Diego Pacheco Tech blog

Let me remove the obvious issues before I make my point. Ignoring problems is bad; ignoring problems at scale is even worse. If we have a network effect of ignoring things at scale, that's the worst thing we can do. Ignoring problems leads to Ignoring culture . Being aggressive with problems is not being reckless; it's not about moving so fast that we break things by doing it so. When applying for software, we ask some apparent questions but sometimes forget to apply for people. In software, we don't want to discover all the bugs in production; we want to shift left and find as many problems as possible before going to production. We must apply the shift left to people and address the issues immediately. The sooner we find problems, the sooner we fix them, and the sooner things improve. 

It's normal for engineers to think of the best solution possible when we think of solutions. A bad engineer would deliver as fast as possible without even considering whether his work is good enough or right. A "good" engineer would think a lot about how to do it and be very slow. A great engineer does both things. So, how can you be fast and slow at the same time? When we are working on a pretty small problem, or in a green field(a new project where you can do whatever you want), and/or a small company or startup with very little software. We all want to have success, and we want companies to thrive; success means more software, and more software often means more technical debt, and it becomes impossible to change everything all the time.

July 2024: I wrote the first blog post about The Dark Side of LLMs . During these 7 months, many things have changed; the usage of AI and LLMs in engineering has kept growing. LLMs and AI are cool. However, they are not a free lunch and have consequences. If you have not read the first blog post of this series, go there and read it because it will be relevant to this one. One significant open-source development in LLM was  DeepSeek .DeepSeek is interesting for two factors: one that is considerably cheaper and second that is open source. Deepseek introduced a series of optimizations like parallelism, chain of thought (COT), which step by step so we can fix the model where is wrong and usage of Reinforcement Learning (RL) along side with Destilation. RL is how robots roll and self-driving cars also move in a city.  Deepseek's being open source is great for the community; however, we also see interesting moves from big tech companies like  Meta ,  Microsoft ,  Goog...

I have been doing practical and real software architecture for more than 20+ years. Software architecture is a great passion of mine, close to my heart and even to my identity or just id function if we think about functional programming :-). I have mentored and coached many architects during the last two decades. Today, I want to share some thoughts on something that represents the complexity and duality of the software architect role. Being an architect is not easy, it requires a lot of sound judgment, trade-offs analysis, design skills, research, requirements extraction, trend prediction, futurology, and lots of non-obvious skills. Architects must code, be practical, and make very good calls, resulting in better positioning for the future. Doing such a task is not easy and requires a lot of hard work; it's demanding and requires constant improvement and attention to detail. What is essential to extrapolate an architect's non-obvious antagonistic skill set, which the architect...

I love feedback. I believe in feedback a lot. However, not all feedback is good, not all feedback is applicable, and not all feedback is fair. Feedback is critical for course correction and growth. However feedback can be manifested in a variety of shapes, forms and intentions. I believe in creating several mechanisms for feedback because, eventually, what needs to be found will be found. Feedback is a signal; sometimes, it tells more about who is giving the feedback than the person receiving it. Other times, feedback is just wrong. Whether feedback is written or bad, it's an important signal. I believe in being more effective and in the speed of change and improvements. However, can you go fast if you dont understand what you are doing? That's my issue with feedback. Oftentimes, feedback is poorly constructed and missing essential details. So, dealing with feedback is not so different than handling high-priority, difficult production bugs. Requires deep tought, introspection, ...

Quality often means something different to each person. My definition of quality revolves around technical excellence. To achieve this, we need good architecture, sound design based on strong principles, good code, tests in a wide variety and diversity, and proper observability. To get there, we need refactoring(a lot), and I would also include good troubleshooting and review sessions.  Quality involves not only delivering automated product deployments but also ensuring the software is maintainable. Delivering software on time is not enough, and delivering value to the customer is not enough either because people and software are expensive. We need to do better.  Quality needs to be built-in, a strong, solid lean principle. However, we don't have as many incentives to built-in quality as we do for finishing projects on time. Projects are always associated with direct value to the company, and quality is often optional and mismanaged. Quality does not mean QA, and it's way beyo...

If you look up on dictionary.com the first two definitions of state are: the condition of a person or thing, as with respect to circumstances or attributes: a state of health. The condition of matter with respect to structure, form, constitution, phase, or the like: water in a gaseous state. Software is all about data, which is the state. The state could be your basic data, such as your name, last name, address, phone, email, bank account ID, or any other IDs and information you might have. Buying software has many side effects, many of which  are negative . Such data needs to be captured somewhere, usually in a relational database. But it could be in any other data store like a NoSQL Database like Cassandra, a K/V store like Redis, or an object store like S3. Ideally, the state should be contained and even isolated. However, in distributed systems, we often need a distributed state. The state is necessary. However, we might create additional complexity if we don't deal with the s...