In this episode of Building With AI, host Haroon Choudery is joined by Jason Liu, a seasoned AI operator and consultant who advises seed-stage start-ups on tech strategy, research, and infrastructure.

With several years of experience in machine learning, Jason has gained recognition for creating AI-specific dev tooling and contributing to several open-source projects.

During the conversation, they discuss:

General applications vs. AI applications,
How developers should work with LLMs,
What LLMOps companies need to focus on,
Why saying 'no' can improve your AI's success rate,
Building agile AI systems,
Best practices for RAG systems,
And much more!

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[00:00] Up next: Jason Liu

[00:25] Episode Introduction

[01:12] Autoblocks: AI Optimization Platform

[02:07] Jason's introduction

[03:44] General applications vs. AI applications

[05:08] The two categories of dev tools

[06:43] The AI landscape for non-technical users

[08:47] The one skill developers need

[09:57] The eval puzzle

[11:52] What LLMOps companies need to focus on

[16:26] Why saying 'no' can improve your AI's success rate

[18:15] How can you build an agile AI system?

[21:41] Strategies for building products that stick

[24:29] Similarities between RAG and recommendation frameworks

[26:03] Best practices for RAG systems

[28:27] The importance of short-term metrics

[29:30] Data strategies for effective RAG systems

[35:22] Jason's hottest take on AI

[36:22] Jason's future projects

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Brought to you by Autoblocks (https://www.autoblocks.ai) — how product teams deliver better AI experiences.

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Subscribe to Building With AI:

Website: https://www.bwai.autoblocks.ai
X: https://x.com/bwaipodcast

Where to find Jason Liu:

Linkedln: https://www.linkedin.com/in/jxnlco/
X: https://twitter.com/jxnlco

Where to find Haroon Choudery:

Linkedln: https://www.linkedin.com/in/haroonchoudery/
X: https://x.com/haroonchoudery

Learn more about Autoblocks:

Ep. 604: "Unintentional Curator"

Roderick on the Line

Preference for Heavier, Durable Garments

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