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Image by upklyak on Magnific Run an application. Click a few buttons. If the terminal doesn't have errors, then everything is working. Right? What's the point of writing tests if all seems to be fine. Let's explore testing discipline and why it's a habit every developer should build early. What is Testing Discipline? Testing discipline is the habit of verifying that your code works. It's not something you do at the end of a project. It's something you build into your development process. The goal is simple. Catch bugs as early as possible. A bug found while writing code usually takes minutes to fix. The same bug found in production can take hours to investigate, reproduce, and resolve. The earlier you find problems, the less expensive they become. Different Types of Tests When people talk about testing, they're usually referring to three categories. The first is unit testing . A unit test checks a single piece of functionality, usually a function or method. These tests are fast and easy to write, making them the best place for beginners to start. Next are integration tests . These verify that different parts of your application work together correctly. For example, does your service communicate properly with the database? Finally, there are end-to-end tests . These simulate a real user interacting with the application from start to finish. They provide the most realistic results but are usually slower and more complex. As a beginner, I recommend that you should focus on unit tests first. Different Testing Approaches As you continue learning, you'll come across different testing methodologies. One of the most popular is Test-Driven Development , often called TDD. The idea is simple. Write the test first. Watch it fail. Write enough code to make it pass. Many developers like this approach because it forces them to think about requirements before writing implementation details. You may also hear about Behaviour-Driven Development , or BDD. This approach focuses on desc

Over the past few months, I’ve increasingly noticed something through my network: more people from non-technical backgrounds are building software as AI tooling improves. Designers are prototyping product ideas. Product managers are testing workflows. Founders are building MVPs. Operators are creating internal tools. People who would not have called themselves “technical” a year ago are now using AI to make ideas tangible. I think this is genuinely exciting. It has never been easier to create. I even attended a hackathon where participants only had 20 minutes to build a demoable product! This raises the question: When AI makes building easier, how do we make sure understanding does not disappear? I recently published Thinking in the Age of AI , a guide for software engineers (you can check out my previous post here ). That guide focused on individual reflection for engineers: how to keep developing technical intuition, reasoning, and judgment while using AI tools. But the landscape has changed quickly. AI-assisted building is no longer only an engineering workflow. It is becoming a builder workflow accessible to all. And by builders, I mean anyone using AI to turn ideas into software-like artifacts: vibe coders designers product managers founders operators marketers students non-engineering team members So I wanted to create a new version of the system for this wider builder audience. Thinking in the Age of AI: Builder Edition The opportunity is real I do not think we should dismiss this shift. I have spoken with people from all kinds of backgrounds who are actively building now. People who previously had to wait for engineering time can now create something concrete. That changes the conversation. Instead of describing an abstract idea, you can show a flow. Instead of writing a long product spec, you can prototype the interaction. Instead of asking “would this work?”, you can test a rough version. That is powerful. But there is a trap. A prototype can look much mor

I recently launched SpotClause, a small AI contract review and reader tool. The idea came from a simple problem: contracts are often difficult to read, especially for freelancers, consultants, and small teams who receive agreements but do not work with contract language every day. SpotClause helps users: summarize contracts in plain language identify key clauses understand payment terms, renewal terms, cancellation language, obligations, and deadlines compare two contract versions and see added, removed, changed, and unchanged wording I also added a Contract Clause Library with plain-language explanations of common clauses like cancellation clauses, renewal clauses, payment terms, confidentiality clauses, and notice periods. You can try the AI Contract Review Tool here: AI Contract Review Tool You can explore the Contract Clause Library here: Contract Clause Library SpotClause is not a law firm and does not provide legal advice. The goal is to help people understand contract language more clearly. I would appreciate feedback on: whether the homepage explains the product clearly whether the AI contract review page feels understandable what clause explanations would be useful to add next

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ASUS' new ROG Xbox Ally X20 has mostly the same hardware as last year's handheld, but now comes with a new OLED panel.

Strava will charge a flat monthly fee from developers to access its API

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Shopify Staff Engineer Guilherme Carreiro discusses building and scaling highly customizable platforms. Using Shopify’s Liquid theme system as a case study, he explains how to balance extreme design flexibility with low-latency performance under massive traffic. He shares insights on implementing secure domain-specific languages, native code extensions, and resilient developer tooling. By Guilherme Carreiro

Nvidia has officially entered the world of consumer laptop chips with the RTX Spark, and several device makers already have hardware lined up for it. Microsoft, Asus, HP, MSI, Lenovo, and Dell are expected to launch RTX Spark laptops sometime this fall, and some of those partner companies have shared details about what we can […]

With true plug-and-play support, versatile connectivity, and excellent sound, Universal Audio’s Volt 876 makes recording simple.

The AI productivity paradox states that AI scales whatever abstraction it is built on. If that abstraction is structurally brittle, it scales structural brittleness. This article shows how, to build a future of reliable, AI-driven test automation, we must stop scaling DOM-centric abstractions and build a new testing paradigm grounded in perception and intent. By Amanul Chowdhury, Vinay Gummadavelli

Michael Stiefel spoke to Sonya Natanzon, about the intersection of technical and social aspects of software architecture. Understanding the business and how a company operates is more important than the specific technologies used. Effective requirements analysis requires focusing on problems to be solved that describe good and bad outcomes, rather than statements of need or solution statements. By Sonya Natanzon

Dozens of people have complained to the Federal Trade Commission about Norse Atlantic Airways’ tech-first customer service operation. Some said they lost thousands of dollars.

I tried to explain OpenAI’s solution more clearly than OpenAI did.

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In this excerpt from WIRED Book Club pick The Yahoo Boys, journalist Carlos Barragán traces one scammer’s journey from flop to fortune.

GitHub热门项目 | Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration | Stars: 1,122 | 58 stars today | 语言: JavaScript

The Seoul-based rocket startup is developing its own launch vehicles and engines.

OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new path to build with OpenAI through the AWS environments, controls, and procurement workflows they already use. Customers can get started with OpenAI on AWS and move faster from evaluation to production.