Avoiding expensive AI surprises with LiteLLM

Hosted by Ewan Nisbet and Doug Turnbull

Thu, Feb 5, 2026

5:30 PM UTC (1 hour)

Virtual (Zoom)

Free to join

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Go deeper with a course

Cheat at Search with Agents
Doug Turnbull
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What you'll learn

Put real cost and usage boundaries around LLM experiments

use local proxies like LiteLLM instead of relying on opaque hyperscaler abstractions to manage LLM use

Trade-offs between different ways of accessing Gemini

CLI tools vs APIs vs wrappers - when each approach actually makes sense

What works and what doesn’t running LLM tooling locally

Including lessons from Nix, Apple Containers, and lightweight setups without Docker

Why this topic matters

LLMs have lowered the barrier to experimentation, but raised the risk of silent, unbounded cost. For individual engineers and small teams, the gap between “enterprise best practices” and day-to-day reality is huge. This talk focuses on reclaiming control: making costs visible, experimentation safe, and tooling choices explicit, so you can move fast without unpleasant surprises on your credit card

You'll learn from

Ewan Nisbet

Technologist

I redistribute the future, helping people:

1) Decide where they want to go.

2) Get there.


For the most part I've achieved these outcomes by guiding interactions with technology. Frequently this has been intertwined with the adaption of one or more business processes. I've done this through a mixture of mentoring and bringing people together, insight, and good old fashioned hard work. Sometimes I've supported, other times I've led. When appropriate, I've simply gotten out of the way

Doug Turnbull

Search Practitioner

Doug Turnbull is an expert in search technology and relevance engineering, currently serving as Principal Engineer at Daydream, where he builds hybrid search systems combining lexical and vector retrieval, and develops LLM-driven quality programs for e-commerce search. Previously, he led machine-learning-driven search initiatives at Reddit, significantly improving search relevance through Learning to Rank methods. Doug also advanced e-commerce search at Shopify and served as CTO at OpenSource Connections. He co-authored the influential book Relevant Search (Manning, 2016) and created popular open-source tools, including Quepid and the Elasticsearch Learning to Rank plugin. He regularly speaks at industry conferences, making search relevance accessible to engineers.



Coach Search Teams at

Reddit
Shopify.com
Wayfair
OpenAI
Apple

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