In an era where digital interactions underpin almost every facet of our lives, ensuring the security and authenticity of online identities has never been more crucial. Did you know that over 60% of elder fraud cases are linked to compromised digital identities? From gig work platforms relying on seamless background checks and identity verification to adult websites navigating stringent age verification laws, the need for robust and reliable identity verification solutions is paramount. Enter Chains of Trust and Distributed Identity Verification—innovative concepts poised to revolutionize how we establish and maintain secure online environments. This blog post delves into these cutting-edge technologies, exploring their benefits, real-world applications, and the pivotal role of blockchain-based solutions in navigating the complex landscape of online compliance.

Introduction

With Google’s announcement of its Willow chip, interest in quantum computing continues to grow. To understand its potential implications, I consulted various articles and then used OpenAI’s ChatGPT to help organize and refine the information. After several rounds of prompts and revisions, I compiled the following paper, which explores how quantum computing may shape the future of technology.

Link to my converstion

Classical and Quantum Computing Foundations, Architectures, and Impact

Introduction

The field of computing is undergoing a transformative shift as quantum computing emerges from theoretical possibility to experimental reality. Classical computing, which has formed the bedrock of modern software engineering, is built on deterministic operations and binary data representations. Quantum computing, by contrast, exploits the principles of quantum mechanics—such as superposition—to perform certain computations more efficiently than any known classical algorithm. As professional software engineers, understanding these differences and the potential ramifications on areas like security, simulation of natural systems (e.g., drug discovery), and artificial intelligence is increasingly important.

Managing Software Complexity: Why It Matters and How to Do It Right

In software engineering, complexity isn’t just a buzzword—it’s a challenge that can make or break your projects. The more complex your software, the harder it is to maintain, scale, and extend. This is where understanding and managing software complexity becomes crucial.

But why does complexity matter so much? To answer that, we turn to Lehman’s Laws of Software Evolution, formulated by Meir Lehman in the 1970s. These laws describe the inevitable evolution of software systems and the forces that shape them. One of the key insights from these laws is that software systems must evolve to remain useful. However, as they evolve, they tend to become more complex unless active efforts are made to manage this complexity.

When it comes to deploying your side project without breaking the bank, there are plenty of options available. Popular choices like Vercel and Netlify are widely used, but they come with their own limitations. One of the biggest issues is that it’s easy to exceed their free tier limits, which can lead to unexpected charges. I’ve seen stories of people racking up bills in the thousands because of this. Plus, these platforms don’t offer free databases, which makes it challenging to build sites with dynamic content. And while you used to be able to rely on services like Planetscale for free database hosting, they’ve recently removed their free tier. That’s where Coolify comes in.

Introduction

This post is designed to introduce you to Temporal, a powerful workflow engine, especially if you’re new to its capabilities. We’ll explore how Temporal can bring value to your projects, breaking down its complexities into understandable parts, whether you’re just starting or are already experienced in software development.

What is a Workflow?

Let’s start with some definitions:

• Workflow: Think of a workflow as a series of activities that are executed in a specific order. Each step flows into the next, like a well-choreographed dance. Workflows are central to how Temporal operates. For a deeper understanding of workflows and how they differ from sagas, you can refer to this Stack Overflow discussion and this YouTube presentation.

Managing multiple versions of your tooling can get quite difficult and tedious. There are solutions for specific languages such as Pipenv and Conda for Python. The downside is that you have 2 different package management systems associated with each and you’ll have to reach for a different tool to manage versions of a different programming language.

Enter ASDF, the Multiple Runtime Manager. ASDF allows you to configure your tooling in a single config file per project. This allows you to have entirely different setups between projects and have consistency between your machine, your co-worker’s machine, and in CI/CD pipelines.

At a previous (unnamed) company, I had the privilege of working on a core search project. The goal of this project was to simplify the architecture and reduce the latency in updating the search index based on user actions. In retrospect, this project could have gone a lot better if we had made use of tools and patterns that I learned after leaving the company. I think the team did the best with what we had available to us.

Apache Kafka is a powerful distributed data streaming platform. It allows you to build an event-based architecture where the consumers of data are decoupled from its production. An event source could be your production database, containing all the events for your e-commerce site, or clickstream data from your web app. If required, you can even maintain the order of events on a per-entity basis. This is a huge advantage over similar solutions, such as Amazon SQS. But how can we analyze and make sense of the data in a topic of interest? Let’s explore a few solutions, but first, we must understand a few core concepts.

There seems to have been a massive shift in the available supply of money for tech companies to burn. The ZIRP era has ended. The next question for me is how this will impact the way we build and sell software.

Enter DHH and Jason

Jason C. and DHH had a very interesting conversation in a recent edition of This Week in Startups regarding the impact of the recent belt-tightening required by the market shift. Many SaaS products tend to charge based on the usage of their product. Pricing is commonly based on how many accounts or the volume of data processed by the application. This cost of the product scales with its usage. Some of these offerings have managed to become deeply integrated into the workflows of their customers, which makes their products sticky. If the SaaS company changes their pricing structure, there is little a customer can do. The customer could find an alternative solution, but that is time and money not spent on its own product and operations.