ByteByteGo Newsletter

In this article, we will learn how Instacart’s search infrastructure evolved over the years and the challenges its engineering team faced.

In this article, we will look at this progression that has happened from basic tool use to function calling to the Model Context Protocol, allowing the LLMs to go from isolated text generation tools to assistants that can do interesting stuff for the end users.

Both MCP and Skills extend what an agent can do. But they solve different problems, and picking the wrong one adds cost or complexity you don't need.

In this article, we will learn how Kubernetes is a system of promises, and that every piece of it is a small program keeping one of those promises.

The Tech Stack Powering Wise Most teams optimize models. Few optimize inference. We benchmarked NVIDIA RTX PRO 6000 Blackwell on Akamai Cloud against H100 using real LLM workloads. At 100 concurrent requests, Blackwell reached 24,240 tokens/sec per server, compared to 1,863 TPS on H100. That’s up to 1.63× higher throughput, with additional gains from FP4 precision. The difference comes down to ar…

In this article, we will look at how Stripe’s Radar does this effectively and the architectural decisions the team took while building it.

In this article, we will look at how COSMO works and the challenges the engineering team faced.

Storing data is the easy part. Deciding where and how to organize it is the real challenge.

In this article, we will look at B-Trees and LSM trees in detail, along with the trade-offs associated with each of them.

In this article, we will look at how this architecture was designed and the challenges they faced.

In this article, we will look at how GitHub built a security architecture that assumes the agent is already compromised.

We compile, run, and debug Java code all the time. But what exactly does the JVM do between compile and run?

In this article, we cover the core concepts that inform those decisions. We’ll look at tables, keys, relationships, normalization, and joins, with each concept building on the last.

This article covers how Figma’s design-to-code and code-to-design workflows actually work, starting with why the obvious approaches fail, how MCP solves them, and the engineering challenges that remain.

In this article, we will look at how the LinkedIn engineering team rebuilt the Feed and the challenges they faced.

EP210: Monolithic vs Microservices vs Serverless If slow QA processes bottleneck you or your software engineering team and you’re releasing slower because of it — you need to check out QA Wolf. QA Wolf’s AI-native service supports web and mobile apps, delivering 80% automated test coverage in weeks and helping teams ship 5x faster by reducing QA cycles to minutes. QA Wolf takes testing off your p…

What do authentication, logging, rate limiting, and input validation have in common?

How Spotify Ships to 675 Million Users Every Week Without Breaking Things Most tools are still locked to their own database, blind to everything users already have in Slack, GitHub, Salesforce, Google Drive, and dozens of other apps. That's the ceiling on what you can build. WorkOS Pipes removes it. One API call connects your product to the apps your users live in. Pull context from their tools, …

Nextdoor operates as a hyper-local social networking service that connects neighbors based on their geographic location.

In this article, we’ll look at how LLMs actually process the information you give them, what context engineering is, and the strategies that can help with it.