OpenAI’s New Weapon: Forward Deployed Engineers
From LLM darling to enterprise operator. OpenAI is shifting from product to services. Here’s why it’s a bold power play with a billion-dollar upside.
OpenAI was in a league of its own.
They built the most recognizable GenAI brand. They shipped ChatGPT. They opened the world’s eyes to what large language models could do.
But then the market got crowded. Google, Meta, and Anthropic launched competitive models. And even Microsoft, OpenAI’s closest partner, began aggressively productizing AI across its own ecosystem.
Enterprise interest exploded but deployments stalled. Everyone wanted “ChatGPT for my business,” but most orgs didn’t have the tech stack, data readiness, or AI maturity to pull it off.
OpenAI’s product-led motion hit friction. The models were brilliant but the execution gap was real.
That’s when OpenAI made its move.
They went full Palantir.
OpenAI’s New $10M Consulting Arm
In a major shift, OpenAI has launched a dedicated consulting division, designed to help large enterprises build custom AI systems that solve real, revenue-linked problems.
Here’s what we know:
Minimum engagement? $10 million.
This isn’t advisory services. It’s full-stack, in-the-weeds implementation.
Strategy? Borrowed straight from Palantir.
OpenAI is embedding Forward Deployed Engineers (FDEs) inside client orgs—engineers who live, breathe, and build within your workflows.
Goal? AI systems tailored to your proprietary data, processes, and outcomes.
These aren’t one-size-fits-all models. These are bespoke, operational AI solutions.
Industry experts predict this consulting arm could generate $5–10 billion in early revenue, with potential to scale to $50–100 billion annually as enterprise demand intensifies.
What Is a Forward Deployed Engineer (FDE)?
A Forward Deployed Engineer is OpenAI’s enterprise Swiss Army knife.
These engineers aren’t just coding. They’re embedding within your team, mapping high-leverage problems, and shipping full-stack solutions built around frontier models like GPT-4o.
From the OpenAI job description:
“You’ll embed with customers where model performance matters, delivery is urgent, and ambiguity is the default.”
Translation: You’ll be dropped into chaos with a laptop and expected to make AI magic before Friday.
An FDE’s job is to:
Own end-to-end technical delivery
Build full-stack AI systems that integrate with your existing ops
Drive model adoption with speed and clarity
Share field insights to influence OpenAI’s product roadmap
This role is the fusion of strategy, engineering, and execution.
If you’re leading a transformation, FDEs are your elite AI task force. They land fast, build smart, and deliver outcomes that stick.
A Shifting AI Landscape
OpenAI’s pivot doesn’t just expand their business. It reshuffles the competitive deck.
By embedding engineers and building fully custom solutions, OpenAI is stepping into competition with:
Palantir, whose embedded software + services model has dominated defense and enterprise
Accenture, whose AI transformation services are now a top growth driver
Vertical AI startups, building copilots for law, finance, healthcare, and other high-margin industries
OpenAI isn’t just shipping models…they’re executing outcomes.
And that threatens anyone who’s been filling the “AI implementation” gap.
If you’re a founder, consultant, or tech buyer: Your competitive landscape just changed.
And OpenAI’s pricing power, brand trust, and model performance give them a serious edge.
Why OpenAI Is Betting Big on Consulting
This is more than just a services play. It’s a long-game strategy grounded in three critical truths:
AI is hard to implement well.
Most enterprises don’t need more models. They need help applying them, in particular inside regulated workflows, messy datasets, and legacy infrastructure.
Custom beats generic.
OpenAI knows enterprises want tailored copilots, not “prompt engineering 101.” Their move is designed to own the outcome, not just the model.
Execution drives retention.
By embedding directly in the org, OpenAI increases quality, reduces failed pilots, and locks in long-term, sticky revenue.
It’s no longer just about who has the best models. It’s about who can implement them effectively and drive real business performance.
Real-World Momentum
This isn’t a theory. OpenAI is already:
Running a $200M engagement with the Pentagon
Partnering with Grab to enhance Southeast Asia’s regional mapping
Hiring top talent from Palantir to lead the charge on enterprise execution
They’re moving fast—and so are their clients.
The Tradeoff: Services vs. Scale
Yes, consulting services come with headcount, overhead, and scalability challenges.
Service-heavy models can compress valuations (we’ve seen it with HubSpot and others)
Human capital doesn’t scale like APIs
Hiring and retaining A+ FDEs at scale won’t be easy
But the upside?
Deeper control of the AI lifecycle
Tighter customer lock-in
And a pathway to billions in enterprise revenue that pure product models can’t capture fast enough
What This Means for Your Business
This is your cue to move.
OpenAI isn’t sitting back hoping you adopt their tools. They just signaled a massive shift in how advanced tech companies go to market.
They didn’t build another product. They built a high-ticket, human-led solution layer that embeds inside the enterprise.
If you’re building a SaaS, AI tool, or consulting firm, this changes the game:
1. Product ≠ Value Without Implementation
OpenAI is betting that even the world’s most advanced AI models don’t sell themselves. They need interpretation, integration, and iteration.
Takeaway: If your product doesn’t come with a path to real-world outcomes, someone else will fill that gap—and get the credit (and the budget).
2. Move from Product-Led to Outcome-Led
The future isn’t “try our tool.” It’s “we’ll deliver the outcome.”
Start thinking like this:
Can your product offer a “done-for-you” version?
Can you partner with implementation experts?
Can you create a white-glove onboarding or embedded team model?
3. Monetize Your Expertise, Not Just the Software
Enterprise buyers don’t just want features—they want wins.
Layer services around your product like strategic workshops, technical audits, or embedded specialists. That’s where real margin (and loyalty) lives.
4. Adopt a Hybrid Model Like Palantir and OpenAI
Software + embedded experts + custom AI = higher retention, faster value delivery, and way more revenue potential.
Start small. Offer a “concierge” tier. Or launch a pilot program with a strategic customer.
Build Your Own Forward Deployed Engineer (FDE) model
You don’t need FDEs on payroll to win. Here’s how to replicate OpenAI’s strategy in-house:
For Corporate Leaders & Enterprise Teams:
Here’s your mindset shift:
Stop thinking of AI as a “tool to roll out.” Start treating it like a “problem-solving function to embed.”
Where to start:
Identify your highest-impact departments (RevOps, Customer Success, Compliance).
Assign internal AI-savvy talent (even just power users) to partner inside those teams.
Give them a mandate: embed, experiment, execute.
No more PowerPoints. No more AI “centers of excellence” sitting on the sidelines. You need in-the-field operators driving change. Just like OpenAI.
Even better? Pair them with your IT or automation teams and train them to deliver AI outcomes, not just recommendations.
This is how you become the AI-native enterprise your board is asking for.
For Founders & Startups:
This is your unfair advantage.
While your competitors build features, you build field success.
Offer implementation packages
Hire or train customer-facing engineers who don’t just “support” but embed and optimize
Position your team as the “outcome accelerator”, not just a software vendor
This unlocks premium pricing, longer contracts, and deep product-market fit.
The key?
Stop experimenting. Start solving real business problems.
Final Word: Who Builds the Future?
OpenAI’s consulting move is a power play.
They’ve gone from product-led to outcome-driven.
From pushing tools to embedding teams.
From selling capabilities to shipping transformations.
The next phase of AI isn’t about who has the best model.
It’s about who can embed AI the fastest. And make it work where it matters.
That’s the bar now.
And it’s one you can hit if you build with clarity, speed, and purpose.
#EnterpriseAI #OpenAIConsulting #NoCodeExecution #PalantirPlaybook
If money was no issue, what’s the first AI use case you’d hand off to OpenAI’s consulting team?
Drop it in the comments ⬇️
Let’s build smarter.
– Angela
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