Bringing the Full Stack Builder to Life

A few months ago, I shared our vision for the Full Stack Builder (FSB) model and the transformation we’re driving at LinkedIn. This follow-up dives deeper into why this model is so critical and how we’re bringing it to life.

Full Stack Builder: Why Now?

Technology has always been about empowerment. It’s not just what tech does for us, but what it enables us to do. The Full Stack Builder model is about returning to that core purpose -- creating a true meritocracy where great builders can bring ideas to life with speed and quality, pushing the efficient frontier of product development.

This isn’t just an opportunity. It’s a necessity.

We’re entering a phase where the time constant of change >> the time constant of response. To stay competitive, we must build faster, better, and more frequently. That requires going back to first principles and redesigning how we build from the ground up.

What’s Broken Today

At the heart of every company you have a builder, and their goal is simple: take an insight and bring it to life. To do this right, there are a few key steps every builder needs to take: from researching the problem and designing the solution to coding and ultimately shipping it.

That’s easier said than done, though. Over time this process got super complex, very quickly. Each step expanded to many sequential sub steps. For example, researching the problem requires not only spending time with users and customers but also doing data analyses, looking at feedback tickets, doing research studies, and so on.

And there is a valid reason for each step. BUT, today as a  result, in many at-scale companies building a small feature requires hand-off across many teams, multiple code bases, and takes several sprints before you even get to launch. And launch itself is not even a success! you always need to iterate, and so this density multiples.

This happens not because the work itself is complex, but rather because the process is.

Process complexity leads to organizational complexity

The byproduct of this process complexity is also organizational complexity. It leads to roles that have micro specialization. From one builder, we’ve grown into multiple functions, and then added many sub-specialities. And when you start to include all the different levels, almost without noticing, you end up with a very dense & complex organizational stack:

So when you look at all the roles and all the steps required to bring an idea to life, you suddenly realize that we moved from builders to assembly-line workers.

Now we have an opportunity to collapse the stack, return to craftsmanship & dramatically simplify the product development lifecycle

Introducing the Full Stack Builder

The Full Stack Builder (FSB) is a new archetype, streamlining how we build and also raising the bar on who builds. A full stack builder is capable of developing experiences end-to-end, combining skills & expertise across traditionally distinct domains -- not just as a sequence of steps but as a fluid partnership between human and machine.

When we look back at the product development lifecycle, we want to make sure the majority of the time spent is on things that great builders shine in, including:

• Vision: developing a compelling stance about the future 
• Empathy: profoundly understanding an unmet need
• Communication: aligning and rallying others around an idea
• Creativity: imagining possibilities beyond the obvious
• Judgment: making high quality decisions in complex, ambiguous situations 

Everything else? We want to automate it.

The benefit is not only the ability to prototype and iterate quickly. Now, teams can now form on-the-fly more quickly to tackle emerging priorities and get more shots to innovate. Ultimately, we are enabling a resilient, adaptive, and forward-thinking organization that can navigate the future.

How are we bringing FSB to life at LinkedIn?

For a new startup, adopting the FSB model from day one is straightforward. For a mature company with a large product and organizational stack, it’s a complete transformation. And like any major technological revolution shift, it requires rethinking three core areas: Platforms, Tooling, and Culture.

1. Platforms

Large Language Models (LLM) coding solutions struggle with messy, legacy codebases. Productivity gains are limited if your foundation isn’t built for AI-native development. At LinkedIn, we’re re-architecting our core platform from the ground up (codename Project Nile which we’ll share more about in a future tech blog). This effort breaks our applications into simple, composable UX components that AI can reason over and code against. Think of it as re-platforming our codebase so it can work seamlessly with AI.

This also highlights a key point: we need System Builders to empower Full Stack Builders. System Builders create and maintain the platforms and tools that enable the FSB model at scale.

2. Tooling

Platforms are foundational, but they’re not enough. We’ve had to rethink our tooling end-to-end, starting from the problem statement all the way through design, code, and launch. We look at it in two steps:

Problem Statement → Research → Solution → Roadmap → Design

Today, much of this work is slow, fragmented, and specialist-driven. We’re building domain-specific AI agents to change that, such as:

• Research agents - Trained on our top-priority audience segments and internal insights across our key sources of information, these agents enable on-demand access to rich member understanding. For example: A Builder researching the SMB segment can have a live, conversational interaction with a realistic archetype of a small business owner (generated by the agent using real member insights & studies). This virtual persona shares rich detail about their business type, company size, day-to-day challenges, and decision-making behavior. It’s like running a qualitative interview, but instantly and at scale.
• Growth agent - This agent specializes in our growth playbooks. It ingested all past experiment results, internal playbooks, and our product input/output drivers to proactively analyze, criticize and suggest new growth opportunities. For example: A Builder with a new product idea can ask the Growth Agent to map out the ideal growth funnel and identify optimization levers unique to LinkedIn at every stage. 
• Trust agent - Built on LinkedIn’s deep understanding of abuse patterns and defense mechanisms, this agent automates our Trust & Safety review process. It raises the bar for rigor by detecting potential abuse vectors before they reach production. For example: A Builder can upload their product spec, and the Trust Agent will proactively analyze it for LinkedIn unique abuse vectors such as spam entry points, account-takeover risk, etc. It flags vulnerabilities and recommends mitigations.
• Design agent - Trained on LinkedIn’s design systems, this agent will convert specs and prompts into shippable products depending on the type of design work needed. For example: In case we need more exploratory design work, a prompt can go right to prototype using LinkedIn’s design systems. But for changes to existing flows, we can use natural language to produce production-ready code changes.

Design→ Code→ Test → Launch

Once designs are locked, we shift to code and launch with another set of agents:

• Coding Agent - this agent converts natural language prompts directly into production-ready code for modifications to existing LinkedIn experiences.
• Maintenance agent - this agent (codenamed MAE) expands beyond build fixes to detect and repair post-launch issues. For example: For developers today, receiving a broken build ticket is a regular but painful occurrence, disrupting an entire workflow. This agent is able to jump in, test out different solutions to fix the build, and then share a detailed summary for our developer. Today, MAE resolves over 35% of build failures.
• QA Agent - this agent writes tests in natural language to automate testing processes. For example: this agent mimics how our members use the app and can proactively identify and prevent problems before they reach our users.

3. Culture 

Now that the platforms & tooling are in place, the ultimate question arises: if you build it, will they use it?

The answer is No. Culture is the hardest, and most important, part of this transformation. Builders must be empowered to take initiative and adopt a new way of building. It’s like training a new engine: slow at first, then suddenly you’re in high gear.

It requires empowering builders to take initiative & invest the effort in learning a new way of building. It might feel slow at first, almost like training a new engine, but very quickly, full stack builders will be able to shift into high gear. To ensure we support this evolution, we’re updating how we hire, calibrate, and operate. This includes (1) Redefining Expectations: Embedding FSB criteria into how we hire, operate and do performance reviews, and (2) Piloting New Team Structures: Running small pods capable of building end-to-end with our tools.

I am also excited to announce that we are soon launching a new associate program - our Associate Product Builder Program. It’s a new two-year rotational experience for entry level talent to learn the full-stack craft of building products in the AI era. In this program, builders will not just write specs. They’ll build end-to-end, from idea to launch. Including: speccing, designing, prototyping to shipping real features. They’ll learn to think AI-first. To build and lead with purpose.

The Future Belongs to Builders

We’re still early in this journey, but I’m convinced the Full Stack Builder model will define the future of how we build products in the AI era.

When you collapse the stack, empower great builders, and pair them with the right platforms, tools, and culture, you unlock a level of speed, quality, and innovation that will set the next frontier.