Simulation-Maxxing: How Nubank ships agents 20× faster with simulations
Official Schedule Context
- Date/time: 2026-07-01 · 2:50pm-3:10pm
- Track/room: AI in Finance · Track 3
- Speaker(s): Shreya Rajpal, Aman Gupta
- Session type/status: session · confirmed
Official Description
You know how to build an agent - write a prompt, spec out some tools and call an LLM (or gateway).
At this point, you probably also know how to build an agent that “actually works” using some
combination of agent frameworks, eval tools and looking at your data. This talk is about building an
agent much, much faster using simulations to hill-climb your agent configuration instead of grinding
on real data. We’ll dive deep into a case study of how a top-5 fintech made their agent dev cycle
20x faster using simulation-driven optimization. We’ll cover: - When to use real data vs.
simulations in agent building - How to design simulation environments tailored to your agent - How
to automate the optimization loop so you’re hill climbing agent configurations without manual tuning
Related YouTube Video
Trust, but Verify: Shreya Rajpal (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).
Transcript Status
Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.
People
Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.
Supporting Slides
- youtube 9 vGxMoUM9Y slides — extracted from the related public AI Engineer video.
Slide Evidence
- Slide-only cropped deck: youtube 9 vGxMoUM9Y dense slides (13 viable slide images).
- Related slide/OCR pages:
- youtube 9 vGxMoUM9Y dense slides
- youtube 9 vGxMoUM9Y reconstructed slides
- youtube 9 vGxMoUM9Y slides
- Slide-derived terms:
guardrails,source,change,llms,library,validators,self,deep,querdraie,current,cofounder,past,infra,lead,mlops,driving,cars,classical