Braze's CTO Rethinks Engineering for AI-Driven Growth
· dev
The Agentic Imperative: Why Braze’s CTO is Redefining Engineering Leadership
The role of chief technical officer (CTO) has never been more critical as technology continues to evolve at an unprecedented pace. Jon Hyman, co-founder and CTO of Braze, a customer engagement platform, has led his organization through nearly 15 years of growth and has valuable insights on how he’s approached this evolution.
The Rise of the Agentic Organization
Braze’s transformation into an AI-first team is driven by the agentic imperative – the need for organizations to rethink their leadership structures in light of emerging technologies. The mobile revolution brought unprecedented demands on scalability and speed, requiring engineers and engineering managers to have a strong understanding of how to scale and make products that work. As AI plays an increasingly prominent role in software development, traditional notions of leadership are being upended.
Hyman notes that his organization’s experience shows the importance of having a clear understanding of how to scale and make products that work, particularly when dealing with emerging technologies like AI. This requires a different set of skills from leaders, including the ability to understand complex technologies, communicate effectively with teams, and drive adoption across large organizations.
From On-the-Ground General to AI-Savvy Leader
Hyman’s own evolution as a leader reflects this shift. He has moved from being deeply involved in the technical underpinnings of products – what he calls “a on-the-ground general” – to an AI-savvy leader who can engage with engineers and product managers alike. This new role requires leaders to be able to understand complex technologies, communicate effectively, and drive adoption.
The Challenge of Measuring AI’s Value
One of the key challenges facing Hyman and other leaders is measuring the value that AI brings to their businesses. As he notes, it’s not enough simply to mandate AI adoption – model quality must be prioritized, and skeptics must be won over through effective communication. This requires a clear understanding of how to measure the value of AI in practice.
Braze has found that investing in AI-powered development requires significant upfront costs, but these investments can pay off in the long run by improving product quality and efficiency. However, leaders must be able to communicate the benefits of these investments effectively to stakeholders.
The Surprisingly Steep Cost of Inference at Scale
As more companies embark on their own AI journeys, they’re beginning to realize that inference – the process of applying trained models to new data – comes with a steep cost, particularly at scale. Braze’s experience shows that these costs can quickly add up, but leaders must be able to mitigate them through effective planning and investment.
What Comes Next for Autonomous Agents
Hyman’s conversation with Bailey highlights the growing importance of autonomous agents in software development. These agents are capable of building features overnight, but this raises questions about traditional notions of leadership and engineering. Will we see a shift towards more decentralized decision-making, or will companies find ways to maintain control over their AI-powered development pipelines?
As Braze continues to navigate the rapidly evolving landscape of software development, Hyman’s insights offer valuable lessons for leaders across the industry. His story serves as a reminder that effective leadership in this new landscape requires a deep understanding of emerging technologies and the ability to communicate effectively with teams and stakeholders.
Editor’s Picks
Curated by our editorial team with AI assistance to spark discussion.
- AKAsha K. · self-taught dev
Braze's CTO Jon Hyman is right to emphasize that AI-driven growth demands a new kind of leader: one who can straddle technical and business domains. However, scaling this expertise across an entire organization won't be easy. As teams begin to rely on AI-driven decision-making, there's a risk that leadership will become increasingly siloed, with technical leaders speaking only to their peers and business leaders lost in jargon. To mitigate this, organizations need to prioritize cross-functional collaboration and education – making sure that both technical and non-technical stakeholders have a basic understanding of AI's capabilities and limitations.
- TSThe Stack Desk · editorial
While Hyman's transformation from "on-the-ground general" to AI-savvy leader is a compelling example of adaptability in engineering leadership, it raises questions about the scalability of such an approach. As companies like Braze continue to grow, can individual leaders truly scale their influence and technical expertise to match? The article hints at the need for distributed leadership, but more nuance would be valuable: how do organizations balance the demands of scaling AI-driven growth with the evolving role of technical leaders?
- QSQuinn S. · senior engineer
While Hyman's emphasis on adaptability in leadership is spot on, I'd argue that Braze's CTO also needs to prioritize operationalizing AI-driven growth across the entire organization, not just within engineering teams. This means investing in processes and infrastructure that can scale alongside emerging technologies, rather than simply relying on individual leaders to drive change. By doing so, organizations like Braze can ensure that their strategic decisions are informed by data-driven insights, rather than gut feeling alone.