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
Go deeper with a course

Thu, Feb 5, 2026
5:30 PM UTC (1 hour)
Virtual (Zoom)
Free to join
Go deeper with a course

What you'll learn
Put real cost and usage boundaries around LLM experiments
Trade-offs between different ways of accessing Gemini
What works and what doesn’t running LLM tooling locally
Why this topic matters
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
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