In the fast-paced world of technology, not everything you read is accurate or unbiased. Not everything you read was written by a human! The details can be subtly wrong, or an article can be intentionally misleading. Let's take a look at a few skills that can help you consume tech articles – or any media content.
Developing a healthy sense of skepticism is crucial. Question bold claims, look for supporting evidence, and don't take everything at face value.
An article that starts with a number – like this one – is often a listicle. These are lower effort than longer, single-topic articles. While they can be fleshed out, they may only have a few sentences on each topic. I would say it's good to start with skepticism when faced with a listicle.
Listicles are also much more likely to be AI generated these days. It's easy to ask a generative AI for "ten reasons" or "a dozen best practices" and get something informational back. AI generation doesn't mean the article is bad, but it does require more skepticism because generative AI does not reason about its responses.
Finally, Listicles are also a great way to dress up an advertisement for a product as helpful information. I see these daily.
Avoid agreeing with content just because it sounds authoritative. The writing style can have a lot of impact on how well you absorb and consume the content, but rhetoric is a powerful tool to drive perception. Asserting something is true in an article is not the same as it being true, and we should be cautious of authors that make claims without evidence.
The article source can be important. Tech publications used to provide a level of credibility, but in an open forum we have to do a bit more work. Understanding the background and potential biases of an author can help you better interpret the presented information.
Authors can come from all levels of experience. They can be the developers who created the software in question, or they can be someone sharing their learning journey.
An author can be an expert, writing to share general knowledge. They might describe a specific problem they've overcome. They might share a specific problem their software can overcome. They can be a conduit for generative AI content. Popular creators and influencers may provide "hot takes" to drive engagement more than to share substantive concerns. Understanding the goal of an article can help you decide if you should be more skeptical of a particular article, or a specific author.
We can't expect every content source to be well-established, but credentialed authors can also release questionable content. Still, it's a good starting point. Identifying the author can help set your expectations and help you guard against making assumptions.
This one is hard. It's easy to get caught up in the hype or group-think around a library or coding practice. You'll see a lot of "Stop Using This" and "Do This, Not That" articles suggesting that some new solution, often not yet a standard, is the only right way to do things.
It's also easy to become stuck in the bias of your preconceptions. Are you resistant to certain tools or ideas because you have negative experiences with them? Is the experience the fault of the tool, or were there problems around the implementation?
We are wired to find patterns and establish bias, and doing so can be helpful at times, but is less helpful when presented with new ideas. Change is hard, but self-reflection can help you approach information fairly and recognize when your views might be changing your interpretation.
We don't have to accept everything equally; that's an important part of healthy skepticism. But we can recognize when an internal response occurs while we are still gathering information, and to combat – or at least acknowledge – the assumptions we might make.
Don't rely on a single source for information. Good articles will often provide you links to sources and references that can make this process easier. You may need to take the time to locate other reputable sources.
An article may link to the same source for several points, which can raise questions about the validity of the source or argument. Checking sources provided and established authorities can help you verify facts or assertions and provide a better understanding of the topic.
Supporting evidence is really important. Not everything requires an authoritative source, but factual claims in particular should have a source. If the article contains no links or source references, take the assertions they make with a grain of salt. Remember that "common knowledge" isn't always accurate.
Many industries have built up their own terminology over time, and shared language is an important tool for effective communication. It's hard to read a technical article without running into some jargon. Whether it's the "normal forms" in databases or the many entries in functional programming jargon, there are plenty of terms we won't know.
You should make a habit of looking up unfamiliar terms and concepts. When you can't find resources for a term, don't be afraid to ask or leave a comment. Perhaps a term is industry-specific, and not specifically technical. Likely you are not the only one missing out on the term. Or you might be one of the lucky 10000!
Now that we've looked skeptically at the content, made sure of the source, checked our own biases, validated the information, and learned the terminology, we can get down to the work of absorbing information and letting it transform our understandings.
How could the technology or concept discussed be applied in real-world scenarios? Does it affect your current project? Could it have made sense in a previous project?
This analysis skill helps you connect theoretical knowledge with practical applications, enhancing your overall understanding of the tech landscape. This is critical to growing as a developer.
Not every article needs you to sit down and write some code, but it can be helpful. I often use a tool like RunJS to hack together quick code samples or refactor functions with new ideas. For bigger efforts I might clone a repo or create a branch in my project to try something new.
Spending a little time trying out a new idea, style, or library can help us understand its capabilities and limitations, or our limitations. Maybe we need to do more research in a particular area. Or a specific topic may be really complicated and we just need to keep that in mind when it comes up.
These skills can significantly improve your ability to read and interpret tech articles. Remember, becoming a skilled reader of technical content is an ongoing process. The landscape of content is rapidly changing, both in how we consume valid information and how advertising and generated content of varied quality impacts our reading lists and our time.
Continue to practice these skills, and hopefully you'll find navigating the complex world of technology articles easier.
Are there any skills or techniques you use to help vet sources or improve your analysis? I'd love to hear about them!
I used AI to create an initial outline of this article. Generated content was heavily re-written. I recommend a tool like the QuillBot AI Detector to help identify articles likely to have been produced with generative AI.
Header image generated with Apple Image Playground Beta.
I receive no compensation for mentions or links to sites or products.
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