How Forward Deployed Engineers Transformed Customer Outcomes for Intercom

If you’ve ever wondered how companies like Intercom scale advanced AI solutions while delivering exceptional customer outcomes, the answer might lie in a unique role: the Forward Deployed Engineer (FDE).

In a recent episode of [Un]Churned, host Josh Schachter sat down with Diego Ballona, Senior Director of Engineering at Intercom, to discuss this very topic. Diego leads Intercom’s Forward Deployed Engineering (FDE) team, a critical unit that helped scale their AI-powered support tool, Fin, from five design partners to an impressive 7,000 customers in just 18 months. Along the way, they achieved a 67% resolution rate for customer interactions—a testament to the power of FDE in action.

As AI becomes more integrated into enterprise systems in 2026, the need for roles like FDE is growing. This is not a traditional engineering role or a rebranded consulting function. It’s an innovative approach to bridging technical execution with business outcomes, particularly for companies scaling AI products or rethinking collaboration between Engineering and Customer Success teams.

What Is a Forward Deployed Engineer?

A Forward Deployed Engineer is a hybrid role that combines the technical expertise of engineers, product managers, and data scientists with the customer-centricity of Customer Success teams. The primary goal of an FDE is to work closely with customers to accelerate outcomes, solve real-world challenges, and turn friction points into scalable product features.

Unlike traditional engineering teams that focus on building and deploying products, FDE teams operate at the intersection of technical execution and customer collaboration. They engage directly with customers, iterating on solutions in real time to ensure success while gathering valuable insights to refine the product roadmap.

Diego Ballona described FDEs as outcome-focused problem-solvers who align their efforts with the customer’s goals. By embedding themselves into customer workflows, these teams deliver value faster and create tools and features that scale across a broader user base.

How Intercom Scaled Fin With FDE

Intercom’s journey with Forward Deployed Engineering began 18 months ago as an experiment. At the time, Fin, their AI-powered customer support agent, was in its infancy, serving only five design partners. Recognizing the potential to accelerate customer outcomes, Diego and his team initiated the FDE model.

With a mix of product managers, engineers, and data scientists, the FDE team worked directly with those early customers to identify friction points and fine-tune the product. The results? Fin scaled from five customers to 7,000, achieving an impressive 67% resolution rate for customer interactions along the way.

Diego emphasized that the FDE motion isn’t about acting as a consulting arm or offering professional services. Instead, the focus is on making customers successful while simultaneously improving the product for everyone. “Our success is the customer’s success,” Diego shared. “Everything we do, from our go-to-market teams to the FDE team, revolves around delivering resolutions and outcomes.”

This dual focus on customer success and product innovation allowed Intercom to transform customer insights into actionable features. For example, early feedback led to the development of Fin’s Slack integration, which quickly evolved from a prototype to a general availability product in just three months.

FDE Team Structure

The team’s structure was also pivotal. Each FDE team includes:

• A Product Manager, responsible for defining requirements and ensuring alignment with customer goals.
• Engineers, who focus on configuration, experimentation, and optimization, rather than creating custom features.
• Data Scientists, who analyze customer metrics and provide insights to prioritize improvements.

Together, these roles form a nimble, outcomes-driven unit that accelerates time to value and strengthens customer relationships.

Why FDE Matters for Scaling AI Products

As AI continues to reshape industries, scaling these technologies requires more than technical capabilities—it demands an ability to navigate the complexities of customer workflows and business risks. Forward Deployed Engineers are uniquely positioned to bridge this gap.

AI systems are inherently non-deterministic, which means they can behave unpredictably. For enterprises, this uncertainty often creates hesitation in adopting AI solutions. According to CIO, the real bottleneck in deploying AI isn’t the technology itself but the talent needed to implement it effectively. This is where FDE teams shine.

By collaborating directly with customers, FDEs uncover the nuanced challenges that arise in real-world applications. They bring these insights back to the product team, ensuring the product evolves to meet the needs of a wider audience. Additionally, FDEs help companies build trust with customers by delivering measurable outcomes and reducing the risks associated with adopting new technology.

At Intercom, this approach not only drove Fin’s adoption but also strengthened its reputation as a reliable AI solution. For companies looking to scale AI products, adopting an FDE model can mean the difference between a promising proof of concept and a transformative business tool.

Watch the Full Episode 

Ready to dive into the full blueprint for building an FDE team at your business? Watch the full episode of [Un]Churned. 

FAQs About Forward Deployed Engineering

• What is a forward deployed engineer? A forward deployed engineer is a hybrid role that combines engineering, product management, and data science expertise with customer-facing responsibilities. FDEs work directly with customers to accelerate outcomes, solve challenges, and improve products.
• How does FDE differ from professional services? While Professional Services teams typically focus on implementing and customizing solutions for individual customers, FDE teams aim to drive broader product improvements. By addressing customer-specific challenges, FDEs create scalable features that benefit the entire user base.
• What types of businesses benefit most from FDE? FDE is particularly valuable for companies scaling AI products or those operating in complex, customer-centric industries like SaaS. Businesses that want to accelerate time to value, improve customer outcomes, and gather actionable product insights are ideal candidates for this model.