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The Big Archive for System Design - 2023 Edition (PDF) is available now. And it's completely FREE.
The PDF contains 𝐚𝐥𝐥 𝐦𝐲 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐩𝐨𝐬𝐭𝐬 published in 2023.
What’s included in the PDF?
🔹 Netflix's Tech Stack
🔹 Top 5 common ways to improve API performance
🔹 Linux boot Process Explained
🔹 CAP, BASE, SOLID, KISS, What do these acronyms mean?
🔹 Explaining JSON Web Token (JWT) to a 10 year old Kid
🔹 Explaining 8 Popular Network Protocols in 1 Diagram
🔹 Top 5 Software Architectural Patterns
🔹 OAuth 2.0 Flows
🔹 What does API gateway do?
🔹 Linux file system explained
🔹 18 Key Design Patterns Every Developer Should Know
🔹 Best ways to test system functionality
🔹 Top 6 Load Balancing Algorithms
🔹 Top 12 Tips for API Security
🔹 𝐀𝐧𝐝 100+ 𝐦𝐨𝐫𝐞
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Bytebytego retweeted
5 AI Building Blocks Every Engineer Should Know
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Google Translate: The Ideas Behind Neural Translation
A simplified illustration of common techniques. Not an exact map of Google Translate’s current system.
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Top 6 Techniques to Make Your AI System Efficient
Serving LLMs at scale is expensive. These 6 popular techniques reduce latency and cost, and make your system more efficient.
If you want to redo it yourself, here's the GitHub repo with step-by-step instructions you can follow:
github.com/mikhailsychevbyte…
Watch an ex-YouTube engineer rebuild YouTube in 45 minutes.
By the end it's running:
- Home feed
- Video upload to the cloud
- Video playback from the cloud
- Data in a real database
- Search, using multimodal embeddings
- Deployed to a real URL
All of those explained in under an hour.
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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.
GPT-Live is the most natural, conversational voice model we've tried.
Under the hood, it pairs a new generation of voice model architecture with a serving system built for low latency.
To understand how it all works end to end, we sat down with two engineers on the GPT Voice team: Zahan Malkani and Justin Uberti (the creator of WebRTC).
In our deep dive, you'll learn:
- The three generations of voice systems: cascaded pipelines, turn-based end-to-end models, and full-duplex models
- Why separating thinking from talking is the core idea behind GPT-Live
- The engineering behind the serving system, including the live and async paths
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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.


















