Markizano.NET

You want 5 years experience with Cursor, when this March, 2026, Cursor will be 3 years old??!? I wish you the best of luck looking for your unicorn candidate that can't exist according to the laws of time... It's that time of the cycle again... That time when hiring managers and recruiters are looking for "extensive multi-year experience" in technologies that are barely 1-3 years old... The technology is moving and evolving so quickly that schools, let alone engineers can't keep up. Executives are so far removed from their industry that all they are looking at is Excel spreadsheets with profiles that have the right numbers. They are completely ignoring details that are critical for the success of their business. Meanwhile, the stock market is the most irrational with its "fire first, ask questions later" mentality, causing more chaos and instability. Here's the reality: If you don't know how to describe what you want, how do I know you wil...

In response to a LinkedIn post I came across (If you are part of the AWS Certification & Training ). I hit the character limit 😅, so extending on that here. DevOps Automation DevOps has been trying to automate itself out of its role since its inception. That was the whole point of the role in the first place and yet still many orgs are facing: Totally custom setups and never-ending edge cases. Operational dysfunction. Multiple disjointed tools that perform the same functions. Development teams operating in silos that don't conform to the federated guidance DevOps is attempting to implement. Incomplete monitoring systems or multiple monitoring tools that don't cross communicate. Incredibly ever complex logs with vague descriptions as to what actually went wrong. Office politics where confusion exists around role and responsibility when the pipeline breaks. Current Challenges Many orgs are still: In the phase of getting away from monolithic apps into micr...

This is a rant post. The problem I have with AI has multiple layers. I'll try to cover them as best I can in this post. However, this may change over time. Premise It started with an email from Lovable. This weekend, they are doing "free credits" for this championship match among the top AI companies out there: OpenAI (ChatGPT), Anthropic (Claude/Sonnet) and Google (Gemini). So I login to see what's going on and what can be done. I talk with ChatGPT a bit on the side to help me craft the perfect prompt. Then I feed that into Lovable to see what the result is. My intention is to have it build the scaffolding and beginning of the front-end so I can continue developing the back-end and have the app up in a weekend. This should go like a breeze, right? Wrong... Problems Current AI Limitations Perception Created Results of Perception Let's break down all these points I see and the outcomes they may produce down the line in the hopes I can save at lea...

Regarding: ChatGPT's recent release of Codex I can see so many ways in which this can go right and wrong and in between. Ways it can go right: Vibe Coding : Developers are starting to learn how to incorporate and use LLM's with coding software. This whole "vibe coding" movement is another tool, not a replacement to writing code. There are far too many edge cases and problems with Vibe Coding that warrants a skilled developer to be able to troubleshoot issues and offer a creative hand where LLM's cannot provide. Developer Workflow : I've seen where folks are starting to learn how to spoon feed the LLM a prompt about a specific context, let it work on that context, review the changes, then work on the next context as completion runs along. This isn't new. I've seen devs plan out their functions before filling the body of them with the operations they should consume. This results in more efficient development and hence the reason why TDD ( Test Drive...

The messed up part about AI that nobody's talking about is how it slows down senior engineers. While it may be great at "Hello world" and simple algorithms, many times, senior engineers are way past this, and don't really need help building boiler plate code because it just doesn't scale. I find myself more often than not, fighting with AI in some cases rather than using it to write stuff for me that I need done quickly. From custom algorithms or complex situations where scale, multiple contexts or hidden details about how computers and coding works that you don't gain from the RactJS tutorials, even design patterns that are gained from learning other languages cannot be captured and implemented by AI just yet (learn how C and C++ works and then tell me you know how to code properly in JavaScript) to its inability to write in Angular vs ReactJS or even use a different language other than Python for a product solution. We all know JavaScript and Python are not...

In the world of Development Operations (or DevOps as it's coming to be known today), there are many tools coming into focus that are allowing us to do more and expand to newer heights than before. In this post, I want to talk about Puppet and SaltStack. Both are really great tools, don't get me wrong. I admire the power and benefits of both, but there were solid reasons we chose to go with one over the other, and reasons why I still chose one over the other today. This is going to be a compare and contrast post between the two technologies. Puppet Let's talk about Puppet:  https://puppet.com/ . Puppet is a great tool for what it was designed to do. It was also first on the market with its first beta version back in 2005 . It's first 2.6 release in 2010 , and I came to know about it around version 3.x in 2013. It's good for what it was originally created to perform: Systems automation. However the catalog creation process is often a bottleneck in performance ...