How AI Is Built
Episodes
#056 Building Solo: How One Engineer Uses AI Agents to Ship Production Code
11 Sep 2025
Contributed by Lukas
Nicolay here,Most AI coding conversations focus on which model to use. This one focuses on workflow - the specific commands, git strategies, and revie...
#055 Embedding Intelligence: AI's Move to the Edge
13 Aug 2025
Contributed by Lukas
Nicolay here,while everyone races to cloud-scale LLMs, Pete Warden is solving AI problems by going completely offline. No network connectivity require...
#054 Building Frankenstein Models with Model Merging and the Future of AI
29 Jul 2025
Contributed by Lukas
Nicolay here,most AI conversations focus on training bigger models with more compute. This one explores the counterintuitive world where averaging wei...
#053 AI in the Terminal: Enhancing Coding with Warp
23 Jul 2025
Contributed by Lukas
Nicolay here,Most AI coding tools obsess over automating everything. This conversation focuses on the rightbalance between human skill and AI assistan...
#052 Don't Build Models, Build Systems That Build Models
01 Jul 2025
Contributed by Lukas
Nicolay here,Today I have the chance to talk to Charles from Modal, who went from doing a PhD on neural network optimization in the 2010s - when ML en...
#051 Build systems that can be debugged at 4am by tired humans with no context
17 Jun 2025
Contributed by Lukas
Nicolay here,Today I have the chance to talk to Charity Majors, CEO and co-founder of Honeycomb, who recently has been writing about the cost crisis i...
#050 Bringing LLMs to Production: Delete Frameworks, Avoid Finetuning, Ship Faster
27 May 2025
Contributed by Lukas
Nicolay here,Most AI developers are drowning in frameworks and hype. This conversation is about cutting through the noise and actually getting somethi...
#050 TAKEAWAYS Bringing LLMs to Production: Delete Frameworks, Avoid Finetuning, Ship Faster
27 May 2025
Contributed by Lukas
Nicolay here,Most AI developers are drowning in frameworks and hype. This conversation is about cutting through the noise and actually getting somethi...
#049 BAML: The Programming Language That Turns LLMs into Predictable Functions
20 May 2025
Contributed by Lukas
Nicolay here,I think by now we are done with marveling at the latest benchmark scores of the models. It doesn’t tell us much anymore that the latest...
#049 TAKEAWAYS BAML: The Programming Language That Turns LLMs into Predictable Functions
20 May 2025
Contributed by Lukas
Nicolay here,I think by now we are done with marveling at the latest benchmark scores of the models. It doesn’t tell us much anymore that the latest...
#048 TAKEAWAYS Why Your AI Agents Need Permission to Act, Not Just Read
13 May 2025
Contributed by Lukas
Nicolay here,most AI conversations obsess over capabilities. This one focuses on constraints - the right ones that make AI actually useful rather than...
#048 Why Your AI Agents Need Permission to Act, Not Just Read
11 May 2025
Contributed by Lukas
Nicolay here,most AI conversations obsess over capabilities. This one focuses on constraints - the right ones that make AI actually useful rather than...
#047 Architecting Information for Search, Humans, and Artificial Intelligence
27 Mar 2025
Contributed by Lukas
Today on How AI Is Built, Nicolay Gerold sits down with Jorge Arango, an expert in information architecture. Jorge emphasizes that aligning systems wi...
#046 Building a Search Database From First Principles
13 Mar 2025
Contributed by Lukas
Modern search is broken. There are too many pieces that are glued together.Vector databases for semantic searchText engines for keywordsRerankers to f...
#045 RAG As Two Things - Prompt Engineering and Search
06 Mar 2025
Contributed by Lukas
John Berryman moved from aerospace engineering to search, then to ML and LLMs. His path: Eventbrite search → GitHub code search → data science →...
#044 Graphs Aren't Just For Specialists Anymore
28 Feb 2025
Contributed by Lukas
Kuzu is an embedded graph database that implements Cypher as a library.It can be easily integrated into various environments—from scripts and Androi...
#043 Knowledge Graphs Won't Fix Bad Data
20 Feb 2025
Contributed by Lukas
Metadata is the foundation of any enterprise knowledge graph.By organizing both technical and business metadata, organizations create a “brain” th...
#042 Temporal RAG, Embracing Time for Smarter, Reliable Knowledge Graphs
13 Feb 2025
Contributed by Lukas
Daniel Davis is an expert on knowledge graphs. He has a background in risk assessment and complex systems—from aerospace to cybersecurity. Now he is...
#041 Context Engineering, How Knowledge Graphs Help LLMs Reason
06 Feb 2025
Contributed by Lukas
Robert Caulk runs Emergent Methods, a research lab building news knowledge graphs. With a Ph.D. in computational mechanics, he spent 12 years creating...
#040 Vector Database Quantization, Product, Binary, and Scalar
31 Jan 2025
Contributed by Lukas
When you store vectors, each number takes up 32 bits.With 1000 numbers per vector and millions of vectors, costs explode.A simple chatbot can cost tho...
#039 Local-First Search, How to Push Search To End-Devices
23 Jan 2025
Contributed by Lukas
Alex Garcia is a developer focused on making vector search accessible and practical. As he puts it: "I'm a SQLite guy. I use SQLite for a lot of proje...
#038 AI-Powered Search, Context Is King, But Your RAG System Ignores Two-Thirds of It
09 Jan 2025
Contributed by Lukas
Today, I (Nicolay Gerold) sit down with Trey Grainger, author of the book AI-Powered Search. We discuss the different techniques for search and recomm...
#037 Chunking for RAG: Stop Breaking Your Documents Into Meaningless Pieces
03 Jan 2025
Contributed by Lukas
Today we are back continuing our series on search. We are talking to Brandon Smith, about his work for Chroma. He led one of the largest studies in th...
#036 How AI Can Start Teaching Itself - Synthetic Data Deep Dive
19 Dec 2024
Contributed by Lukas
Most LLMs you use today already use synthetic data.It’s not a thing of the future.The large labs use a large model (e.g. gpt-4o) to generate trainin...
#035 A Search System That Learns As You Use It (Agentic RAG)
13 Dec 2024
Contributed by Lukas
Modern RAG systems build on flexibility.At their core, they match each query with the best tool for the job.They know which tool fits each task. When ...
#034 Rethinking Search Inside Postgres, From Lexemes to BM25
05 Dec 2024
Contributed by Lukas
Many companies use Elastic or OpenSearch and use 10% of the capacity.They have to build ETL pipelines.Get data Normalized.Worry about race conditions....
#033 RAG's Biggest Problems & How to Fix It (ft. Synthetic Data)
28 Nov 2024
Contributed by Lukas
RAG isn't a magic fix for search problems. While it works well at first, most teams find it's not good enough for production out of the box. The key i...
#032 Improving Documentation Quality for RAG Systems
21 Nov 2024
Contributed by Lukas
Documentation quality is the silent killer of RAG systems. A single ambiguous sentence might corrupt an entire set of responses. But the hardest part ...
#031 BM25 As The Workhorse Of Search; Vectors Are Its Visionary Cousin
15 Nov 2024
Contributed by Lukas
Ever wondered why vector search isn't always the best path for information retrieval?Join us as we dive deep into BM25 and its unmatched efficiency in...
#030 Vector Search at Scale, Why One Size Doesn't Fit All
07 Nov 2024
Contributed by Lukas
Ever wondered why your vector search becomes painfully slow after scaling past a million vectors? You're not alone - even tech giants struggle with th...
#029 Search Systems at Scale, Avoiding Local Maxima and Other Engineering Lessons
31 Oct 2024
Contributed by Lukas
Modern search systems face a complex balancing act between performance, relevancy, and cost, requiring careful architectural decisions at each layer.W...
#028 Training Multi-Modal AI, Inside the Jina CLIP Embedding Model
25 Oct 2024
Contributed by Lukas
Today we are talking to Michael Günther, a senior machine learning scientist at Jina about his work on JINA Clip.Some key points:Uni-modal embeddings...
#027 Building the database for AI, Multi-modal AI, Multi-modal Storage
23 Oct 2024
Contributed by Lukas
Imagine a world where data bottlenecks, slow data loaders, or memory issues on the VM don't hold back machine learning.Machine learning and AI success...
#026 Embedding Numbers, Categories, Locations, Images, Text, and The World
10 Oct 2024
Contributed by Lukas
Today’s guest is Mór Kapronczay. Mór is the Head of ML at superlinked. Superlinked is a compute framework for your information retrieval and featu...
#025 Data Models to Remove Ambiguity from AI and Search
04 Oct 2024
Contributed by Lukas
Today we have Jessica Talisman with us, who is working as an Information Architect at Adobe. She is (in my opinion) the expert on taxonomies and ontol...
#024 How ColPali is Changing Information Retrieval
27 Sep 2024
Contributed by Lukas
ColPali makes us rethink how we approach document processing.ColPali revolutionizes visual document search by combining late interaction scoring with ...
#023 The Power of Rerankers in Modern Search
26 Sep 2024
Contributed by Lukas
Today, we're talking to Aamir Shakir, the founder and baker at mixedbread.ai, where he's building some of the best embedding and re-ranking models out...
#022 The Limits of Embeddings, Out-of-Domain Data, Long Context, Finetuning (and How We're Fixing It)
19 Sep 2024
Contributed by Lukas
Text embeddings have limitations when it comes to handling long documents and out-of-domain data.Today, we are talking to Nils Reimers. He is one of t...
#021 The Problems You Will Encounter With RAG At Scale And How To Prevent (or fix) Them
12 Sep 2024
Contributed by Lukas
Hey! Welcome back.Today we look at how we can get our RAG system ready for scale.We discuss common problems and their solutions, when you introduce mo...
#020 The Evolution of Search, Finding Search Signals, GenAI Augmented Retrieval
05 Sep 2024
Contributed by Lukas
In this episode of How AI is Built, Nicolay Gerold interviews Doug Turnbull, a search engineer at Reddit and author on “Relevant Search”. They dis...
#019 Data-driven Search Optimization, Analysing Relevance
30 Aug 2024
Contributed by Lukas
In this episode, we talk data-driven search optimizations with Charlie Hull.Charlie is a search expert from Open Source Connections. He has built Flax...
#018 Query Understanding: Doing The Work Before The Query Hits The Database
15 Aug 2024
Contributed by Lukas
Welcome back to How AI Is Built. We have got a very special episode to kick off season two. Daniel Tunkelang is a search consultant currently workin...
Season 2 Trailer: Mastering Search
08 Aug 2024
Contributed by Lukas
Today we are launching the season 2 of How AI Is Built.The last few weeks, we spoke to a lot of regular listeners and past guests and collected feedba...
#017 Unlocking Value from Unstructured Data, Real-World Applications of Generative AI
16 Jul 2024
Contributed by Lukas
In this episode of "How AI is Built," host Nicolay Gerold interviews Jonathan Yarkoni, founder of Reach Latent. Jonathan shares his expertise in extra...
#016 Data Processing for AI, Integrating AI into Data Pipelines, Spark
12 Jul 2024
Contributed by Lukas
This episode of "How AI Is Built" is all about data processing for AI. Abhishek Choudhary and Nicolay discuss Spark and alternatives to process data s...
#015 Building AI Agents for the Enterprise, Agent Cost Controls, Seamless UX
04 Jul 2024
Contributed by Lukas
In this episode, Nicolay talks with Rahul Parundekar, founder of AI Hero, about the current state and future of AI agents. Drawing from over a decade ...
#014 Building Predictable Agents through Prompting, Compression, and Memory Strategies
27 Jun 2024
Contributed by Lukas
In this conversation, Nicolay and Richmond Alake discuss various topics related to building AI agents and using MongoDB in the AI space. They cover th...
Data Integration and Ingestion for AI & LLMs, Architecting Data Flows | changelog 3
25 Jun 2024
Contributed by Lukas
In this episode, Kirk Marple, CEO and founder of Graphlit, shares his expertise on building efficient data integrations. Kirk breaks down his approach...
#013 ETL for LLMs, Integrating and Normalizing Unstructured Data
19 Jun 2024
Contributed by Lukas
In our latest episode, we sit down with Derek Tu, Founder and CEO of Carbon, a cutting-edge ETL tool designed specifically for large language models (...
#012 Serverless Data Orchestration, AI in the Data Stack, AI Pipelines
14 Jun 2024
Contributed by Lukas
In this episode, Nicolay sits down with Hugo Lu, founder and CEO of Orchestra, a modern data orchestration platform. As data pipelines and analytics w...
#011 Mastering Vector Databases, Product & Binary Quantization, Multi-Vector Search
07 Jun 2024
Contributed by Lukas
Ever wondered how AI systems handle images and videos, or how they make lightning-fast recommendations? Tune in as Nicolay chats with Zain Hassan, an ...
#010 Building Robust AI and Data Systems, Data Architecture, Data Quality, Data Storage
31 May 2024
Contributed by Lukas
In this episode of "How AI is Built", data architect Anjan Banerjee provides an in-depth look at the world of data architecture and building complex A...
#009 Modern Data Infrastructure for Analytics and AI, Lakehouses, Open Source Data Stack
24 May 2024
Contributed by Lukas
Jorrit Sandbrink, a data engineer specializing on open table formats, discusses the advantages of decoupling storage and compute, the importance of ch...
#008 Knowledge Graphs for Better RAG, Virtual Entities, Hybrid Data Models
20 May 2024
Contributed by Lukas
Kirk Marple, CEO and founder of Graphlit, discusses the evolution of his company from a data cataloging tool to an platform designed for ETL (Extract,...
#007 Navigating the Modern Data Stack, Choosing the Right OSS Tools, From Problem to Requirements to Architecture
17 May 2024
Contributed by Lukas
From Problem to Requirements to Architecture.In this episode, Nicolay Gerold and Jon Erich Kemi Warghed discuss the landscape of data engineering, sha...
#006 Data Orchestration Tools, Choosing the right one for your needs
10 May 2024
Contributed by Lukas
In this episode, Nicolay Gerold interviews John Wessel, the founder of Agreeable Data, about data orchestration. They discuss the evolution of data or...
#005 Building Reliable LLM Applications, Production-Ready RAG, Data-Driven Evals
03 May 2024
Contributed by Lukas
In this episode of "How AI is Built", we learn how to build and evaluate real-world language model applications with Shahul and Jithin, creators of Ra...
Lance v2: Rethinking Columnar Storage for Faster Lookups, Nulls, and Flexible Encodings | changelog 2
29 Apr 2024
Contributed by Lukas
In this episode of Changelog, Weston Pace dives into the latest updates to LanceDB, an open-source vector database and file format. Lance's new V2 fil...
#004 AI with Supabase, Postgres Configuration, Real-Time Processing, and more
26 Apr 2024
Contributed by Lukas
Had a fantastic conversation with Christopher Williams, Solutions Architect at Supabase, about setting up Postgres the right way for AI. We dug deep i...
#003 AI Inside Your Database, Real-Time AI, Declarative ML/AI
19 Apr 2024
Contributed by Lukas
If you've ever wanted a simpler way to integrate AI directly into your database, SuperDuperDB might be the answer. SuperDuperDB lets you easily apply ...
Supabase acquires OrioleDB, A New Database Engine for PostgreSQL | changelog 1
17 Apr 2024
Contributed by Lukas
Supabase just acquired OrioleDB, a storage engine for PostgreSQL. Oriole gets creative with MVCC! It uses an UNDO log rather than keeping multiple ve...
#002 AI Powered Data Transformation, Combining gen & trad AI, Semantic Validation
12 Apr 2024
Contributed by Lukas
Today’s guest is Antonio Bustamante, a serial entrepreneur who previously built Kite and Silo and is now working to fix bad data. He is building bem...
#001 Multimodal AI, Storing 1 Billion Vectors, Building Data Infrastructure at LanceDB
05 Apr 2024
Contributed by Lukas
Imagine a world where data bottlenecks, slow data loaders, or memory issues on the VM don't hold back machine learning.Machine learning and AI success...