I have a hunch that both OpenAI and Anthropic are building towards this very quickly. It's one of the startup ideas that will be killed overnight when it's "officially" launched. Claude Tag was just released which lets Claude participate in chats in Slack - only a matter of time until they move those chats out of Slack and into their own platform.
That hunch is probably right - the labs are likely building towards this. However, our bet is that in knowledge work the labs don't have a structural advantage: the model isn't the product there, unlike coding where it mostly is - and even in coding, opencode and others are gaining real traction.
What they do have is funding and distribution, but that's the same advantage every incumbent has against every startup.
The single biggest advantage we have is that the labs are tied to their ecosystems. Claude still doesn't have image generation; Gemini-flash-lite is the best cheap model, but Gemini's apps can't use the latest models from Anthropic or OpenAI. We can always use the best tool for each job.
I've heard that refrain ("we can switch models so we won't be obsolete!") a hundred times, but it doesn't hold any water for me. OpenAI and Anthropic command such a large percentage of LLM usage that it doesn't really matter which one implements your product - either way, you're screwed.
Your end users literally do not care what model you use behind the scenes or if you're using "the right tool for the job".
Just did - asked Claude Opus 4.8 in Claude Desktop to generate an image of a horse. It drew an SVG by hand in code and said (verbatim): "I drew it by hand in code, not with an AI image generator. There's no diffusion/photo image model wired into this session."
On the labs: agreed that end users don't care about the model - only that the job gets done well, which is our argument too. At any point some model is best at a given job, so any single lab is behind for a portion of time on a portion of tasks.
I seem to remember GitHub working on something similar. I remember having seen a video from a conference talk someone at GH gave at an European AI conference a while back. She presented some current prototype/early version they were working in. Where AI was basically like a team member in a chat interface with access to the task boards, issue tickets and also the whole conversation of the team, if I remember correctly.
Also different members of the team could steer/approve what the AI did or did not do.
