I’ve spent decades watching where tech is headed by following the money, the people, and the job boards. After hearing Kipp Bodnar and Kieran Flanagan break down a simple tactic for reading the AI race, I’m convinced: the smartest signal right now isn’t a keynote or a demo. It’s who the giants are hiring.
My view is clear. If you want to know where AI is going, study the roles the top labs are posting—then build your 12-month plan around those clues. That’s not theory. It’s a practical edge anyone can use.
The Big Tell: Roles Over Roadmaps
Kipp and Kieran point to a habit I’ve used for years in crypto and marketing: track job postings. The insight is simple, and it hits hard for operators.
“Ask it to build a table of open jobs in Google DeepMind, Claude/Anthropic, and OpenAI and show who they’re hiring for. It tells you a lot about their strategy.”
That line stuck with me. Product roadmaps can be vague. Press quotes are polished. Job listings are hard evidence. They show where budget, focus, and urgency live inside these labs.
The most telling trend they flagged: a surge in “forward-deployed engineers”—people who don’t just build models, but sit with customers to make the models work inside real companies.
“They are hiring for forward-deployed engineers… not to swap steam for electricity, but to redesign your business around these models.”
That’s the shift. This isn’t about a few AI features tacked onto old systems. It’s about new workflows, new roles, and new revenue lines shaped around model-native processes.
Why This Matters For Operators
I’ve watched big waves—Web 1.0, social, mobile, crypto—wash over firms that waited for “maturity.” Those firms lost. The winners learned from the builders and moved first. AI is no different. When OpenAI, Anthropic, and Google DeepMind hire customer-facing engineers at scale, they’re telling you three things:
- They expect complex, high-stakes deployments in real businesses, fast.
- They know off-the-shelf won’t cut it for most enterprises.
- They plan to shape operating models, not just ship APIs.
That’s a playbook for you. If the labs are investing in boots-on-the-ground integration, your team should mirror that with cross-functional squads that mix engineering, ops, and revenue.
My Take: Use The Job Boards As Your Strategy Radar
Here’s how I would turn this into action next week using public tools and a few hours of focus:
- Pull current job listings from OpenAI, Anthropic, Google DeepMind, and any model vendor you use.
- Ask an AI assistant to group roles by function: model research, infra, safety, deployment, customer engineering, product.
- Track month-over-month growth by function. Note spikes. Note new role types.
- Map those roles to your business: which ones mirror gaps on your team?
- Pilot one “forward-deployed” motion internally: pair an engineer with a business owner to rebuild a single workflow with a model-first approach.
Explainers and screenshots help, but results win. Pick a process with clear numbers—support resolution, onboarding time, sales follow-up—and measure the lift.
Addressing The Skeptics
Some will say job postings can mislead. Sure, a listing isn’t a signed offer. But patterns across companies rarely lie. When multiple labs post similar roles at the same time, that’s a trend you can bank on.
Others argue that AI still “isn’t ready.” I’ve heard that for every tech wave since dial‑up. The truth is simple: the tech gets ready because operators force it to meet real needs. Early movers shape the standards and lock in advantage.
What To Do Now
Your next step isn’t another brainstorm. It’s a build sprint. Set a 30-day challenge to ship one model-native workflow in the wild. Don’t bolt AI onto a broken process. Redesign the process around the model.
- Choose one revenue-critical workflow.
- Define a single success metric.
- Assign a “forward-deployed” pair: one engineer, one operator.
- Ship a v1 in two weeks, then iterate for two more.
I agree with Kipp and Kieran on the core signal: hiring pages are strategy maps. Read them. Then act on them. The next era won’t reward spectators. It will reward teams that learn from the builders and move faster than the press release cycle.
Build your own forward-deployed muscle now. Study the roles the labs are racing to fill, copy the parts that fit, and ship something that changes how your business works this quarter—not next year.
