GitHub is the world’s largest and most popular platform for version control and collaborative coding. But when it comes to choosing a GitHub plan, things can get confusing. With different pricing tiers, storage limits, CI/CD allowances, and add-ons like GitHub Copilot, it’s easy to feel overwhelmed. This guide breaks down GitHub’s pricing structure, explains the differences between each plan, and helps you figure out which option best suits your needs.
AI coding assistants have rapidly evolved into tools that developers now use daily. Among the most talked-about options are GitHub Copilot and Cursor. Both promise to accelerate development, reduce repetitive work, and make coding more enjoyable, but they do so in different ways.
Microsoft licensing is vast and constantly evolving, which makes understanding it a critical, but complex, task for IT leaders. With so many product tiers, bundles, and add-ons, it’s not always clear how to structure a licensing strategy that balances cost, capability, and flexibility.
Most leaders know the frustration of unreliable data: reports that don’t match, duplicate customer records, or systems that don’t talk to each other. I’ve seen these challenges play out in organizations of every size, and I’ve also seen how proper Master Data Management can turn the tide.
I stared at my screen, equal parts amazed and alarmed. I had just vibe-coded a solution to a code challenge that normally takes senior devs 3–4 hours to complete. I had done it in 10 minutes — and it passed 100% of our review checks. Software development is undeniably changing. The question on my mind is: what is it changing into?
Data strategy is inherently cross-functional. It lives at the intersection of business goals, operational workflows, technology, and user behavior. Without a shared definition of success, teams operate in silos and often solve the wrong problems with the right tools. Here’s the question I always come back to with clients: What decision are you trying to support? Everything flows from there.
Artificial intelligence is moving fast, but most enterprises still feel stuck. A recent McKinsey study found that 70% of AI proof-of-concepts never make it past the pilot phase. At Emergent Software, we’ve spent the last few years deep in the AI trenches, helping organizations move from experimentation to tangible outcomes. Alongside my colleague Brian Anderson, we’ve gathered a number of lessons from the field that can help enterprises break through the common barriers and finally get AI into production.
When I think about the skills that have made the biggest difference in my career, one stands out that doesn’t always get the recognition it deserves. Translation.
When organizations seek agility and scalability, they turn to containerization—the driving force behind modern application deployment. Azure Container Apps, Microsoft's innovative serverless container service, paired with the power of Docker, empowers organizations to build applications that thrive under dynamic workloads. In this blog, we’ll uncover how Azure Container Apps redefines enterprise deployment, offering a seamless blend of scalability, reliability, and efficiency.
It’s easy to overspend in the cloud if you’re not watching closely. It’s just the nature of the platform. You’ve got flexibility, endless features, and instant scalability... but if you treat Azure the same way you treated your old data center, you may run into some issues.
Emergent Software offers a full set of software-based services from custom software development to ongoing system maintenance & support serving clients from all industries in the Twin Cities metro, greater Minnesota and throughout the country.
A software development and consulting company serving clients from all industries in the Twin Cities metro, greater Minnesota and throughout the country.
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