DeveloperWeek 2025

Mithun A. Sridharan, Think Insights, Founder

A principles-based framework for AI governance provides a compass to navigate the ethical and responsible development and use of Artificial Intelligence. Unlike rigid rulebooks, these frameworks establish core principles that guide decision-making throughout the AI lifecycle to address the unique challenges posed by different AI systems.

Several prominent examples of principles-based frameworks exist. The European Union's Ethics Guidelines for Trustworthy AI, the Bletchley Declaration, SR 117, and ISO/IEC 42001 are a few frameworks that provide a comprehensive set of principles for organizations to manage AI throughout its lifecycle.

The principles-based approaches provide a strong foundation for navigating the complexities of AI development and implementation. As AI technology continues to evolve, these frameworks can be revisited and refined to address new challenges. By focusing on core ethical principles, they ensure that AI development remains responsible and human-centric. 

Shambhavi Srivastava, Appen, AI Solutions Architect

Data annotation involves assigning relevant information to raw data to enhance machine learning (ML) model performance. While this process is crucial, it can be time-consuming and expensive. The emergence of Large Language Models (LLMs) offers a unique opportunity to automate data annotation. However, the complexity of data annotation, stemming from unclear task instructions and subjective human judgment on equivocal data points, presents challenges that are not immediately apparent.

In this session, Chris Stephens, Field CTO and Head of AI Solutions at Appen will provide a overview of an experiment that the company recently conducted to test the tradeoff between quality and cost of training ML models via LLMs vs human input. Their goal was to differentiate between utterances that could be confidently annotated by LLMs, and those that required human intervention. This differentiation was crucial to ensure a diverse range of opinions or to prevent incorrect responses from overly general models. Chris will walk audience members through the dataset used as well as methodology for the experiment, as well as the company’s research findings.

 

Krishna Sankar, U.S. Bank, SVP/Distinguished Engineer
OWASP Certified 

Yishai Beeri, LinearB, CTO

Generative AI has taken the world by storm since its general availability to the public in early 2023. Going from novel technology to commodity in months, this disruptive technology quickly found applications in the software development world - and many engineering organizations are trying to capitalize on the disruptive technology.

Nearly every engineering organization has adopted, or is thinking about adopting GenAI as a tool for developers. It has become wildly popular for everything from generating code, to writing and deploying tests, pull request reviews, experimentation and PoCs and much more. But who checks the machines?

In this talk I'll dive into the actual measurable outcomes - positive and negative - of adopting GenAI in engineering organizations. While engineering leaders rapidly jumped on the GenAI bandwagon, many are still struggling to quantify its value, not to mention manage its risks. This talk will discuss how and what to measure to understand adoption, quantify benefits and control risks in your initiative to leverage AI in your engineering organization. Join us to learn about the specific metrics you should be monitoring to ensure maximizing ROI on your GenAI engineering org initiatives.

Benji Azaria, Cloudinary, VP Data

Most of our customers do not know how to quantify the time and money we save them, as they don't analyze data or calculate the value we provide. This lack of understanding makes it challenging to renew licenses or secure repeat purchases. If customers understood the exact savings, their satisfaction would increase, leading to internal marketing and higher consumption. Despite having extensive data on customer actions, we've primarily used it internally. Our customers are eager to understand how they compare to competitors, their effective use of our services, and potential growth areas. Providing this information will help them articulate our value and calculate ROI, making license renewals easier. In my presentation, I will detail our process, share industry examples, and highlight the impact on customers and our organization 

Parth Shukla, Cequence Security, Security Analyst
Khyati Ganatra, Cequence Security,  Manager, Applied ML

In the presentation titled "AI Frontiers: Shielding Digital Gateways from Bot Invasions," we delve into the forefront of cyber defense against bot-driven threats that exploit API vulnerabilities. This comprehensive study explores how advanced AI and ML models are being harnessed to fortify digital defenses, offering a detailed analysis of API communication patterns and the evolving landscape of bot attacks. Through a series of real-world case studies, we illuminate the mechanisms of sophisticated bot strategies—ranging from data breaches and account takeovers to shopping bots that deplete inventories. The narrative progresses to unveil how AI/ML technologies serve as the cornerstone of innovative defense mechanisms. We dissect the architecture of AI-driven systems tailored to detect and counteract anomalous behaviors indicative of bot activities, leveraging vast datasets to train ML models that adeptly differentiate between legitimate user interactions and malicious bot intrusions. The discussion further navigates through the technical and operational nuances of implementing AI/ML defenses, emphasizing predictive analytics for preemptive action, machine learning for dynamic threat adaptation, and the overarching impact of such technologies in securing digital ecosystems against the insidious threats posed by automated attacks. This presentation not only highlights the challenges but also showcases the resilience and adaptability of AI/ML solutions in the ever-evolving battle against digital villains.

Mahesh Chayel, Meta, Product Management Lead

Product managers face numerous challenges in delivering a seamless customer experience for enterprises, including managing complex product portfolios, personalizing experiences at scale, maintaining consistency across channels, and proactively resolving issues. They struggle with efficient knowledge management, handling high volumes of inquiries, understanding customer sentiment, and reducing churn. To address these challenges, enterprises must streamline onboarding processes, provide multilingual support, and strike a balance between automation and human touch. Continuous improvement is also crucial to meet evolving customer needs.

In this session, I will share how by leveraging AI technologies, PMs can enhance their customer experience, leading to increased satisfaction, loyalty, and business growth.

Oz Katz, Treeverse, CTO & Co-Founder

Langchain has become one of the most popular frameworks for anyone building custom, generative AI-driven apps powered by LLMs, that leverage RAG for the most enhanced results. But like all data products, these applications are really only as good as the org data fed into them.

In this live session you’ll learn how to build a reproducible AI app pipeline with Langchain & lakeFS, including how to build a RAG chatbot, while iteratively tuning it for best results leveraging Delta Lake’s temporal versions, you’ll come away with improved methods for data reproducibility for custom AI apps.

Shireen Nagdive, Salesforce, Senior Software Engineer
Jatin Taneja, Salesforce, Senior Member of Technical Staff

With today’s tools, creating APIs has become a streamlined process—just write the API contract and generate the rest. Yet, despite similar backend functionalities, some APIs stand out and are preferred by users over others. One critical differentiator is API resiliency: the ability to stay functional and dependable when faced with failures or unexpected conditions.
In this session, we’ll dive into proven strategies for designing resilient APIs and examine common issues that arise with different resiliency approaches. By understanding these patterns and their potential pitfalls, developers can ensure their APIs are built not just for functionality but for long-term success in real-world environments.

After attending this session, attendees will walk away knowing -
1. Understanding API resiliency and its importance.
2. Why resiliency is key to API success.
3. Common resiliency strategies and their challenges.

Shay Mandel, Next Insurance, Product Architect

Large features that stretch over 6 or more can quickly become monstrous undertakings, filled with hidden traps that can derail even the most experienced product managers. From dealing with overlapping initiatives and shifting company strategies to navigating the rapid rise of new technologies like AI, these projects are fraught with complexities. Add in the challenges of managing team dynamics, preventing feature creep, and keeping executive buy-in, and the path forward can seem daunting.

In this session, we’ll share case studies that break down the five biggest traps that long-term features can present and provide you with practical strategies to avoid them. Discover how to keep your team focused, safeguard your feature’s scope, and secure ongoing executive support. We’ll also explore how leveraging Scrum can help you manage these complexities, ensuring your project stays on track.

Attend this session to gain actionable insights and tools to turn long-term challenges into opportunities for success, making you a more effective and resilient product manager.

Alison Cossette, Neo4j, Data Science Strategist, Advocate, Educator

As generative AI continues to push boundaries, creating novel content by learning from massive datasets, we are faced with complex issues around intellectual property, privacy, and the ethical use of data. Current systems of copyright, fair use, and data protection lack the scope to fully address the unique challenges posed by AI pattern recognition and generation.

This pivotal talk introduces the pioneering concept of "Pattern Rights" - a holistic ethical framework to inform the development and deployment of generative AI technologies. Pattern Rights serves as an umbrella construct, encompassing principles of copyright, fair use, training data transparency, privacy, data ownership, and accountability.

We will explore how Pattern Rights can ensure appropriate attribution and compensation when AI models learn from copyrighted works or personal data. It establishes guidelines around consent, anonymization, and ethical data sourcing practices.

As the AI industry is rapidly evolving, we urgently need governance to foster innovation while upholding rights and safeguarding against misuse. Pattern Rights provides a roadmap to navigate this uncharted territory responsibly and equitably.

Emerson Taymor, InfoBeans, SVP, Design

Drawing inspiration from the Renaissance, a time of explosive cultural and economic growth, we explore how GenAI is poised to revolutionize product development. I’ll explore its groundbreaking impact on global collaboration, user research, and product development process. I will also highlight potential caveats and pitfalls. This talk promises an action-packed look at GenAI's role in shaping a new era of human-centric and economically impactful product development, ensuring you're equipped to experiment in this modern renaissance. 

Dan Edwards, Crowe, Managing Director

In an era where artificial intelligence (AI) and machine learning are rapidly evolving, the accounting profession stands at the precipice of significant transformation. This session aims to demystify the impact of AI technologies, such as Microsoft Copilot, on the future of accounting.

Join us for an insightful exploration into the capabilities of AI in the accounting space, where we will delve into the current state of AI tools like Microsoft Copilot, their potential to automate complex accounting tasks, and the implications for accounting professionals.

This session is designed for accounting professionals at all levels who are seeking to understand the impact of AI on their careers and how to strategically position themselves for success in a rapidly changing technological landscape. Whether you're a seasoned CPA or a recent graduate, this session will provide valuable insights into the future of accounting.

Michael Mace, UserTesting, VP Market Strategy

The idea of failing fast has become so central to Agile development that it’s almost a religious belief. It’s been the subject of countless articles and even full books. According to Google Trends, the phrase “fail fast” has been on the rise since late 2009.

We’ve become so focused on the “fail fast” mantra that it’s easy to forget that the goal of failing fast isn’t actually to fail; it’s to maximize your speed of learning, so you can evolve a better product quickly. Back when cloud computing first appeared, deploying software was so fast and customer research so slow that it made sense to try things and see what worked rather than waiting months to do a research study.

But today the situation has changed. Through fast feedback products, you can now get customer feedback almost instantly on virtually any idea or experience —within a sprint, without waiting to ship it.

In this session we'll give specifics on how product teams are using fast feedback to make higher-confidence decisions without slowing down the agile process -- reducing rework and increasing customer satisfaction. We'll give real-world examples and practical advice based on UserTesting's own processes, plus examples from other companies.

Utkarsh Contractor, Aisera, VP of AI

Enterprises are on the cusp of a transformative shift. They are moving beyond task-specific AI to embrace agentic systems capable of autonomous decision-making and actions through probabilistic reasoning. This evolution marks a new era of autonomy, where AI not only augments human capabilities but also drives business outcomes by:
- Optimizing Operations: Self-regulating systems enhance efficiency, ensure compliance, and proactively mitigate risks.
- Accelerating Innovation: Data-driven insights fuel strategic decision-making, enabling rapid market adaptation.
- Enhancing Customer Experience: Intelligent agents anticipate customer needs, delivering personalized solutions.

Although the potential benefits are immense, successful implementation demands a strategic approach that encompasses ethical considerations, security, and complexity management.

Join Utkarsh Contractor, VP of AI/ML at Aisera, as we explore the opportunities and challenges of this paradigm shift and how organizations can harness agentic AI to achieve sustained competitive advantage.

Sam Bradley, PayPal, Director of Product Management, Offers & Rewards

A talk on how to approach building and measuring trust in products that product managers lead. The talk will review several examples around a framework of measuring trust. I will also review the impact of AI on trust with customers and how that will continue to evolve as the technology becomes more mainstream

 

Ajit Ghuman, Monetizely, CEO

Pricing strategy can be the difference between growth and stagnation for SaaS companies. Drawing on examples from Twilio, Zoom, and Medallia, Ajit Ghuman will guide participants through the process of building a robust pricing model that aligns with business goals. This session will cover key aspects of pricing such as selecting the right metrics, avoiding common packaging pitfalls, and designing flexible, scalable pricing structures. Whether your company is pre-IPO or scaling post-IPO, this session will provide critical insights into how the best SaaS companies price and package their products.