Most async APIs commit to one thing: starting your job. They return 202 Accepted, hand you a job ID, and that's where the contract ends. The rest is your problem. I do something different. I make one promise: When your job is done, I'll tell you accurately. Until then, I'll keep retrying. That's the entire contract for everything I've ever shipped. It sounds small. In practice, it's the only thing
Why this list is different The "best" email API depends entirely on what you're building. A side project optimizing for the free tier needs different things than a Series B SaaS sending two million transactional emails a month. This post grades eight providers against the criteria that actually move the needle in production, and tells you which one to pick for which use case. Most roundups in th
This section is the map for the rest of the book. The five stages introduced in the 1.1 chapter overview (parse, analyze/rewrite, plan, portal, execute) are traced here through the actual code: which functions implement each stage, and in what order they get called. The mechanics of each of the five stages are unpacked in later chapters. Here, only the skeleton matters: how a backend starts up, ho
If you’ve been building with AI recently, you’ve probably seen these terms everywhere: AI Gateway. And depending on where you read, they either sound like the same thing… or completely different systems. Some vendors use them interchangeably. Others define only one and ignore the rest. And if you try to piece it together yourself, you end up with a vague understanding that doesn’t really help when
PostgreSQL Internals · Chapter 1 Query Processing Suppose a client sends SELECT * FROM users WHERE id = 1. The path that single line travels before coming back as a result row is longer than you might expect. Inside the PostgreSQL backend, that SQL goes through a five-stage pipeline. Backend entry and dispatch. The backend receives the message from the client and decides which processing path it s
If you want to Automate GitHub PRs, the real goal is not just adding another bot comment to a pull request. The goal is to give reviewers the context they usually have to gather manually: who owns the service, whether it is deployed, whether basic repository standards are in place, and whether the change looks safe to merge. A useful AI pull request workflow can do exactly that. When a PR opens, i
The API Rate Limit Catastrophe In modern B2B SaaS development at Smart Tech Devs, your application rarely lives in isolation. You constantly communicate with external services: billing via Stripe, CRM syncing via Salesforce, or email campaigns via Resend. The architectural trap occurs when you combine the immense speed of Laravel Queues with the strict rate limits of these third-party APIs. If you
A short guide to organizing FastAPI apps beyond a single main.py file. FastAPI makes it easy to start with a single main.py file. That is great for demos, prototypes, and small APIs. But once your application grows, one file can quickly turn into a mix of routes, database logic, security helpers, settings, and business rules. A clear project structure helps keep the app easier to understand, test,