Vol. 13 AdalFlow: Auto-Optimizing LLM Apps with Li Yin episode artwork

EPISODE · Feb 24, 2025 · 1H 2M

Vol. 13 AdalFlow: Auto-Optimizing LLM Apps with Li Yin

from 双成记

[Hosts]Jucheng (Jack) | Raychen[Guest speaker]Li Yin, the author of AdalFlow and the founder of Sylph AI.AdalFlow is a library to build and auto-optimize any LLM task pipeline. Before AdalFlow, Li was an AI research scientist at Meta AI and a PhD dropout from UT Arlington.AdalFlow is named in honor of Ada Lovelace, the pioneering female mathematician who first recognized that machines could go beyond mere calculations. As a team led by a female founder, AdalFlow aims to inspire more women to pursue careers in AI.[What you’ll hear]01:19 Introduction to AdalFlow and SylphAI: AdalFlow aims to build and optimize LLM task pipelines and is part of SylphAI’s open-source efforts04:42 Deepseek’s impact on Prompt Engineers: Deepseek aids in prompt optimization and enables transparent reasoning06:44 AdalFlow’s collaborative research with UT Austin scholars excels in automated prompt generation, outperforming DsPy and Text Grade08:39 The concept of the AI Digital Engineer product: SylphAI focuses on solving LLM application challenges to boost engineer productivity12:37 Li expresses surprise at their latest paper trending on Hacker News’ front page, noting developers’ growing awareness of eliminating manual prompts15:48 AdalFlow’s underlying mechanism as an automatic differentiation framework: It optimizes by building differentiable graphs and gradient-driven optimizers, using mini-batch training and backpropagation to refine prompts18:14 AdalFlow’s origin in April 2024: The goal was to create a library for automated prompt optimization21:28 Startups must stay focused: Despite AdalFlow trending on Hacker News, the team remains as two-person operation26:17 Progress on finding a co-founder: Collaboration with UT Austin may naturally lead to finding a CTO27:16 Socializing in San Francisco: After moving there, Li joined the Mission Control community and engaged actively in events28:49 LinkedIn’s role in community-building: Attracted attention from senior executives and investors30:19 Lessons from Connor: Learned to read the book Pitch Anything31:18 Beware of “ChatGPT Engineers”: Caution against over-reliance on ChatGPT, especially for remote roles39:24 Simplify code and life: Less code is better; structured code beats spaghetti code40:20 Women still face challenges in STEM and entrepreneurship42:55 Investors want grand visions: Founders must pitch ambitiously—no room for modesty49:20 AdalFlow’s next steps: UT Austin students will use it for research. Future plans include automating dataset creation for components and training cheaper ML models55:39 Advice for young people: Become a community expert, solve real problems, iterate gradually, and stay action-oriented57:45 Release daily updates and iterate rapidly58:39 Advice to past self: Enjoy the journey, specialize deeply, and become an expert1:01:28 Final advice: Just do it! Never quit, work with users, and tackle real-world problems[Mentioned articles, books, people]1/ LLM-AutoDiff: Auto-Differentiate Any LLM Workflow (arxiv)2/ Pitch Anything by Oren Klaff3/ Connor Watumull, VP at Bessemer Venture Partners- - - - - - - - - - - - - - - - - - - - - - - - - - - - -【主播】炬成 | 叡成【嘉宾】Li Yin,AdalFlow作者、SylphAI创始人。AdalFlow 是一个用于构建和自动优化任何 LLM 任务管道的库。在 AdalFlow 之前,Li 是 Meta AI 的人工智能研究科学家,也是得克萨斯大学阿灵顿分校的博士生。AdalFlow 是以 Ada Lovelace 的名字命名的,她是第一位认识到机器可以超越单纯计算的女性数学先驱。作为一个由女性创始人领导的团队,AdalFlow 的目标是激励更多女性从事人工智能职业。【你将听到】01:19 AdalFlow 和 SylphAI 的介绍:AdalFlow 旨在构建和优化 LLM 任务管线,是 SylphAI 开源工作的一部分04:42 Deepseek 对 Prompt 工程师的影响:Deepseek 有助于 Prompt 优化,能够以透明的方式进行推理06:44 AdalFlow 与 UT Austin 学者的合作研究在自动 prompt 生成方面表现出色,优于 DsPy 和 Text Grade08:39 AI Digital Engineer 产品的概念:SylphAI 致力于解决构建 LLM 应用的问题,旨在提高工程师的生产力12:37  Li 对于最新论文登上 Hacker News 首页感到惊喜,开发者开始意识到消除手动 prompt 的重要性15:48 AdalFlow 自动微分框架的底层机制:AdalFlow 的优化包括构建可微图和梯度驱动的优化器,使用 mini-batch 训练和反向传播来优化 prompt18:14 AdalFlow 始于 2024 年 4 月,旨在创建一个能够自动进行 prompt 优化的库21:28 创业公司需要保持专注:即使 AdalFlow 登上了 Hacker News 的首页,团队仍然只有两个人26:17 寻找 co-founder 的进展:与 UT Austin 合作后,可能会自然而然地找到 CTO27:16 在旧金山社交的经历:搬到旧金山后,Li 加入了 Mission Control 社区,并积极参与各种活动28:49 LinkedIn 帮助建立了社区,并吸引了高级管理人员和投资者的关注30:19 从 Connor 身上学到的:从 Connor 那里学到要读《Pitch Anything》这本书31:18 警惕 ChatGPT 工程师:要小心那些过度依赖 ChatGPT 的工程师,特别是远程工作的39:24 简化代码和生活:代码越少越好,结构化的代码胜过大量的 spaghetti 代码40:20 女性在 STEM 领域和创业领域依然面临许多挑战42:55  投资者希望听到创业者将他们的梦想和愿景说得更大,在 pitch 时不能谦虚49:20 AdalFlow 的下一步计划:UT Austin 的学生将使用 AdalFlow 进行研究,未来探索如何自动为每个组件创建数据集,并训练更便宜的机器学习模型55:39 给年轻人的建议:成为社区专家,解决实际问题,逐步迭代产品,并保持行动57:45 每天发布新进展,快速迭代产品58:39 给过去的自己的建议:享受所做的事情,专注于领域,成为专家1:01:28 最后的建议:Just do it! 永不放弃,与用户一起工作,解决实际问题【提到的书、资源、与人】1/ LLM-AutoDiff: Auto-Differentiate Any LLM Workflow (arxiv)2/ Pitch Anything by Oren Klaff3/ Connor Watumull, Bessemer Venture Partners 副总裁【在这里找到我们】公众号:双成记收听渠道:苹果|小宇宙|QQ音乐海外用户:Apple Podcast|Spotify如果你是一名华人创业者/投资人,期待与你交流。欢迎添加微信:jacknottim,备注“双成记 - 嘉宾”。在小宇宙查看该单集文稿

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Vol. 13 AdalFlow: Auto-Optimizing LLM Apps with Li Yin

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