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.
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.
This episode explores how platforms like TikTok are reshaping the way tech professionals learn, teach, build credibility, and find opportunities. We’ll discuss whether short-form content can drive real career growth, help launch projects, attract clients, and even influence how companies hire or evaluate talent.
This episode shines a spotlight on Bisaya tech professionals who grew up, studied, or started their careers in Visayas and Mindanao, then took bold steps into larger tech ecosystems—whether Manila, overseas, or remote global roles.We explore what makes Bisaya talent resilient, resourceful, and highly competitive in tech, and the unique challenges faced when leaving home—culture shifts, language barriers, confidence gaps, financial risks, imposter syndrome, and navigating bigger corporate environments.At the same time, we celebrate their wins: breaking into top companies, earning certifications, mentoring others, and proving that world-class tech talent doesn’t only come from big-city schools.
We look at the power of open-source philosophy as the competitive edge for modern companies. This episode explores how transparent development, shared knowledge, and active community mentorship accelerate innovation far more effectively than closed, proprietary systems. Our guests discuss the economic benefits, ethical responsibilities, and cultural shifts required to truly embrace an open future.
Is your job just a job, or is it a calling? This episode explores the concept of purpose-driven careers in technology, where professionals seek meaning beyond standard metrics like salary or job title. Our guests share their personal journeys on aligning their values with their work, transitioning to roles with higher social impact, and sustaining motivation through meaningful contributions.
We challenge the conventional view of leadership as being tied to a job title. This episode explores how influence, mentorship, and driving initiatives happen at every level in open and agile organizations. Our guests share insights into contributing value beyond defined roles, taking ownership of problems, and cultivating a culture where everyone feels empowered to step up and lead change.
Software development is a team sport, and this episode shines a light on the crucial roles outside of coding. We celebrate the professionals—from QA testers and technical writers to product owners and support specialists—who ensure technology is functional, reliable, and user-ready. Our guests discuss career paths, the unique skill sets needed, and how non-developers directly drive the success of a product.
The best code is built by the best teams. This episode explores the vital role of engineering culture in driving success. We discuss how high-performing teams foster trust, handle constructive conflict, and establish psychological safety, moving beyond just technical excellence. Our guests share actionable strategies for leaders and members to cultivate an environment where collaboration thrives.
On this episode, we have Ryana Que, Jaime Hing III, and Dominique Villafuert joining us to discuss "Empathy by Design" and how human-centered tech drives meaningful change.We dive into the philosophy of human-centered design, where technology is built with the user's real-world context and needs in mind. This episode explores how empathy leads to more inclusive and impactful products, discussing the difference between building something that works and building something that genuinely serves humanity. How can engineers and designers actively build empathy for users whose backgrounds are vastly different from their own? (Generalization)Engineers and designers can actively build empathy through immersive research and intentional exposure. This involves moving beyond simple surveys to conduct field studies, contextual interviews, and "shadowing" users in their natural environments. Another effective technique is persona creation that includes socioeconomic, cultural, and technological access details, forcing the team to design for constraints they don't personally share. Furthermore, incorporating diverse users into the testing and feedback loops—not just at the end, but throughout the design process—is crucial for recognizing and mitigating personal biases.What is one non-obvious example of a product where a lack of empathy led to a critical failure? (Generalization)One non-obvious example is the early design of some biometric or facial recognition systems that exhibited much higher error rates for individuals with darker skin tones. The failure wasn't malicious, but a lack of empathy in the training data—the developers, often unconsciously, used datasets that disproportionately featured lighter-skinned individuals. This lack of inclusive data empathy led to a critical failure where the technology was effectively less functional and inherently biased against a significant portion of the global population, causing ethical and practical failures.In the race for speed, how do teams ensure they don't sideline inclusivity and accessibility checks? (Generalization)To prevent sidelining these checks, teams must integrate them as non-negotiable, automated steps within the development pipeline. This means adopting a "shift left" approach, where accessibility and inclusivity are baked into the definition of "done" for every feature, not treated as a final-stage QA step. Utilizing automated accessibility tools in continuous integration and making compliance with global standards (like WCAG) a core requirement for code review ensure these checks are a fundamental part of speed, rather than a separate hurdle.What role does thoughtful design play in mitigating the negative ethical or social impacts of new technology? (Generalization)Thoughtful design serves as the first line of defense against negative ethical and social impacts. It involves proactively considering the "worst-case scenario" or unintended consequences of a product—not just how it can be used, but how it could be misused. By employing ethical design principles (e.g., designing friction to slow down harmful actions, prioritizing privacy by default, and making AI decisions transparent), designers can build guardrails into the user experience. This helps steer user behavior toward positive outcomes and minimizes opportunities for misuse or social manipulation.
On this episode, we have Ryana Que, Waffen Sultan, Paolo Mahomuri, and Josan Astrid Dometita joining us to discuss building for impact beyond the 9-to-5 through passion projects and community-driven innovation.Not all great tech starts in the office — sometimes it begins as a personal itch to solve a problem. In this episode, we explore how passion projects, volunteer work, and community-driven innovation can evolve into tools that impact citizens, businesses, and government. Hear how simple curiosity, grit, and a desire to help can scale into mission-driven technology with real-world influence.
On this episode, we have Ryana Que, Andrew Concepcion, and Waffen Sultan joining us to discuss "Code for the People: Inside the BetterGov Movement" and how open-source developers are reshaping digital governance in the Philippines.The Philippines' digital infrastructure has long been a source of frustration for its citizens, with outdated websites and confusing processes creating barriers to essential services. We explore the BetterGov Movement, a grassroots, volunteer-driven initiative using open-source technology to build a more user-friendly and transparent national government portal. We talk to these civic tech advocates about turning citizen frustration into collaborative action.What was the specific moment of frustration that compelled you to stop waiting and start building BetterGov.ph? (Generalization)The compelling moment of frustration is typically an experience with a broken or confusing government online service. This often involves a simple task, like checking requirements for a document or finding an official form, that becomes unnecessarily complicated by outdated websites, broken links, or conflicting information. The realization is that the problem isn't technical complexity, but a lack of user-centric design and cohesion. This leads to the thought, "If I can build a better user interface in a weekend, imagine what a community could do," thus starting the initiative.How do you maintain quality and consistency when the entire project is built and maintained by volunteers? (Generalization)Maintaining quality in a volunteer project relies heavily on strong processes, clear governance, and community culture. This involves strictly enforcing code review standards, utilizing continuous integration tools to automate quality checks, and maintaining comprehensive, accessible documentation. Consistency is ensured by establishing a design system and style guide early on. Crucially, the community culture must prioritize learning and mutual respect, where constructive feedback is the norm and veteran volunteers mentor newcomers to ensure code quality is a shared responsibility.What is the biggest lesson the government could learn from an open-source, community-led project like this? (Generalization)The biggest lesson is the power of transparency and iterative development. The community model thrives on open communication, allowing citizens to see progress, suggest improvements, and hold the project accountable. This contrasts with traditional government projects that are often opaque. By embracing open-source principles, the government could learn to launch early, iterate based on user feedback (citizens), and leverage the collective intelligence of the nation's developer pool to rapidly improve essential digital services.What is the biggest challenge of working with public data and making it truly accessible to the non-technical Filipino citizen? (Generalization)The biggest challenge is the poor quality and fragmented nature of the source data. Government data often resides in silos, lacks standardization, is not machine-readable, or is simply outdated. Making it accessible requires more than just displaying it on a website; it means translating complex bureaucratic language into simple, actionable information and designing user interfaces that require zero technical skill to navigate. The difficulty lies in sanitizing and unifying disparate data sources so the non-technical citizen can easily find definitive answers to their essential questions.
Winning isn't the only goal. This episode is for everyone who is nervous about joining their first hackathon. While most people talk about how to win, we're focused on what you can learn from losing. We'll share our own stories of not winning and explain why it's not a failure, but a crucial step toward building new skills, expanding your network, and setting yourself up for future
Highlighting expertise in early-stage product dev, market fit, prototyping, and AI.On this episode, we have Jon Prado, Grahssel Dungca, Andresito De Guzman and Luis Maverick Gabriel joining us to discuss the tough but rewarding process of finding product-market fit and the keys to early-stage product development in startups, especially those leveraging AI.Startups succeed or fail on whether their product actually meets a market need. This episode explores the tough but rewarding process of finding product-market fit, especially in AI and tech-driven products. Guests share stories about prototyping, iterating, and pivoting—plus insights on what early teams often miss.What’s a mistake you’ve made (or seen) in chasing product-market fit? (Generalization)A common and costly mistake is building too much, too soon, based on assumptions rather than validated customer needs. This is often called "solution looking for a problem." Startups might spend months polishing a comprehensive feature set without properly validating whether customers would actually pay for the core value proposition. This leads to wasted resources and a painful realization that the market doesn't value the complexity. The right approach is to focus on a Minimum Viable Product (MVP) to quickly test the core hypothesis.How does AI change the prototyping and product design process? (Generalization)AI dramatically accelerates the prototyping and product design process by providing powerful new capabilities. It allows teams to prototype features that were previously impossible, such as real-time personalization, predictive user flows, or complex data analysis. AI tools also enable rapid iteration on design itself by generating wireframes, code snippets, or content variations. However, it also introduces complexity, requiring designers to think about data input, model explainability, and ethical implications from the earliest design stages.For startups, how do you know when it’s time to pivot vs. persist? (Generalization)Knowing when to pivot versus persist often comes down to analyzing key performance indicators (KPIs) and the conviction of the founding team. You should persist if your core hypothesis is sound, but your execution or market timing is slightly off, showing gradual positive traction. You should pivot if you are seeing continuous low engagement, high churn, or if your customer interviews consistently reveal that your solution doesn't solve a high-priority problem for them. The decision to pivot is generally made when the data shows that the current path is financially unsustainable or leads to a dead-end market.What’s one tool or framework you recommend for early-stage teams? (Generalization)The most highly recommended framework for early-stage teams is the Lean Startup Methodology. This framework emphasizes the Build-Measure-Learn feedback loop, which is essential for quickly achieving product-market fit. It forces teams to prioritize validated learning over pure feature development. Key tools that support this framework include simple prototyping tools for quick MVPs and robust analytics platforms for accurately measuring user behavior and validating or refuting core assumptions.
Why empathy-driven design and security must go hand in hand.On this episode, we have Asi Guiang, Piolo Justin Cabigao, Kayne Rodrigo, and Ted Mathew Dela Cruz joining us to discuss empathy in innovation and why building secure tech requires a human-centric approach.Technology is meant to serve people, but what happens when it makes them vulnerable? In this episode, we're exploring the critical connection between empathy and cybersecurity. We’ll discuss why understanding a user's fears and needs is the key to building secure and ethical tech. Our guests will share how a human-centric approach to design can protect people from online threats and build trust in the digital world.How does empathy help you anticipate user vulnerabilities that security protocols might miss? (Generalization)Empathy helps anticipate user vulnerabilities by forcing you to see the product through the eyes of the person using it, not just the code. It allows you to understand their real-world context, common stressors, and behavioral patterns. For example, a security protocol might enforce a complex password, but empathy recognizes a tired user will write it down or reuse a similar one. By considering the "human element"—their lack of specialized knowledge, potential for distraction, or motivation to take shortcuts—empathy reveals vulnerabilities that purely technical audits would overlook, leading to more practical and effective security solutions.Can you give an example of a product that failed because it lacked empathy in its security design? (Generalization)A common example is two-factor authentication (2FA) systems that are difficult, slow, or constantly interruptive to the user's workflow. While technically secure, a system that lacks empathy for the user's time and convenience may lead to widespread user adoption failure. Users might disable the feature, choose the least secure option (like SMS), or simply become so frustrated they avoid using the secure system altogether. This failure isn't technical; it's a failure of adoption caused by prioritizing technical rigidity over a smooth user experience, ultimately leaving the user vulnerable.What's one practical step developers can take to include empathy in their security practices? (Generalization)One practical step is to adopt the practice of "persona-based threat modeling." Instead of only modeling threats from sophisticated malicious actors, developers should create personas for their actual users (e.g., a time-crunched manager, a non-technical senior) and model threats based on user mistakes and common vulnerabilities. This involves asking, "How might this person accidentally expose data?" This approach shifts the focus from purely stopping hackers to building fewer opportunities for user error, making the security inherently more resilient and user-friendly.How can we train the next generation of tech professionals to prioritize both innovation and user safety? (Generalization)We can train the next generation by integrating ethics and user-centric security into the core curriculum, rather than treating them as add-on courses. Every project, from the start, should include mandatory requirements for both security and usability reviews. Creating interdisciplinary teams composed of designers, developers, and security experts during academic and early career projects helps them learn to speak the same language. This teaches them that security and empathy are not blockers to innovation, but rather foundational requirements for building trustworthy and sustainable technology.
Work Smart, Not Harder: The New Rules of TechIn this episode, we're diving into the ever-evolving world of tech and how our ways of working are changing with it. It's a crucial conversation for the Philippines, where we've seen a slower adoption of new work styles. We'll explore the often-unspoken topics that truly shape a tech career, from the intricacies of corporate politics and how to navigate them with grace, to optimizing working agreements to ensure your team not only collaborates, but also hits its product goals. Join us as we unpack these challenges and share practical insights to help you thrive in the modern tech landscape.
Why the future of innovation depends on understanding what people feel, not just what they do.Technology doesn’t just solve problems—it makes people feel safe, frustrated, empowered, or excluded. This episode explores how emotional intelligence in design can be the difference between a product’s failure and success. Guests will share how emotions shape adoption, trust, and the user’s overall journey.
It's our anniversary, and we're dedicating this episode entirely to the Kakacomputer community! We're diving into the Spotify comments to read your feedback, shout out your usernames, and share the posts that made us smile. This is your episode, packed with direct audience interaction and appreciation. Thanks for a fantastic year!
 User research is more than surveys and interviews—it’s the foundation of breakthrough innovation. This episode dives into how listening to users uncovers hidden needs, guides product direction, and even prevents costly mistakes. Guests highlight methods, stories, and how empathy drives better solutions.
Your Degree Doesn't Define You. Tech Is For Everyone.On this episode, we have Michael Escobilla, Charvin Peñaverde, Juan Carlo Claudio, and Luigi Espiritu joining us to discuss "When Non-Tech Goes Tech - A Transformation Journey" and why your degree doesn't define you.This episode is for anyone who thinks a career in tech is out of reach without a computer science degree. We'll share our own stories of moving from non-tech roles, like Human Resources, into the digital world. Join us as we talk about the changes we made and the lessons we learned on our journey. It's an inspiring conversation that proves you don't have to be a traditional tech professional to innovate and make a real impact in today's world.What was the moment you realized you wanted to shift into tech? (Generalization)The realization often comes from a moment of dissatisfaction with the status quo of the previous career and an attraction to the problem-solving nature of technology. It might be realizing that tech skills were needed to solve a key issue in the non-tech field, or simply discovering that the fast pace and continuous learning inherent in the IT world were more engaging. For many, the shift is driven by seeing the massive impact that technology has on every industry and wanting to be part of that innovation.For someone coming from a non-tech background, what's the one skill they can leverage the most? (Generalization)The most valuable skill non-tech professionals can leverage is domain expertise and business context. A background in fields like HR, finance, or marketing gives them an intimate understanding of specific user needs, regulatory constraints, and business goals that pure technologists often lack. This knowledge is crucial for bridging the gap between technical teams and business stakeholders, allowing them to build products and solutions that are truly relevant and impactful to the organization.What was the biggest learning curve for you? Was it a technical skill or something else entirely? (Generalization)For many, the biggest learning curve is less about a specific technical language and more about adopting the "tech mindset". This involves shifting from a static, procedure-driven approach to an iterative, agile, and constantly evolving one. It means becoming comfortable with continuous failure, debugging, and rapid change. While technical skills can be learned, internalizing the culture of perpetual learning, documentation, and systematic problem-solving is often the hardest, yet most critical, transition.How did you deal with the feeling of imposter syndrome when you first started working in a tech role? (Generalization)Dealing with imposter syndrome requires consciously separating feelings from facts. The strategy involves acknowledging the feeling but focusing on small, verifiable wins and contributions to build confidence incrementally. Finding a mentor or supportive colleague to talk to is also crucial, as they can provide objective validation of skills and progress. Recognizing that everyone in tech is constantly learning and that having a non-traditional path provides a unique, valuable perspective helps to quiet the internal critic.