"Subscribed for quick summaries of topics. Saves time. Googling and Youtube and collating info isn't convenient."
— RB
Making practical sense of software and AI.
What’s an inference provider?
How the rise of open source AI models is fueling the growth of a new infrastructure category.
I Let Claude Code Autonomously Run Ads for a Month
Applying the Ralph Wiggum loop to things other than writing code.
How AI content detectors work
Learn how AI detectors work
Prompt Engineering
Prompt engineering is the art of talking to AI models in a way that gets you the results you actually want.
Token
A token is the basic unit of a Large Language Model's vocabulary.
Post-training
LLM post-training turns a model from a knowledgeable blob that produces rambling answers, into a helpful assistant.
Loss Function
When training a machine learning model, a loss function is something you design that tells the model when its answers are right and when they're wrong.
Databricks is apparently worth $100B. What do they even do?
What we should really be asking is “What does Databricks not do?”
What does Alteryx do?
Alteryx is a group of tools that helps business teams get insights out of their data, without needing to write any code.
What's a Data Migration?
Data migration is about transferring information (data) from one place to another.
Analytics
Analytics just means trying to use data to learn something.
Product analytics
Product analytics is the process of companies figuring out what users are actually doing in their product, with the goal of improving it.
Snowflake
Snowflake sells a powerful cloud data warehouse for analytics and data science teams.
OpenAI
OpenAI is the most popular provider of generative AI models like GPT-4.
Database
A database is just a place to store data; even Excel is technically a database.
Query
A query is how talk to your database.
MongoDB
MongoDB is a highly popular unstructured, NoSQL document database for powering your applications.
Elastic
Elasticsearch is a popular open source database for storing and searching unstructured data.
A Beginner’s Guide to Bring Your Own Cloud
The profitable but challenging deployment model sweeping the nation.
What's documentation?
How companies like Stripe win by writing better product docs, and where platforms like GitBook can help.
Developers hate this one thing (all about code reviews)
A deep dive into why code reviews take so long, how AI tools like CodeRabbit are speeding them up, and what great teams do to ensure clean code.
Kubernetes
Developers use Kubernetes to turn their individual containers and virtual machines into full fledged, working applications.
Port
Computers have digital ports – literally, like for a boat – for other computers to connect to over a network.
Vercel
Vercel builds the AI cloud – they make it easy for engineers to deploy and run the user facing (frontend) + AI parts of their applications.
Twilio
Twilio makes a suite of products that helps you communicate with your customers via SMS, video, calls, and more.
VPN
A Virtual Private Network (VPN) lets you route your internet access through a specialized server that keeps your sensitive information private.
Tokenization
Tokenization is one of the ways that backends protect sensitive information, like credit cards or social security numbers.
Okta
Okta is an enterprise-focused identity provider: they take care of managing usernames, passwords, and permissions.
Snyk
Snyk helps developers make sure that the code they're writing is secure.
"Technically has allowed me better bridge the gap between user problems and how our system works under the hood."
— Adelaide Hallowell
How the rise of open source AI models is fueling the growth of a new infrastructure category.
Will RaphaelsonApplying the Ralph Wiggum loop to things other than writing code.
The profitable but challenging deployment model sweeping the nation.
Will RaphaelsonLearn how AI detectors work
Christy Bieber
And why is every startup around following the Palantir model?
Sung Won Chung
What actually goes on inside the buildings propping up the US economy.
Will Raphaelson
Finally, an explanation for why AI models can't seem to quit them.
Christy BieberWhat their products actually do and why they're so valuable.
Quick explanations of the concepts you see every day.

Kalshi just raised a new round at an $11B valuation. How much revenue does their prediction market really make?
Sam Schneider
What's the forward deployed engineer role, and why is every startup hiring them?
Sung Won ChungCurated collections of foundational articles to guide you through the basics of getting more technical at work.
How to understand and work effectively with AI and ML models and products.
Breaking down what ChatGPT and others are doing under the hood
How AI models learned to stop being weird and start being helpful.
GPT-3 is a Machine Learning model that generates text.
Data Science Notebooks help data teams explore data with code.
The products and business models of leading software companies.
What we should really be asking is “What does Databricks not do?”
Snowflake sells a powerful cloud data warehouse for analytics and data science teams.
OpenAI is the most popular provider of generative AI models like GPT-4.
dbt (no capitals) is a tool for transforming and organizing data in your warehouse.
How to make positive contributions to your product roadmap.
Engineering and code basics that can make you a better PM to work with.
Code is step by step directions, but for computers.
A network of computers all connected to each other and sharing information.
Cloud is how companies rent infrastructure over the internet.
You've outgrown Excel, but you've got to put that data somewhere besides your parents basement.
There are 300+ databases; what do they all do?
If you’re not a data scientist but you have questions, you want to know SQL.
Why that schema change is going to take your engineers two weeks.
Why your feature is held up by a migration and why this is actually good.
How do these things actual work under the hood? What does it mean to train one? Is it more like going to the gym, studying for a test, or sleeping?
How computers learn patterns from data: the foundation for everything from stock price prediction to ChatGPT.
Breaking down what ChatGPT and others are doing under the hood
A deep dive into how models like ChatGPT get built.
Unlike an onion, hopefully these neural network layers won't make you cry.
How to make positive contributions when working with analytics and data science teams.
Product analytics is how teams instrument and analyze data about their product usage.
A deep dive into all of the tools that data teams use to do their work.
If you’re not a data scientist but you have questions, you want to know SQL.
The new set of tools data teams use to get their jobs done.