An embedded agency is an outside firm that works from inside your company instead of across the table from it: on your channels, in your meetings, with visibility into the work as it happens, rather than a report delivered after the fact. The term has meant one specific thing for most of the last decade. This year, it has started to mean a second thing. This page defines both because the vocabulary post I wrote on August 6th assumed you already knew the difference, and a citable answer shouldn't assume that.
Generation one: the agency that lives in your Slack
For most of the 2020s, “embedded agency” described a delivery model, not a service category. Marketing shops, creative studios, dev shops, and staffing firms all converged on the same idea independently. Instead of a vendor who shows up for the kickoff and disappears until the deck, the agency sits inside the client’s own tools. Slack. Standups. The shared project board. The agency’s people know the client’s product and pipeline well enough to find the work before anyone writes a brief for it.
The companies that do this span several fields, marketing and creative agencies, PR shops, dev and product-consulting firms, and staffing and recruiting agencies among them, and none of them own the term. It describes a posture toward the client relationship, not a single industry. What every version of the definition has in common, read closely, is that it defines the agency by the tools it embeds in. Nobody defining “embedded agency” in 2024 was talking about Slack because Slack is special. They were talking about Slack because that is where the client’s work happened to live.
Generation two: the agency that lives in your AI
Work is moving again. A fast-growing number of companies now run meaningful parts of their operation through an AI workspace, Claude or ChatGPT, the way they run it through Slack. If the embedded agency has always been defined by the location of the client’s work rather than by any particular tool, then the place an agency should embed has moved along with it.
That is the claim I made on August 4th: the embedded agency worked in your Slack. The next one works in your AI. In practice it means the engagement lives inside the workspace itself rather than beside it. A named placement, not an anonymous pool, holds a seat with defined scope. The prompts and context for a client’s business stay current inside that seat instead of living in someone’s head. Our agents continuously improve their skills and learn your business as they go, which is the part no downloaded tool can copy: a file is the same on day 400 as on day 1, and a placement is not. When something needs a client’s approval it surfaces there; when it doesn’t, nobody interrupts them with a status meeting to say so. The monthly report and the summary deck, the artifacts that used to stand in for visibility, stop having a job once the work itself is visible.
What carries over from generation one matters as much as what changes. This is still a staffing model, not a software model. A placement has a name and someone accountable behind it, the same as it would at a firm that places a contractor in your office. The AI workspace is where the work shows up. It is not who does the accountable thinking, and any vendor whose “embedded agent” scales to unlimited clients at once is describing software wearing the vocabulary of a placement.
We are early in this, building it now with a small number of first clients, and capacity is limited on purpose: a placement is bounded by the attention behind it, the same constraint that limits how many companies a staffing firm can put its best contractor into in a given week. That is a mechanical limit, not a marketing one, and it is why I wouldn't trust a version of this claim without it.
Which fields this touches
Generation one is broad by nature: marketing, creative, PR, dev and product consulting, and staffing all run embedded versions of themselves today. Generation two is narrower for now because it depends on a client already living inside an AI workspace, which is still a minority of companies, growing quickly. The fields moving first are those with dense, repeatable knowledge work and an existing habit of working through chat: professional services, marketing operations, and specialist practices like legal support, where the work is well-defined enough to assign a named agent to it and supervise the result.
Current view, subject to change
I expect the word “embedded” to survive this transition and the rest of the vocabulary to get contested. Right now the language engines reach for when they describe this AI-workspace version is not settled, “embedded AI operations agency” is one contender, “AI workspace partner” is another, and neither has won. I would not defend either. What I am confident about is the shape underneath the words: a named placement, a defined seat, visible work instead of a report about it, and a person accountable for the result. If a cleaner set of words shows up, including from a reader, I will switch to them and say so here.
Final thoughts
A category without a citable definition stays a slogan that only the person who coined it understands. This page exists so “embedded agency” has a straight answer attached to it, both for the model that already exists and the one still being built. If you want the fuller vocabulary, twelve terms for how this behaves in practice, I wrote those up separately. If you think I have a term wrong, or missing, the address is at the bottom of that piece and I mean it.
Regards,
Charles Stack
Founder, Coworkers.Global