Building for a Company of Builders | Lithic

Building for a Company of Builders

March 11, 2026

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Johnie Lee

Director of Engineering

Claire Jacobs

Senior Product Marketing Manager

Table of Contents

At Lithic, we're building a company of Builders. Not in the Silicon Valley platitude sense, in the literal sense. Everyone builds.

Let me explain what that means, how we got here, and where we think this is going.

Builders and Operators

For most of tech history, companies have been split into two camps: Builders and Operators.

Builders: Product and Engineering — wrote the code, shipped the features, and designed the systems. Operators: Operations, Support, Finance, Marketing, Sales, Legal, HR — made the product actually work for customers. Builders also built the internal tools that Operators used, which meant Operators were perpetually waiting in line for engineering capacity to solve their problems.

This divide was never clean, and the best companies have always tried to blur it. But there was always a ceiling. Operators could push spreadsheets and manual processes only so far. Real software still required real engineers, and that dependency created a permanent bottleneck between the people who understood the problem best and the people who could build the solution.

That ceiling is gone.

The Lithic Builder Vision

Our CEO, Bo Jiang, has pushed a vision for what Lithic should become: a company where everyone is a Builder. Not as a title. Not as an aspiration. As a practice.

Everyone, from Product and Engineering to Data Analysts to Marketing to Risk to Legal to HR, is expected to be able to build tools, automate workflows, and solve their own problems with the help of AI. And they are.

Here's what that looks like in practice:

This is what a company of Builders looks like. They saw problems, and they were empowered to solve them.

Building the Company of Builders

These stories didn't happen by accident. Over the past year, one thing we've learned is that AI transformation is not primarily about technology. It's about organizational design. The hardest problems in technology adoption aren't technical, they're human. It's not enough to pick the right tools. You have to transform how people and organizations work.

Governance First

Before a single tool was purchased, we worked with our legal team to establish a clear acceptable use policy for AI. For a company handling sensitive financial data on behalf of clients and their customers, this wasn't a checkbox exercise. We wanted every employee to understand not just what the rules were, but why they existed, so that judgment calls in ambiguous situations would land in the right place.

The most critical requirement was straightforward: any AI tool adopted at Lithic could not train on our data. Full stop.

Let a Thousand Flowers Bloom

With guardrails in place, we gave every engineer a budget to purchase and try whatever AI tools they were curious about, then asked them to share findings through dedicated channels and knowledge-sharing sessions.

This approach was deliberate. Like every major technological shift before it, from dotcom to mobile to cloud, real adoption comes from the grassroots. Picking technologies top-down doesn’t yield the same success.

Trust Compounds

One of the more important observations from the past year is how AI adoption evolved as people built trust in the tools.

Early on, the use was narrow: AI as a sophisticated autocomplete, useful for syntax, boilerplate, and quick lookups. As trust developed, engineers started delegating more - pair programming, handing off discrete tasks. More recently, the scope has expanded significantly. It's now possible to delegate an entire project workstream to AI, requirements, design, implementation, and testing, with an engineer directing and reviewing rather than writing line by line.

The results were hard to ignore. Engineers using AI saw a 3-5x increase in velocity versus those who didn’t, and the quality gains were just as significant.

AI With Company-Wide Context

Last year, the AI landscape was crowded with competing visions. Without a clear point of view, it would have been easy to end up with a dozen disconnected tools and no coherent strategy.

We identified vendors that fit into this paradigm and started building internal tooling to access our systems from within our AI platform. A year later, that vision has proven out. AI is now the kick-off point for most work across the company.

Building Forward

A few years ago, "company of Builders" was a vision. Today, it's how we work. Our Head of Support builds his own tools. Our Data Analysts build automation pipelines. Our legal team builds review workflows. Our designers ship features. None of them waited for permission to get started. They saw problems, and they built solutions.

The technology will keep evolving, better models, smarter agents, deeper context. But the foundation that makes all of it work isn't technical. It's a culture where everyone is expected to build, empowered to build, and supported to build safely. That's what we've been building for. And we're just getting started.