
A year ago, most teams had one problem: getting people to adopt AI. Today, many teams have the opposite problem. Everyone is using AI, but nobody is using it the same way.
Some people rely on ChatGPT. Others prefer Claude. Developers use Cursor. Designers have their own tools. Marketers have their own workflows. And while each person may be individually more productive, collaboration often becomes more fragmented.
So how are teams actually managing work across multiple AI tools?
Despite the headlines, most teams aren't standardizing around a single assistant.
Developers often work with Cursor and Claude. Founders use ChatGPT. Product managers experiment with multiple tools. Teams naturally end up with a mix of assistants, each serving different roles.
The result is not one AI workflow. It's many.
Reading discussions on Reddit and developer communities reveals a pattern.
Many users describe themselves constantly:
copy-pasting outputs between tools
rebuilding context
keeping notes and protocol documents
maintaining Notion pages
sharing screenshots and links
manually translating information between AI tools and the team
The work gets done, but coordination remains manual.
Instead of relying on one platform, many teams are assembling workflows themselves.
Some teams rely on Slack and Notion, while others organize work through Google Docs, shared folders, project management tools, or simple files like tasks.md and protocol.md. Rather than adopting a single system, many are combining familiar tools to create workflows that fit the way their teams and AI assistants already work.
These systems help, but they're often stitched together rather than designed for AI collaboration.
One interesting pattern appears repeatedly.
People rarely complain about the quality of AI anymore.
ChatGPT is good.
Claude is good.
Cursor is good.
The complaint is usually somewhere else.
The challenge is keeping everyone — and everything — aligned.
As AI becomes part of everyday work, the biggest challenge may no longer be execution.
It may be coordination.
Not because AI tools aren't powerful enough, but because teams now have multiple people, multiple assistants, multiple contexts, and no shared way to coordinate them.
There are plenty of tools for communication, project management, automation, and AI.
But teams are still experimenting. Some rely heavily on Slack for coordination, while others organize work through Notion. Many are building their own systems by combining different tools and processes. And perhaps that's the biggest signal of all. When people start inventing workarounds and stitching together their own solutions, it usually means a new category is beginning to emerge.
When every employee has their own AI assistant, where does all that work come together?
Workast