Sid Bendre
Co-Founder of Oleve
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Sid Bendre is the co-founder of Oleve, a company building a portfolio of iconic consumer software across multiple verticals. With a lean team, Oleve has already launched two virally successful consumer AI products that have amassed over 250 million views across social media platforms. One of their products reached #4 on the App Store's Education charts in 2024 and #5 in 2025, competing alongside giants like Photomath (Google) and Duolingo. Backed by Neo, Cal Henderson (co-founder of Slack), Russell Kaplan (President of Cognition), and Maria Zhang (ex-CTO of Tinder), Oleve is building the AI infrastructure to run a $1B portfolio of consumer software over the next decade. At Oleve, Sid leads technical and AI efforts, running the “Platform” team responsible for the underlying AI infrastructure that powers their lean scaling approach. Before Oleve, Sid led AI experimentation efforts at a startup hedge fund and worked at Slack, Zendesk, and Microsoft.
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Building AI Products That Actually Work
You've made the demo. How do you make the product? A lot of AI products don't actually work. Even worse, a lot of the techniques being advertised for making AI products better don't work either. We'll cover the challenges + techniques we've seen actually work in the real world.
The New Lean Startup
In this session, I will be presenting a case study of Oleve's journey, revealing how we've scaled a profitable multi-product portfolio with a tiny team. I'll walk you through the emergence of "tiny teams," our two-track engineering methodology that has become our blueprint, as well as an inside look at our technical alpha – specifically how we've engineered deterministic AI agents to deliver magical and reliable consumer experiences to millions. You'll learn how we've built internal tools to grow leanly and created operating playbooks to scale operations without traditional headcount requirements. I'll also share our approach to scrappy infrastructure innovation and how our investment in internal tooling has served as a critical force multiplier. Finally, I'll give an overview of parts of the profitable portfolio playbook that keeps us lean, adaptable, and profitable across multiple product lines.
Structure of talk:
- the tiny teams revolution
- the two-track engineering approach
- technical alpha: deterministic ai agents at scale
- scrappy infrastructure innovation
- internal tooling as a multiplier
- the profitable portfolio playbook
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