Bytebytego retweeted
5 AI Building Blocks Every Engineer Should Know
- LLMs
- Embedding Models
- RAG
- Agent Harnesses
- World Models
Bytebytego retweeted
Google Translate: The Ideas Behind Neural Translation
A simplified illustration of common techniques. Not an exact map of Google Translate’s current system.
Bytebytego retweeted
Jev is TypeSafe AI's first System One Model.
It is 100x faster and cheaper than frontier LLMs.
That opens up a lot of use cases people usually skip because the big models are too slow or too expensive for them.
Here are 9 use cases where we think Jev could be used instead of an LLM.
Bytebytego retweeted
🚀 Announcing ByteByteGo Live: learn AI live from real builders.
I’ve spent the past 8 years on education: thousands of hours writing books, deep dive newsletters, YouTube, etc.
Two issues I keep seeing are: 1) it’s very different to learn from real builders. 2) most online courses never get finished (~4% completion).
Over the past 12 months, we’ve been working on what we can do to change that.
Today, I’m excited to announce ByteByteGo Live: live cohort courses taught by real builders.
- Taught by real builders. Our instructors include very senior engineers from Google, Meta, etc., as well as @KentBeck , the creator of TDD. They teach what they use in their own work.
- Live cohorts. Every course runs live with a group of people, and instructors answer your questions in real time.
The current lineup:
- AI Engineering Fundamentals
- Build with Claude Code
- Build Production Grade AI Systems
- Rebuild YouTube with AI
- AI Evals in Practice
- AI Cost Optimization
- Trust-optimized AI Development
We have big plans for the year ahead: more courses, more instructors, and deeper hands on projects.
Check out go.bytebytego.com/live-launc… and let us know what you think.
Bytebytego retweeted
What keeps the Internet running.
We probably forget they exist until the day something breaks.
Bytebytego retweeted
Visualizing a SQL query in 5 mins
SQL statements are executed by the database system in several steps, including:
- Parsing the SQL statement and checking its validity
- Transforming the SQL into an internal representation, such as relational algebra
- Optimizing the internal representation and creating an execution plan that utilizes index information
- Executing the plan and returning the results



















