Every time there’s a major technological shift, something interesting happens.
Customers don’t fully understand the new technology yet. It’s unfamiliar. Unproven. Sometimes intimidating.
And in those moments, forward-deployed experts — people embedded close to the customer — have consistently played a critical role.
They don’t just deliver software. They educate, bridge the gap, and accelerate adoption.
Companies that master this model often go on to dominate their industries.
🏛 A Brief History of Forward Deployment
This is not a new idea. We’ve seen this story unfold multiple times.
SAP in the 1990s:
When SAP introduced its enterprise software suite, most companies didn’t fully understand how to configure or extend it for their unique business processes.
SAP solved this by deploying engineers onsite who built on the ABAP programming language. These engineers became trusted guides, configuring the platform in real time. That strategy helped SAP become an enterprise powerhouse.Palantir in the 2010s:
Palantir took a similar approach. It embedded engineers directly at customer sites, working shoulder-to-shoulder with users to build AI-powered applications on top of their platform.
The result: faster value delivery, deeper customer trust, and massive defensibility.
Lesson: Forward deployment isn’t just implementation. It’s a strategic growth lever.
🤖 From Shipping Features to Shipping Agents
The nature of software itself is changing.
The old model looked like this:
Build features
Ship them
Wait for adoption
This was rigid, linear, and slow.
The new model is different:
Build AI agents that are purpose-built for specific domains
Ship those base agents
Let Forward-Deployed Product Managers (FD-PMs) configure and extend them in real time with customers
Product iteration doesn’t happen in a distant backlog anymore.
It happens at the edge — inside the customer’s environment.
“Product no longer ends at launch. It begins at deployment.”
🧭 The Role of the Forward-Deployed Product Manager
Forward-Deployed PMs are not engineers in the traditional sense.
They don’t write code. But they do something equally powerful: they use AI-native tools to configure, extend, and activate platform capabilities.
They work at the intersection of:
The Platform (where the AI agents live)
AI Tools (low-code, no-code, orchestration, grounding, prompting)
Customer Context (real-world workflows and edge cases)
This role is emerging because speed matters. Customers can’t wait months for features. They need outcomes now.
🧠 The FD-PM Skill Stack
Forward-Deployed Product Managers bring a new kind of toolkit.
AI Awareness & Prompting:
Understand AI models, how prompts shape behavior, and how to design probabilistic experiences.AI-Native Prototyping:
Use low/no-code tools and APIs to build fast and co-create with customers.Context Engineering & Guardrails:
Grounding, retrieval, orchestration, and constraint building — making AI reliable and explainable.Error Analysis & Evaluation:
Manual and automated evaluation loops to improve quality continuously.Product Thinking:
Translate customer jobs-to-be-done into structured, scalable product artifacts.
This is product management reimagined for the AI era.
🆚 FD-PMs vs Professional Services
This is not “services in disguise.”
Professional Services Forward-Deployed PMs Implements after product is built Co-creates productized solutions Execution-focused Product thinking + execution One-off work Configurable, scalable patterns Linear cycle Real-time iteration
The difference is not just speed — it’s strategic leverage.
🌍 Why This Matters
SAP and Palantir both understood the power of forward-deployed models.
Their success stories weren’t just about technology. They were about how the technology reached customers.
We’re now at a similar inflection point with AI.
Instead of shipping static software, companies will ship AI agents, and forward-deployed product managers will bring them to life at the edge.
“If SAP and Palantir built with forward deployed engineers, the next decade will be built by forward-deployed product managers with AI Agents.”
📬 If you’re building AI products or rethinking your product org structure, this is a moment worth paying attention to. The future of enterprise software won’t be built in backlogs. It’ll be built at the edge.
