Fine-tune styles with smart selectors Continuing down our CSS path. The previous article can be found here: https://blog.devgenius.io/css-p3-nested-styling-and-styling-multiple-elements-ea40cc5ac727 Pseudo-class Selectors The last type of selector that we’ll cover is the pseudo-class selector. The ones that you will likely encounter are the ones pertaining to anchor tags, <a>. Let’s start by creating a simple link. <a href=”https://dinocajic.com”>Dino Cajic</a> The browser will underline the link and make the text color blue. When you hover over it, you may or may not see the color change. Visiting the link will likely change the color of from blue to purple. To modify the link appearance,
Author: Dino Cajic
Style whole sections with one smart rule Let’s continue with the CSS Basics. If you haven’t read the previous article, make sure to read it first. https://www.dinocajic.com/css-p2-basic-styling/ Nested Styling CSS allows for nested HTML element styling. In the example below, we have two paragraph tags. Each paragraph has a link and a button. <p id=”first-p”> <a href=”#”>Link 1</a> <button>Click Me</button> </p> <p id=”second-p”> <a href=”#”>Link 2</a> <button>No, Click Me</button> </p> Since neither the link, nor the button, has neither an id nor a class attribute, we must specify their styles through nesting. To select the link contained inside the first paragraph, we would write
Every inbox is a street market: noisy, cramped, and hard to stand out in. The first stall that catches your attention usually wins the sale, and in email that “stall” is your subject line. Executives now see subject lines as high-leverage real estate, and AI is turning it into data science. Analysts expect 75% of marketers to use AI for subject lines within a year, with vendor revenue growing about 25% annually . When the stakes are millions of emails, even small percentage lifts move the needle. What kind of lift? Studies peg the average bump at 10% more opens
And now onto the final part of the 3 part series. If you need to re-read the first two, here they are: Generative AI Use Cases in Enterprise Marketing Teams (2025) Generative AI Use Cases in Enterprise Marketing Teams (2025) – Part 2 – Social Media Use Cases AI-Powered Sentiment Analysis and Brand Reputation Monitoring Companies are using generative AI to gauge public sentiment and brand health across vast data sources, enabling proactive reputation management. Traditional sentiment analysis tools can tag mentions as positive/negative, but modern AI goes further: it can understand nuanced language and summarize why customers feel a
If you haven’t read the first article on Content Creation Use Cases, this is where you can find it. Generative AI Use Cases in Enterprise Marketing Teams (2025) In this one, we’ll continue with social media use cases. AI-Powered Social Media Content Generation & Scheduling Social media teams use generative AI to plan, write, and even schedule posts across platforms at scale. Instead of manually crafting each tweet (yes, I still refuse to call it an X) or LinkedIn update, marketers can leverage tools like Ocoya, Hootsuite’s OwlyWriter, or Copy.ai to generate dozens of posts in one go. These platforms
Generative AI is rapidly transforming how large marketing teams create content, manage social media, and track brand health. Recent reports show that over 60% of marketers are now using generative AI, primarily in content ideation and creation. Enterprise adopters are moving beyond experiments to scaled deployments that boost productivity and ROI. Below, I’ve compiled 15 concrete use cases across Content Creation, Social Media, and Brand Monitoring, with examples of tools and workflows (both off-the-shelf platforms like Jasper or Copy.ai and custom GPT-4/Claude integrations). Each use case includes a brief explanation of the AI-driven process and its outcome, including any available
A year ago, most people thought of autonomous AI workflows as something coming “soon.” But they’re already here, and they’re working. Across supply chain, finance, and healthcare, AI agents are showing they can make decisions on their own. They don’t just suggest next steps; they take action. And the companies using them are starting to see results. Supply Chains Are Learning to Fix Themselves Supply chain leaders have moved past dashboards and static alerts. Nearly half are using AI in production to reduce delays and cut costs (Gartner, 2025). These aren’t just smarter alerts; they’re full systems that reroute shipments,
A few weeks ago, I came across something that made me pause: the FDA is testing out OpenAI’s tech to speed up drug approvals. It’s not science fiction…it’s already happening. I’ve worked in environments where compliance, regulation, and tech all collide. And I know firsthand how slow those systems can move. So the idea of the FDA pushing for speed, using generative AI no less, caught my attention. And raised some questions. What’s happening? The FDA met with OpenAI to explore how a custom version of ChatGPT, something they’re calling “cderGPT,” might assist reviewers inside its drug evaluation division. What’s
Six months can be a lifetime in AI. The tools and processes that felt cutting-edge just a few months ago might already be behind the curve today. In an era where artificial intelligence capabilities are leaping forward at breakneck speed, professionals can’t afford to cling to static workflows. The core message is simple: stay flexible and proactive. What worked last year, or even last quarter, may now be outdated. By regularly reassessing and upgrading your workflow with newer, more capable AI models and platforms, you ensure you’re leveraging the best tools available rather than falling behind. The Rapid Evolution of
The rise of generative AI tools in the workplace has been meteoric. In early 2024, 75% of global knowledge workers reported using generative AI at work, a figure that nearly doubled in just six months . ChatGPT, for example, reached 1 million users in only five days(versus five years for Netflix), illustrating the breakneck pace of AI adoption. Business leaders have eagerly embraced these tools, hoping to boost efficiency amid economic pressures to “do more with less.” In fact, 96% of executives expect AI to increase productivity. Many organizations have even dubbed 2023 the “Year of Efficiency,” pushing teams to