AIWA "The One Thing" #19: Anthropic. OpenAI. Google. Forward Deployed. Fully Funded.

Three threads have been worth watching across three consecutive months last year.

The first one came in July.

Enterprise AI is not a one-dimensional technology problem. It is three-dimensional.

People, Process + Technology.

*Link to OpenAI post above

The second came from Massachusetts Institute of Technology in August.

95% of enterprise AI pilots fail.

Not because of the models. Because of the learning gap.

*Link to the MIT post above

The third ran in September, in response to a The Wall Street Journal piece arguing AI was killing the consulting industry.

The counter-argument: this is not the death of consulting. It is the birth of Consulting 2.0.

The complexity of enterprise AI implementation will make the firms that evolve indispensable. The piece named Forward Deployed Engineers (FDEs) as part of the mechanism.

*Link to the WSJ post above

In the months since, the open question was whether the FDE model and the broader reinvention of consulting were workarounds or the answer.

Last week, the labs answered.

Anthropic announced an enterprise AI services JV with Blackstone, Apollo, Hellman & Friedman and Goldman Sachs. Hours later, OpenAI launched the OpenAI Deployment Company with $4 billion of initial investment and a consortium led by TPG, Bain & Company, Brookfield and McKinsey & Company.

*Link to the Anthropic + Blackstone Press Release

*Link to OpenAI Deployment Company announcement

A few days later Google doubled down on its go-to-market team’s investment in Forward Deployed Engineers.

*Link to Google's FDE announcement

Three frontier labs. Days apart. Billions in capital. One quiet admission.

The press releases sell the upside.

The single line that does the real work belongs to Anthropic:

"Claude's capabilities change on a monthly or even weekly basis, which creates a different kind of engineering challenge than traditional software deployment."

That is not a marketing line. That is an architecture statement.

The job descriptions tell you what the work actually is.

Google's FDE is a "builder-consultant, moving beyond architecture to code, debug, and jointly ship bespoke agentic solutions."

The work itself: "architecting and coding the connective tissue between Google's AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters."

The September 2025 piece had a sharper framing for it.

In enterprise AI, the model is the easy part. The hard part is framing the right problem, building the data plumbing, designing the org, and bringing people along the way.

That is the work the labs just funded at billions of dollars.

From my vantage point, inside FDE pods, this is familiar territory.

A senior operator FDE paired with a deeply technical lead. Code over decks. Solutions over strategy artifacts. Connective tissue between the C-suite and the engineering team.

The labs and their partners just announced billions in FDE capacity.

Whether it’s FDEs committed to one lab’s frontier technology or FDEs that are technology agnostic, we all hit the same wall once we land.

The model is ready. The pod is ready.

The data and knowledge layer underneath, the part below the waterline, usually isn’t.

That is the next bottleneck.

More on that in the coming weeks.

Humans + Machines. Never Humans vs. Machines.