AI DevSummit 2025 + DeveloperWeek Leadership 2025: Full Schedule

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1:00pm PDT

PRO Session: One Thousand People, One Roadmap

Thursday May 29, 2025 1:00pm - 1:25pm PDT

Fabricio Buzeto, Brex, Engineering Manager

As a company grows, the tendency to divide and conquer can nurture siloed goals that do not align with the company. Impeding the ability to deliver constant and meaningful improvements. The natural tendency is to increase bureaucracy and control, which usually only hinders the results. Companies like Airbnb and Brex have been in the headlines for trying the opposite. Reducing layers and bureaucracy while bringing alignment and increasing velocity. Let me tell you about what I learned while living in such a reality.

Speakers

Fabricio Buzeto

Engineering Manager, Brex

Fabricio has a Ph.D. in Computer Science and is currently an Engineering Manager at Brex. For the past 20 years have been developing software in distributed teams focused on digital products consulting for both big and small organizations. Amongst his own ventures, it can highlight... Read More →

Thursday May 29, 2025 1:00pm - 1:25pm PDT
DeveloperWeek Leadership Expo Stage

DeveloperWeek Leadership

Additional Topics Cross-functional Collaboration, Technical Decision Making, Team Collaboration, Learning and Development, Leadership Career Paths
Session Type OPEN Session
Tracks DeveloperWeek Leadership, Technical Leadership / Management & Teams (Managing People) (DeveloperWeek Leadership), Strategy / Methodology & Tooling (DeveloperWeek Leadership), OPEN Session, Career Development: Impact & Change (DeveloperWeek Leadership)
In-Person/Virtual In Person

2:00pm PDT

PRO Session: Decoding Enterprise AI for Devs: Choosing Between Private LLMs and Public Generative AI Services

Thursday May 29, 2025 2:00pm - 2:25pm PDT

AI DevSummit Main Stage

Shomron Jacob, Iterate.ai, Head of Applied Machine Learning & Platform

This AIDev Summit session will navigate an increasingly pivotal crossroads: the decision between investing in proprietary, custom-tailored Large Language Models (LLM) or capitalizing on the versatility and ease of public generative AI services.

The session will begin by demystifying the complexities of private LLMs. With domain-specific capabilities and enhanced data security, these models have faster customization and compliance with industry-specific regulations. Yet, they also pose challenges: a bigger investment, infrastructure requirements, and ongoing maintenance. These elements necessitate a thorough examination.

Next, the session will scrutinize public generative AI services, exploring the inherent benefits of these ready-to-use solutions. With their scalability, diverse applications, and lower upfront costs, they hold significant appeal. But they also come with their own set of considerations, such as data privacy, standardized performance, and reduced control over the model’s behavior.
With real-world examples, we will walk through how various organizations have approached this decision, the results they achieved, and the invaluable lessons learned.

The session will then go into a decision-making framework, with the purpose of enabling attendees to assess their options between private LLMs and public generative AI services more effectively.

Speakers

Shomron Jacob

Head of Applied Machine Learning & Platform, Iterate.ai

Shomron Jacob is the Head of Applied Machine Learning & Platform at Iterate.ai. Shomron began his career as a software engineer but soon found himself learning ML/AI and switched his professional direction to follow it. He lives in Silicon Valley.

Thursday May 29, 2025 2:00pm - 2:25pm PDT
AI DevSummit Main Stage

AI DevSummit

Additional Topics Generative AI, LLMs, Governance and Regulation, AI Integration Strategy, AI Product Strategy, Technical Decision Making, AI Strategy and Leadership
Session Type PRO Session
Tracks AI DevSummit, AI Leadership & Strategy (AI DevSummit), DeveloperWeek Leadership, Strategy / Methodology & Tooling (DeveloperWeek Leadership), Machine Learning / Models & Architectures (AI DevSummit)
In-Person/Virtual In Person