KakaComputer : Weekly Guide for IT Insights

YoungCTO and others

>> Episodes Drop Tuesday and Thursday Morning >> "🎙️ Dive into the digital world with KakaComputer! 💻 Your go-to podcast for tech tips, IT insights, and the latest in computing. Whether you're a newbie or a pro, we've got something for everyone. Tune in and level up your tech game!"

  1. 104 - Clean Code: More Than Just Pretty Syntax

    2 DAYS AGO

    104 - Clean Code: More Than Just Pretty Syntax

    Why writing maintainable code is a career skill, not a coding style. On this episode, we have Alex, Christopher Bryan, Charles Mejica Madronero, and Edd Alc joining us to discuss clean code and why writing maintainable code is a career skill, not just a coding style. Clean code isn’t about perfection—it’s about clarity, maintainability, and collaboration. In this episode, we talk to developers who prioritize writing code that other people (including their future selves) can read, debug, and scale. We’ll unpack why clean code matters beyond job interviews, how it impacts teams and long-term projects, and the habits that separate average coders from great ones over time. What’s your personal definition of clean code? (Generalization) My personal definition of clean code is code that is easy to read, easy to understand, and easy to change. It’s code that tells a story, so that another developer can look at it and immediately grasp its purpose without excessive comments. It’s also code that has a clear structure and organization, making it predictable and simple to navigate. Essentially, it's code that prioritizes the human reader over the machine. Have you ever had to clean up someone else’s messy codebase? What was that like? (Generalization) Absolutely. Cleaning up a messy codebase is a common rite of passage for many developers. It can be a very challenging and frustrating experience, much like trying to untangle a massive knot of string. The process often involves a lot of detective work to understand the original intent of the code, and a significant amount of time spent on refactoring and writing tests to ensure changes don't break existing functionality. While difficult, it's also a powerful learning experience that highlights the importance of good code hygiene. What small habits help you write cleaner, more maintainable code every day? (Generalization) A few small habits make a big difference. I always aim to use descriptive variable and function names so their purpose is immediately clear. I also try to keep functions small and focused on a single task, following the Single Responsibility Principle. Additionally, I’m a firm believer in automated testing; a good suite of tests acts as a safety net that allows me to refactor and improve code confidently without fear of introducing new bugs. Is there ever a time when writing clean code is not the priority? (Generalization) Yes, there are rare situations where clean code is not the top priority. This most often happens in a crisis or emergency, such as when a critical system is down and needs to be fixed immediately. In such cases, the priority is to get the system working again as quickly as possible. Similarly, during a rapid prototyping or proof-of-concept phase, a developer might prioritize speed and functionality to validate an idea. However, in these situations, it's crucial to acknowledge the "mess" and plan to refactor it later to avoid long-term technical debt.

    17 min
  2. 103 - Low-Code, No-Code, AI Code: Who’s Building What Now?

    4 DAYS AGO

    103 - Low-Code, No-Code, AI Code: Who’s Building What Now?

    Are developers being replaced—or just evolving? On this episode, we have Alex, Christopher Bryan, Charles Mejica Madronero, and Edd Alc joining us to discuss the rise of low-code, no-code, and AI-generated code and explore who's building what now. The rise of low-code, no-code, and AI-generated code is changing who gets to build software—and how fast it gets built. This episode explores what these tools mean for traditional developers, citizen developers, and tech teams as a whole. We’ll talk about opportunities, limitations, and whether this shift is empowering or threatening the future of software engineering as we know it. What are the biggest misconceptions about low-code and no-code platforms? (Generalization) One of the biggest misconceptions is that these tools are only for simple websites or prototypes. In reality, modern low-code platforms are powerful enough to build complex, enterprise-level applications with custom logic. Another misconception is that they will completely replace developers. Instead, they are better seen as tools that automate repetitive tasks, freeing up developers to focus on more challenging architectural problems, integrations, and unique features. Can someone build a real career using only these tools? (Generalization) Yes, a person can build a real and valuable career as a "citizen developer" or "low-code engineer." However, this career often looks different from a traditional software engineering path. Success depends on a deep understanding of business processes, problem-solving, and data integration. Professionals who master these tools can become highly valuable by rapidly delivering solutions and bridging the gap between business needs and technical implementation. How should developers respond to the rise of AI-generated code? (Generalization) Developers should respond to AI-generated code not with fear, but by embracing it as a new and powerful tool. AI will likely handle more boilerplate and repetitive coding tasks, allowing developers to focus on higher-level design, complex logic, and architectural challenges. The role of a developer is shifting to one of a technical leader who can write, debug, and critically evaluate the code AI produces, ensuring it's robust, secure, and fits within the larger system. What kinds of projects are a good fit for low-code solutions—and which aren’t? (Generalization) Low-code solutions are an excellent fit for projects with well-defined business logic and standard requirements, such as internal tools, customer portals, or simple mobile apps. They are ideal when speed and rapid iteration are the top priorities. They are generally not a good fit for projects that require highly custom, performance-critical, or complex algorithms, such as high-frequency trading platforms, graphics engines, or specialized machine learning models that demand fine-grained control over the code.

    16 min
  3. 102 - Building a Dev Agency. Scaling Your Development Business.

    20 AUG

    102 - Building a Dev Agency. Scaling Your Development Business.

    On this episode, we have Raphael Quisumbing, Miguel Fermin, and Jason Tores joining us to discuss the journey of building a successful dev agency. This episode dives into the challenging yet rewarding journey of building a successful development agency from the ground up. Our guests, who have navigated this path, will share their experiences in moving from a solo freelancer to leading a team. We'll explore the key steps in a dev agency's growth, from finding your first clients to building a sustainable business model, and discuss the unique challenges of managing people, projects, and profits in the dynamic world of tech. What are the key differences between being a solo freelancer and running a development agency? (Generalization) The key difference is the shift from a "doer" to a "manager". As a freelancer, your focus is on delivering projects yourself and managing client relationships. As an agency owner, your primary job becomes managing a team, overseeing multiple projects, and focusing on business development, sales, and marketing. You move from billing for your time to creating a scalable system that can deliver work through others, which requires a completely different skill set. How do you find your first clients and build a reputation in a competitive market? (Generalization) Finding your first clients often starts with leveraging your existing network and personal connections. Building a reputation is about delivering exceptional work on those early projects and getting strong testimonials or case studies. You can also build credibility by actively participating in tech communities, speaking at local events, or creating valuable content that showcases your expertise. The goal is to establish trust and demonstrate a track record of success. What are some of the biggest challenges in scaling a dev agency, and how can they be overcome? (Generalization) One of the biggest challenges is talent acquisition and retention, as a great team is the core of any agency. Another major hurdle is managing cash flow and pricing projects correctly to ensure profitability. Overcoming these involves building a strong company culture, offering competitive benefits, and establishing robust project management processes. You must also constantly refine your sales and marketing strategy to ensure a steady pipeline of work that supports your growing team. What are the essential business skills that a tech-savvy person needs to learn to successfully run an agency? (Generalization) A tech-savvy founder needs to learn essential business skills like financial management, including budgeting, invoicing, and understanding profit margins. Sales and negotiation are also crucial, as is effective people management, including hiring, performance reviews, and team leadership. Learning to delegate and trust your team is perhaps the most important skill, as it allows you to step away from the day-to-day technical work and focus on the strategic growth of the business.

    27 min
  4. 101 - Team Size Management. Aligning people, not just tasks.

    18 AUG

    101 - Team Size Management. Aligning people, not just tasks.

    In this episode, we have Raphael Quisumbing, Andresito De Guzman, and Jason Tores joining us to discuss the strategies behind effective team size management. Navigating the optimal size for a tech team is a critical challenge for any leader. This episode explores the art and science of team size management, from the agile "two-pizza team" to scaling larger projects. Our guests will discuss the signs that a team is too big or too small, the impact of team size on communication and productivity, and practical strategies for restructuring teams to meet evolving project needs. We’ll delve into the balance between maintaining a cohesive, efficient unit and ensuring you have the right talent to get the job done. What are the telltale signs that an IT team is becoming too big or too small for its current project? (Generalization) A team that is too big often suffers from increased communication overhead and slower decision-making, leading to a noticeable drop in individual productivity. Conversely, a team that is too small might show signs of developer burnout, consistent missed deadlines, and a lack of specialization for key tasks. Both scenarios can result in a significant decrease in project velocity and overall team morale. The right size is often indicated by a smooth workflow and a manageable number of communication channels. How does the size of a team directly impact communication and overall project productivity? (Generalization) The size of a team is directly tied to its communication complexity, often following a non-linear scale. As a team grows, the number of potential communication pathways increases exponentially, which can lead to misinformation, silos, and slower collaboration. While a larger team has more hands for coding, the added time spent in meetings and aligning work can actually decrease overall productivity. Smaller teams, on the other hand, benefit from direct communication and greater cohesion, which can make them highly productive. What are some practical strategies for restructuring or re-sizing a team to meet evolving project needs? (Generalization) Restructuring a team requires a thoughtful, data-driven approach. A common strategy is to split larger teams into smaller, more focused "pods" or sub-teams with clear, independent goals. This can improve efficiency and reduce coordination overhead. For teams that are too small, leadership can identify skill gaps and strategically hire to fill specific needs, or cross-train existing members to increase flexibility. The key is to avoid arbitrary cuts or additions and instead base all changes on the project's evolving requirements. How can leaders balance the need for a cohesive, long-standing team with the need to bring in new talent for new projects? (Generalization) Leaders can maintain this balance by fostering a strong, welcoming team culture that values new perspectives as much as established relationships. When bringing in new talent, they should have a structured and thoughtful onboarding process that integrates them smoothly. Existing team members can be empowered to act as mentors, which solidifies their own knowledge while building trust with new hires. This approach ensures that the team benefits from new skills without losing the cohesion and shared knowledge that has made it successful.

    19 min
  5. 100 - CTO Time Machine: First 3 Years vs. Next 5 Years. The evolution of leadership in a growing tech company.

    13 AUG

    100 - CTO Time Machine: First 3 Years vs. Next 5 Years. The evolution of leadership in a growing tech company.

    On this episode, we have Maki Villano, Ragde Falcis, Rafi, and Andresito joining us to discuss the CTO Time Machine and how leadership evolves in a growing tech company. The role of a CTO doesn’t stay the same for long. In a growing company, leadership evolves alongside the technology. This episode takes a time-machine-style look at how CTOs transition from scrappy early builders to strategic leaders managing scale, people, and long-term vision. Our guests share key lessons from both phases—and the moments that forced them to rethink everything they thought they knew about leading in tech. What were your main responsibilities in your first year as CTO, and how have they changed? (Generalization) In the first year as CTO, responsibilities were often hands-on and tactical. The primary focus was on building the initial product, making key architectural decisions, and writing a significant amount of code. The job was about being the lead builder and problem-solver. Today, the role has shifted to being more strategic and managerial. The focus is now on scaling the engineering organization, mentoring team leads, fostering a strong technical culture, and aligning technology investments with the long-term business vision. How do you balance hands-on coding with long-term strategy? (Generalization) Balancing hands-on work with long-term strategy is a constant challenge. The key is to delegate effectively and trust the team to handle the day-to-day technical challenges. While it's important to stay technically sharp, a CTO's primary value is in setting the strategic direction. This often means reserving a small portion of time for code reviews or small technical spikes, but dedicating the majority of time to roadmap planning, architectural governance, and identifying future technological opportunities and risks. It's about being a guide, not just a doer. What’s something you wish you invested in earlier—tools, people, or processes? (Generalization) Most CTOs wish they invested in people and processes earlier, as these are the true foundations for scaling. While a focus on building a product is natural at the start, underinvesting in hiring the right talent and establishing clear development processes can create significant bottlenecks later. This includes investing in strong talent acquisition, onboarding procedures, and implementing disciplined project management and documentation practices. Tools are important, but the right people and processes make the tools truly effective. What does “success” look like now compared to when you started? (Generalization) When starting out, "success" was often defined by shipping a product, fixing a critical bug, or hitting a technical milestone. It was a very binary, tangible form of success. Today, success is much more nuanced. It’s measured by the growth and autonomy of the team, the robustness of the system, and the ability of the technology to enable new business opportunities. Success now means building an organization that can innovate and scale independently, rather than just a product that works.

    16 min
  6. 99 - Is the Software Development Life Cycle Still Relevant? Rethinking SDLC in the age of Agile, DevOps, and AI.

    11 AUG

    99 - Is the Software Development Life Cycle Still Relevant? Rethinking SDLC in the age of Agile, DevOps, and AI.

    On this episode, we have Alex, Maki Villano, Edd Alc, and Charles Mejica Madronero joining us to discuss if the Software Development Life Cycle is still relevant in the age of Agile, DevOps, and AI. The Software Development Life Cycle (SDLC) has long been a foundation of software engineering—but is it still relevant in today’s fast-moving tech world? This episode revisits the classic SDLC model in light of Agile, DevOps, and AI-assisted coding. We’ll examine how modern practices have evolved or replaced traditional phases, and whether the core principles of SDLC still hold value in current development workflows. Do you think the traditional SDLC is outdated—or just misunderstood? (Generalization) The traditional SDLC is often considered misunderstood rather than completely outdated. While the rigid, sequential "waterfall" model is no longer practical for most modern projects, the underlying core principles of the SDLC—like planning, design, implementation, and testing—are still fundamental. Modern methodologies like Agile and DevOps haven't replaced the SDLC; instead, they represent a more iterative, continuous, and collaborative way of executing these same essential phases. The concept is still valid, but its application has evolved significantly. Which part of the SDLC do you think developers ignore the most today? (Generalization) Developers today often tend to ignore the documentation and maintenance phases of the SDLC the most. In the fast-paced world of Agile and continuous delivery, the focus is heavily on rapid development and new feature releases. Comprehensive documentation is sometimes seen as a secondary task and can be neglected, leading to knowledge gaps. Similarly, proactive maintenance and long-term planning for system health can be overlooked in favor of building new features, which can create significant technical debt down the line. How do Agile and DevOps integrate or conflict with classic SDLC stages? (Generalization) Agile and DevOps don't necessarily conflict with classic SDLC stages; rather, they integrate them into a continuous, cyclical process. Instead of a single, long-form SDLC, they break the cycle into smaller, iterative loops. Agile focuses on delivering working software frequently and getting continuous feedback, so all SDLC stages are repeated for each sprint. DevOps emphasizes automating and integrating the development and operations stages, particularly testing and deployment, to ensure a smooth flow throughout the entire lifecycle. Has AI development changed how we plan or test software? (Generalization) Yes, AI development has fundamentally changed how we plan and test software. In the planning phase, we now have to consider data collection, quality, and ethical implications in a way that traditional software didn't require. Testing has also been transformed. We're moving beyond simple unit tests to focus on more complex, data-driven challenges like evaluating model accuracy, detecting bias, and ensuring the reliability of predictive outcomes. AI-assisted coding tools are also starting to change the implementation phase, helping developers write code more efficiently and with fewer errors.

    16 min
  7. 98 - IT Project Management 101: Plans, People, and Pivots

    6 AUG

    98 - IT Project Management 101: Plans, People, and Pivots

    On this episode, we have Maki Villano, Oscar Oganiza, Andresito De Guzman, and Eddnie Alcaraz joining us to discuss "IT Project Management 101: Plans, People, and Pivots" and What it really takes to lead tech projects from idea to execution. Project management in IT isn't just about tools—it’s about people, pressure, and pivoting fast. This episode breaks down what it really takes to manage tech projects successfully, especially when things don’t go according to plan. The guests share experiences from the field, covering stakeholder management, communication breakdowns, and how to maintain momentum when timelines shift or resources run thin. What’s one project that taught you a tough lesson about leadership? (Generalization) One project stands out as a significant learning experience, offering profound insights into the intricacies of project leadership. It presented unique challenges that tested the limits of conventional management strategies. The experience ultimately reshaped the understanding of effective leadership in a dynamic project environment. How do you decide when it’s time to pivot or change scope? (Generalization) Determining the right moment to pivot or alter a project's scope involves careful consideration of multiple factors. It often requires assessing the project's current trajectory against its original objectives and anticipated outcomes. The decision is frequently influenced by new information, unforeseen obstacles, or shifts in the broader market or technological landscape. What’s your strategy when a project starts slipping off schedule? (Generalization) When a project begins to deviate from its schedule, a proactive and structured strategy is immediately implemented. This involves a thorough analysis to identify the root causes of the delay. Subsequently, a revised plan is developed, often incorporating resource re-allocation, task prioritization, or the introduction of accelerated workflows to bring the project back on track. How do you keep the team aligned when stress levels rise? (Generalization) Maintaining team alignment becomes paramount when stress levels escalate within a project. The focus shifts to fostering open communication and ensuring every team member feels supported and heard. Strategies often include regular check-ins, transparent updates on project status, and reinforcing shared goals to keep everyone unified despite the pressure.

    17 min
  8. 97 - The Frontlines of Tech: What IT Support Specialists Actually Do

    4 AUG

    97 - The Frontlines of Tech: What IT Support Specialists Actually Do

    On this episode, we have Maki Villano, Jayz Carrillo, Raphael Quisumbing and Oscar Oganiza joining us to discuss "The Frontlines of Tech: What IT Support Specialists Actually Do" and A deep dive into one of IT’s most underrated roles. IT Support Specialists are often the unsung heroes of the tech world. This episode sheds light on what they actually do—from resolving technical issues to keeping systems running and ensuring teams stay productive. We explore the skills needed to succeed in this role, how it’s evolving with automation and AI, and why strong support can make or break an organization’s daily operations—especially when things go wrong. What’s the most misunderstood part of being in IT support? (Generalization) Many people outside of the field believe IT support is solely about fixing computers. However, it involves a wide range of responsibilities, including user education, proactive maintenance, and strategic problem-solving. The complexity of troubleshooting modern systems is often underestimated by those who are not directly involved. What kind of skills does this role require beyond technical knowledge? (Generalization) Beyond technical expertise, this role demands exceptional communication skills, as specialists often translate complex technical issues into understandable terms for diverse users. Patience and empathy are also crucial, as they frequently interact with frustrated individuals experiencing technical difficulties. Problem-solving skills are paramount, enabling effective diagnosis and resolution of often intricate issues. Can IT support be a long-term career path—and what does growth look like? (Generalization) IT support can certainly be a long-term career path with various avenues for advancement. Growth often involves specializing in areas like network administration, cybersecurity, or cloud computing. Many professionals also transition into management roles, leading teams of support specialists. How do you handle burnout when problems just keep coming? (Generalization) Managing burnout in this demanding role requires effective strategies for stress reduction. Taking regular breaks and maintaining a healthy work-life balance can help prevent exhaustion. Prioritizing tasks and delegating when possible are also key to managing the continuous flow of issues. How is the IT support role evolving with the rise of AI and automation? (Generalization) The IT support role is significantly evolving with the integration of AI and automation, which are streamlining many routine tasks. This shift allows specialists to focus on more complex, strategic problems that require human intervention and critical thinking. The future of IT support will likely see a greater emphasis on advanced troubleshooting and system optimization rather than repetitive issue resolution.

    15 min
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>> Episodes Drop Tuesday and Thursday Morning >> "🎙️ Dive into the digital world with KakaComputer! 💻 Your go-to podcast for tech tips, IT insights, and the latest in computing. Whether you're a newbie or a pro, we've got something for everyone. Tune in and level up your tech game!"

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