I build recommendation systems and AI-powered experiences that serve customers at scale. Currently, I'm a Principal Applied Scientist at Amazon. Outside of work, I also...
30 Mar 2025 · Frequently Asked Questions about My Writing Process
18 Mar 2025 · NVIDIA GTC 2025 - Building LLM-Powered Applications
16 Mar 2025 · Improving Recommendation Systems & Search in the Age of LLMs
12 Jan 2025 · Building AI Reading Club: Features & Behind the Scenes
08 Dec 2024 · A Spark of the Anti-AI Butlerian Jihad (on Bluesky)
24 Nov 2024 · How to Run a Weekly Paper Club (and Build a Learning Community)
03 Nov 2024 · 39 Lessons on Building ML Systems, Scaling, Execution, and More
18 Aug 2024 · Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge)
26 May 2024 · Prompting Fundamentals and How to Apply them Effectively
12 May 2024 · What We've Learned From A Year of Building with LLMs
30 Jul 2023 · Patterns for Building LLM-based Systems & Products
11 Jun 2023 · Obsidian-Copilot: An Assistant for Writing & Reflecting
21 May 2023 · Some Intuition on Attention and the Transformer
14 Aug 2022 · Simplicity is An Advantage but Sadly Complexity Sells Better
31 Jul 2022 · Uncommon Uses of Python in Commonly Used Libraries
12 Jun 2022 · Design Patterns in Machine Learning Code and Systems
18 Mar 2025 · NVIDIA GTC 2025 - Building LLM-Powered Applications
27 Jun 2024 · AI Engineer 2024 Keynote - What We Learned from a Year of LLMs
31 May 2024 · Netflix PRS 2024 - Applying LLMs to Recommendation Experiences
09 Oct 2023 · AI Engineer 2023 Keynote - Building Blocks for LLM Systems
23 Sep 2022 · RecSys 2022 Keynote - Is the Juice Worth the Squeeze?
12 Jan 2025 · Building AI Reading Club: Features & Behind the Scenes
27 Oct 2024 · AlignEval: Building an App to Make Evals Easy, Fun, and Automated
04 Sep 2022 · Writing Robust Tests for Data & Machine Learning Pipelines
201 posts, 30 talks, 17 prototypes, 401,718 words, and countless hours.
• AI Reading Club: Prototyping an AI-powered reading experience
• AlignEval: An App to Make Evals Easy, Fun, and Semi-Automated
• AI Coach: Talk to Tara, an AI Coach, anytime at +1 (206) 558 8782
• Obsidian-Copilot: A Prototype Assistant for Writing and Reflecting
• Raspberry-LLM: Dr. Seuss headlines, HackerNews trolls, etc.
• ApplyingML.com: Ghost knowledge of applying ML effectively
• RecSys in PyTorch: Baselines + improvements via Graphs & NLP
• Image Classification: Transfer learning via Keras and Theano
• Title Classification: Getting Amazon data, modeling, building a UI
applied-llms.org:
Practical lessons from a year of building with LLMs
applyingml.com:
Papers, guides, and interviews on how to apply ML effectively
applied-ml:
Papers on real-world machine learning systems in industry
open-llms:
Open large language models available for commercial use
llm-reading-list:
Language modeling reading list (to start a paper club)
ml-design-docs:
Template of design docs for machine learning systems
python-collab-template:
Template with tests, type checks, linting, etc.
papermill-mlflow:
Experimentation workflow for machine learning
1-on-1s:
Questions to ask during 1-on-1s, from my time as a manager
omscs-faq:
Georgia Tech Online Master's of Science in Computer Science
teardowns:
Surveys & deep dives of data/machine learning systems