The FDE Shortage Is Real
Every company rolling out AI agents at scale is saying the same thing: we cannot hire enough Forward Deployed Engineers. The shortage is not just a hiring problem. It is a structural issue about what it actually takes to get AI deployed inside a real enterprise.
FDEs sit at the intersection of product, engineering, and customer success. They go on-site, understand actual workflows, and configure the product to work inside those workflows. They are not building from scratch. They are not doing basic support. They are doing the hard middle work of making software actually land in the real world.
Palantir built their entire go-to-market around this model. You could not buy Palantir and self-serve your way to value. You needed their people inside your organisation. That model was expensive and did not scale the way SaaS was supposed to scale. But it worked.
Now almost every serious AI product has the same requirement. Palantir announced recently they have gotten deployment times down over 90% using FDEs. That is remarkable. It also means the best-in-class operator in this model is still deploying manually, just faster. 90% reduction in deployment time is not the same as automating deployment.
Why CS Cannot Fill This Gap
The instinct at most companies is to solve this with customer success. CS is already post-sale, already focused on adoption. Just upskill them, right?
Wrong.
Traditional CS was built for a different era. The job was: help customers use software they have already decided to buy, make sure they hit their renewal metrics, escalate bugs. It was reactive, relationship-driven, and optimised for retention.
FDE work is different in almost every way. It is proactive, technical, and optimised for deployment. You are not waiting for a customer to have a problem. You are going in before the problem exists and configuring the system so the problem never happens.
The skill set required is closer to a solutions engineer or a junior product manager with strong customer empathy than it is to a traditional CS rep. Most CS teams do not have it. Retraining takes longer than most companies want to admit.
Agents Cannot Deploy Themselves
The whole premise of AI agents is that they automate work. But deploying an AI agent is itself significant work, and it is work the agent cannot do for you. Not yet.
Someone has to understand the customer's workflows deeply enough to know where the agent fits. Someone has to train the agent on the right data, the right context, the right edge cases. Someone has to test it, catch where it breaks, and iterate. Someone has to get internal buy-in from the people whose jobs will change when the agent goes live.
That is FDE work. And it is manual, high-judgment, human work.
A $6 billion AI company recently had an agent quoting incorrect pricing after a year in beta. No one had properly trained the agent. The company's own people had not done the deployment work on their own product. If a $6 billion AI company cannot train its own agent correctly after a year in beta, imagine what is happening inside the enterprises buying these tools.
What This Means for ANZ Sales Teams
Every serious AI vendor is now competing for the same small pool of people who can do this work. The companies that came up through Palantir, the solutions engineers from the major cloud platforms, the implementation consultants from the enterprise software world. Everyone wants them, and there are not enough of them.
Palantir maintains a modest ANZ presence with roughly 50 to 70 headcount across Sydney and Melbourne, focused on government and defence sales. Sales team size here is small, around 10 to 15. Growth lags the US and Europe due to regulatory hurdles in public sector AI deployments.
Meanwhile the demand is exploding. Every enterprise that decides to deploy AI agents needs FDE-caliber people to make it work.
What Works
Three things worth considering if you are selling AI tooling:
Do group training. The companies winning at deployment are building serious enablement programmes, not just documentation, but hands-on training that gives customer-side operators the skills to configure and train agents themselves. If you cannot train them one-to-one for smaller deals, at least try to do it in groups.
Hire for deployment instinct, not just technical skills. The best FDEs are not always the most technically deep. But they really need to know how AI agents work and how enterprises actually operate.
Budget for it. If you are a sales leader evaluating AI tooling for your team, ask who is doing the deployment work. If the vendor says "it is self-serve" or "CS will handle it," you are probably looking at a six-month implementation that the vendor thinks will take six weeks. Real deployment requires real people. Make sure someone is paying for them.