{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Fundamentals of Software Engineering","title":"E10 - Context Engineering Is Just Data Fundamentals in Disguise","html":"","width":"100%","height":180,"duration":3431,"description":"In this episode of Fundamentals of Software Engineering, Nate and I dig into context engineering, the phrase that has quietly replaced prompt engineering as the term on everyone's 2026 bingo card. Our core argument is simple. Context engineering is not a shiny new AI skill, it is a data fundamental you probably already know, just wearing a new name. Prompt engineering is about how you ask. Context engineering is about what the model actually knows when you ask. We frame it as a desk and a filing cabinet, where the context window is the desk and your job is deciding what belongs on it right now. Along the way we get into structured versus unstructured data, retrieval augmented generation, tools, and why getting the right information in front of a model matters far more than crafting the perfect prompt.We also pump the brakes on the idea that coding is solved and engineers are optional. We talk through the headlines, Spotify shipping thousands of deploys a day with most pull requests now AI assisted, and Ford rehiring hundreds of veteran engineers after AI could not replace decades of hard earned wisdom. That leads us to data hygiene, access control, and lineage, because AI does not fix garbage data, it exposes it. We cover keeping context fresh, why a confidently wrong AI is worse than no AI, and why curation beats volume when tokens are the currency of large language models. We close on data migration, version control for your schema with tools like Flyway and Liquibase, data validation, and the case for smaller local models fed the right context. Data is the backbone of everything we build, even in the age of AI.__________________________________________________Key Highlights🚀 Deploy Versus Release: Spotify reportedly ships around 4,500 production deploys a day with 73 percent of pull requests AI assisted, which opens a great conversation about why a deploy is not the same thing as a release.🛑 Pump the Brakes on Coding Is Solved: Ford rehired more than 300...","thumbnail_url":"https://img.transistorcdn.com/1BiOcr3jOEw_uiwQk5MInsKiSAl8JXHgE7p7L1stz0g/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82NmM2/MmE3OWEzYWVkMWFl/MWUxNzhkOWY1YzY1/Njg2Ny5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}