Technically
AI Reference
Your dictionary for AI terms like LLM and RLHF
Company Breakdowns
What technical products actually do and why the companies that make them are valuable
Learning Tracks
In-depth, networked guides to learning specific concepts
Posts Archive
All Technically posts on software concepts since the dawn of time
Terms Universe
The dictionary of software terms you've always wanted

Explore learning tracks

AI, it's not that ComplicatedAnalyzing Software CompaniesBuilding Software ProductsWorking with Data Teams
Loading...
PodcastI'm feeling luckyPricing
Log In

"Subscribed for quick summaries of topics. Saves time. Googling and Youtube and collating info isn't convenient."

— RB

Technically

Making practical sense of software and AI.

AI
Recent Articles

What's a decision model?

And why do we need models like Jev?

What is Google doing with AI?

Inside Google's full-stack cloud bet, and how it differs from Microsoft and AWS.

How to use open-weight AI models

Picking a model, a harness, and where to run the thing.

AI Reference

Fine Tuning

Fine tuning is the process of taking a pre-trained AI model and specializing it for your specific use case.

Neural Network

Neural networks are the mathematical brains behind modern AI—think of them as simplified versions of how your actual brain processes information.

Terms

LLM

Large Language Models take in a prompt and generate text.

Machine Learning

Machine Learning uses math to predict an output given an input

All AI →
Analytics
Recent Articles

Databricks is apparently worth $100B. What do they even do?

What we should really be asking is “What does Databricks not do?”

Terms

Analytics

Analytics just means trying to use data to learn something.

Linear Regression

Linear Regression is an old school statistical method for predicting outcomes from a series of numbers.

Companies
Databricks

Databricks

Databricks sells a data science and analytics platform built on top of an open source package called Apache Spark.

Segment

Segment

Segment helps teams track their product and marketing data and send it to whichever tools it needs to go to.

All Analytics →
Databases
Recent Articles

What's DuckDB?

Meet the world's friendliest database (allegedly).

Software Eng for Vibe Coders: Databases + Storage

Where your vibe coded app actually keeps its data, and how it might break when real users show up.

What does Turbopuffer do?

And what's going on in the category formerly known as vector databases?

Terms

Database

A database is just a place to store data; even Excel is technically a database.

ORM

An Object Relational Mapper is software that lets developers interact with their database in their programming language of choice – instead of SQL.

Companies
Confluent

Confluent

Apache Kafka is a framework for streaming real time data, and Confluent offers Kafka as a managed service.

MongoDB

MongoDB

MongoDB is a highly popular unstructured, NoSQL document database for powering your applications.

All Databases →
DevOps
Recent Articles

The Vibe Coder's Guide to Cloud + Scaling

How to survive your app going viral.

The Vibe Coder's Guide to Deployment

How your app gets off your laptop and onto the real internet, and what to do when a deploy breaks.

Software Eng for Vibe Coders: On Frontends + Backends

A new series to help non-engineers build products that can handle going viral.

Terms

Version control

Version control lets you track and manage changes to your code in a more sophisticated way than you’re used to.

Networking

Networking in software engineering refers to connecting two or more different things.

Companies
New Relic

New Relic

New Relic is observability software: teams use it to monitor the performance of their apps and infrastructure.

Zapier

Zapier

Zapier helps business people make custom integrations between their favorite tools, without needing to write any code.

All DevOps →
Security
Recent Articles

Software Eng for Vibe Coders: Auth + Security

How to make sure anyone on the internet can't just delete your app's data, and other security considerations.

Terms

Tokenization

Tokenization is one of the ways that backends protect sensitive information, like credit cards or social security numbers.

VPN

A Virtual Private Network (VPN) lets you route your internet access through a specialized server that keeps your sensitive information private.

Companies
WorkOS

WorkOS

WorkOS gives developers the building blocks for enterprise login, like single sign-on and user provisioning, so they don't have to build them from scratch.

Okta

Okta

Okta is an enterprise-focused identity provider: they take care of managing usernames, passwords, and permissions.

All Security →

"Technically has allowed me better bridge the gap between user problems and how our system works under the hood."

— Adelaide Hallowell

Latest

The Vibe Coder's Guide to Observability

The Vibe Coder's Guide to Observability

How to find out your app broke before your users do.

Will RaphaelsonWill Raphaelson

Recent

What's a decision model?Free

And why do we need models like Jev?

Sam SchneiderSam Schneider

What does LangChain do?

What started as a humble LLM framework has become an everything store for agents.

David KrevittDavid Krevitt

The Vibe Coder's Guide to Cloud + ScalingFree

How to survive your app going viral.

Will RaphaelsonWill Raphaelson

What's DuckDB?Free

Meet the world's friendliest database (allegedly).

Garrett O'BrienGarrett O'Brien
All posts →

Technically Speaking, hosted by Megan Reynolds, presented by Railway

Thanks to AI, everything we knew about software is stale.

On Technically Speaking, host Megan Reynolds, founder of infra.nyc, asks high-profile technical leaders to explain how it works and where it's headed. (Honestly, they're figuring it out too.)

Listen on
YouTubeApple PodcastsSpotify
Or use the RSS feed
Episode 2 · Thursday, October 29

What actually is AI research?

Every few weeks a new AI model tops the charts, as if dropped out of the sky. But what's the work that actually goes into that?
Jonathan FrankleChief AI Scientist at DatabricksMegan ReynoldsHostFounder at infra.nyc

Earlier episodes

  • Episode 1 · Thu, Oct 22

    We can do better than --dangerously-skip-permissions

    Michael GrinichFounder & CEO at WorkOS

Coming soon

  • Episode 3 · Out Thu, Nov 5

    What DeepSeek figured out, and why you shouldn't copy it

    Julien LaunayCofounder at Adaptive MLSesh NallaVP of Engineering at Datadog

On the calendar

  1. Episode 4 · Thu, Nov 12Jake Cooper, Founder and CEO at Railway
  2. Episode 5 · Thu, Nov 19Guest to be announced, Head of HardwareGuest Name, Head of Hardware at Company
  3. Episode 6 · Thu, Dec 3Guest to be announced, CEOGuest Name, CEO at Company
  4. Episode 7 · Thu, Dec 10Guest to be announced, Co-founder and CEOGuest Name, Co-founder and CEO at Company
  5. Episode 8 · Thu, Dec 17Guest to be announced, Co-founder and CEOGuest Name, Co-founder and CEO at Company
All episodes →
AI ReferenceSee all →

The guide to AI that you've been looking for. Click on any term for an in depth explanation.

Context WindowA context window is how much data an AI model can hold in memory at once.Post-TrainingPost-training turns a model from a knowledgeable blob that produces rambling answers, into a helpful assistant.Pre-TrainingPre-training is the "undergrad degree" phase where the model builds its foundational knowledge and world model.Training DatasetTraining datasets are the examples you show an AI model so it can learn to recognize patterns and make predictions.
The Vibe Coder's Guide to Deployment

The Vibe Coder's Guide to DeploymentFree

How your app gets off your laptop and onto the real internet, and what to do when a deploy breaks.

David KrevittDavid Krevitt
What is Google doing with AI?

What is Google doing with AI?

Inside Google's full-stack cloud bet, and how it differs from Microsoft and AWS.

Paolo PerronePaolo Perrone
Software Eng for Vibe Coders: Auth + Security

Software Eng for Vibe Coders: Auth + SecurityFree

How to make sure anyone on the internet can't just delete your app's data, and other security considerations.

David KrevittDavid Krevitt
How to use open-weight AI models

How to use open-weight AI models

Picking a model, a harness, and where to run the thing.

Will RaphaelsonWill Raphaelson
CompaniesSee all →

What their products actually do and why they're so valuable.

CloudflareCloudflare
Cloudflare provides networking tools that help companies distribute their apps globally and securely.
ElasticElastic
Elasticsearch is a popular open source database for storing and searching unstructured data.
LangChainLangChain
LangChain helps developers build AI experiences into their products.
New RelicNew Relic
New Relic is observability software: teams use it to monitor the performance of their apps and infrastructure.
GlossarySee all →

Quick explanations of the concepts you see every day.

AnalyticsAnalytics just means trying to use data to learn something.IaaSIaaS stands for Infrastructure as a Service, and it’s the lowest level of service available in the modern cloud ecosystem.Open SourceOpen source technically means that an app’s code is publicly available, but more generally refers to the movement of communities of developers building transparent, open codebases free for everyone to use.Web AppA web app is an application that you access through your browser.

Contributors

Afzal JasaniAfzal JasaniChristy BieberChristy BieberDavid KrevittDavid KrevittGarrett O'BrienGarrett O'BrienJustin GageJustin GageKenny NingKenny NingMatt HendersonMatt HendersonMegan ReynoldsMegan ReynoldsPaolo PerronePaolo PerronePaul IusztinPaul IusztinSachin BennySachin BennySam SchneiderSam SchneiderSarah Krasnik BedellSarah Krasnik BedellSung Won ChungSung Won ChungTereza TizkovaTereza TizkovaWill RaphaelsonWill Raphaelson

Learning Tracks

Curated collections of foundational articles to guide you through the basics of getting more technical at work.

AI, it's not that complicated ↗

How to understand and work effectively with AI and ML models and products.

  • How do Large Language Models work?

    Breaking down what ChatGPT and others are doing under the hood

  • What's RLHF?

    How AI models learned to stop being weird and start being helpful.

  • What's GPT-3?

    GPT-3 is a Machine Learning model that generates text.

  • What’s a data science notebook?

    Data Science Notebooks help data teams explore data with code.

Analyzing Software Companies ↗

The products and business models of leading software companies.

  • Databricks is apparently worth $100B. What do they even do?

    What we should really be asking is “What does Databricks not do?”

  • What does Snowflake do?

    Snowflake sells a powerful cloud data warehouse for analytics and data science teams.

  • What does OpenAI do?

    OpenAI is the most popular provider of generative AI models like GPT-4.

  • What does dbt do?

    dbt (no capitals) is a tool for transforming and organizing data in your warehouse.

Building Software Products ↗

How to make positive contributions to your product roadmap.

  • The top 5 things PMs should know about engineering

    Engineering and code basics that can make you a better PM to work with.

  • What's code?

    Code is step by step directions, but for computers.

  • What's the internet?

    A network of computers all connected to each other and sharing information.

  • What's cloud?

    Cloud is how companies rent infrastructure over the internet.

From Spreadsheets to Databases ↗

You've outgrown Excel, but you've got to put that data somewhere besides your parents basement.

  • The Beginner's Guide to Databases

    There are 300+ databases; what do they all do?

  • SQL for the rest of us

    If you’re not a data scientist but you have questions, you want to know SQL.

  • The Excel User's Guide to Databases: Schemas

    Why that schema change is going to take your engineers two weeks.

  • The Excel User's Guide to Databases: Migrations

    Why your feature is held up by a migration and why this is actually good.

How AI Models Actually Work ↗

Under the hood of today's powerful AI models: how they're trained, implemented, and otherwise used.

  • What is Machine Learning?

    How computers learn patterns from data — and why it’s the foundation for everything from stock prediction to ChatGPT.

  • How do Large Language Models work?

    Breaking down what ChatGPT and others are doing under the hood

  • How do you train an AI model?

    A deep dive into how models like ChatGPT get built.

  • The beginner’s guide to AI model architectures

    Unlike an onion, hopefully these neural network layers won't make you cry.

Software Engineering for Vibe Coders ↗

Your AI wrote the app. This is everything that happens after — where it runs, how it stays up, and what breaks first when real users show up. A six-part series, made with our friends at Railway.

  • Software Eng for Vibe Coders: On Frontends + Backends

    A new series to help non-engineers build products that can handle going viral.

  • Software Eng for Vibe Coders: Databases + Storage

    Where your vibe coded app actually keeps its data, and how it might break when real users show up.

  • Software Eng for Vibe Coders: Auth + Security

    How to make sure anyone on the internet can't just delete your app's data, and other security considerations.

  • The Vibe Coder's Guide to Deployment

    How your app gets off your laptop and onto the real internet, and what to do when a deploy breaks.

Working With Data Teams ↗

How to make positive contributions when working with analytics and data science teams.

  • How do product analytics work?

    Product analytics is how teams instrument and analyze data about their product usage.

  • What your data team is using: the analytics stack

    A deep dive into all of the tools that data teams use to do their work.

  • SQL for the rest of us

    If you’re not a data scientist but you have questions, you want to know SQL.

  • What's the Modern Data Stack?

    The new set of tools data teams use to get their jobs done.

Impress your agents

Join 70,000+ PMs, engineers, investors and operators who follow Technically to get sharper at work.

Subscribe...or just explore

"I work in private markets investing with an emphasis in technology. You’ve done a great job of succinctly explaining complex concepts in a digestible format."

— Mitchell Brady

"The product market fit between what you write about (and how you write) and what I want to learn about to become a more technically knowledgeable PM could not be tighter."

— James

"I'm a PM and Technically has allowed me better bridge the gap between user problems and how our system works under the hood. It's given me more confidence to push back or participate."

— Adelaide Hallowell

"As a banker without a technology background, I could not find a better learning resource than this."

— Siddarth Mujumdar

Content
  • All Posts
  • Podcast
  • Learning Tracks
  • AI Reference
  • Companies
  • Terms Universe
Company
  • Pricing
  • Sponsorships
  • Contribute
  • Contact
Connect
SubscribeSubstackYouTubeXLinkedInInstagram
Legal
  • Privacy Policy
  • Terms of Service

© 2026 Technically.