Using Nexus over the past few months, it has reached a point where I genuinely struggle to work without it.

At first, AI was a productivity boost. Now it feels more like part of my operating system. Maybe that sounds lazy. But the reality is that I’ve started relying on AI not just to work faster, but to work at the level I’ve become accustomed to.

Recently, I discovered Pi, an extendable agent harness, and decided to give it a try. It’s much more barebones compared to tools like Claude Code or Codex, but that’s also what makes it interesting. Instead of shipping with every feature built in, Pi is designed to be customized through extensions.

What’s particularly fascinating is that you can ask Pi to write those extensions for you. Which is exactly what I did to improve my workflow in Nexus.

Your own extendable AI

Pi is a coding agent similar to tools like Claude Code, Codex, or OpenCode, but what sets it apart is its ability to customize and extend itself.

You can effectively use Pi to improve Pi.

When you boot it up, it shows everything currently loaded into the harness: context files like AGENTS.md or CLAUDE.md, installed skills, and active extensions. It’s also designed to explain its own capabilities, which means you can simply ask it how to extend itself further.

Instead of adapting your workflow to the tool, you start adapting the tool to your workflow.

Memory Browser

The main use case for Nexus is storing memory files in markdown format for future reference. So the first thing I asked Pi to build was a memory browser that lets me quickly search and view memory files within the current project.

Pi already knows how to build interfaces like these and even suggested keyboard shortcuts for navigating and scrolling through markdown files. There’s also a toggle to switch between rendered view and raw markdown.

What’s interesting is how natural the process felt. Instead of hunting for plugins or writing everything manually, I simply described the workflow I wanted and Pi scaffolded the interface for me.

Tasks Manager

Next, I got Pi to build a task manager to replace the HTML dashboard from Claude CoWork’s Productivity plugin so I could quickly view and manage tasks directly inside the terminal.

It separates tasks into sections like Active, Waiting On, Someday, and Done, each accessible through tabs navigated with the left and right arrow keys.

When I toggle a task, the interface tracks pending changes and saves them automatically when I exit the task manager. Completed tasks are moved into the Done section automatically, while also triggering the memory-backup skill to commit the changes.

Individually, these sound like small quality-of-life improvements. But together, they significantly reduce friction and context switching throughout my day.

Calendar

Since I already connected Nexus to my Google Calendar, I asked Pi to build a simple calendar viewer as well.

It pulls events directly from my calendar and displays them day by day. If a meeting contains a join link, it shows that too, along with a shortcut to quickly copy it to the clipboard.

Again, this wasn’t about building a perfect calendar application. It was about extending my existing workflow in small but meaningful ways.

Log Viewer

I also got Pi to build a simple log viewer so I could quickly see changes made to my memory files over time.

It includes pagination and keeps things intentionally minimal, but that’s the point. Most of these extensions aren’t trying to become full applications. They’re small, focused tools designed to remove friction from specific parts of my workflow.

Status Indicators

Pi also allows you to customize its footer, so I asked it to display useful project information at a glance: the number of active tasks, the latest log entry, and the last time a backup was run.

It’s a tiny extension, but one that constantly keeps me aware of the current state of the project without needing to check separate dashboards or commands.

Other Extensions

Since Pi is intentionally barebones, much of its functionality comes from extensions built by the community. Here are a few others that I’ve been using:

• pi-cmux-theme-picker - Live cmux terminal theme picker
• pi-mcp-adapter - MCP (Model Context Protocol) adapter extension
• pi-rtk-optimizer - RTK command rewriting and tool output compaction extension 
• pi-setup-custom-providers - Interactive wizard to manage custom LLM providers and models

You can find more extensions in the Pi Package Catalogue.

What makes this ecosystem interesting isn’t just the extensions themselves, but how quickly new capabilities can be added. Instead of waiting for official features or software updates, the workflow becomes something you can continuously shape and evolve alongside the AI itself.

The Extension Mindset

AI brings a real shift in how you think about software. It’s no longer just a tool you use, but something you can extend and mould to your exact needs.

The interesting part is you don’t even have to build everything yourself anymore. You can rely on AI to adapt and extend itself.

You can check out the extensions I’ve built in Nexus, but the real value isn’t in copying them. It’s in building your own and extending yourself through it.

In just a few years, AI has become part of every stage of my software development workflow.

ChatGPT Deep Research agents help me explore and understand new domains. Warp.dev terminal assists in setting up and troubleshooting my coding environment. Cursor agents generate code based on plans we designed together while Claude Code double-check the results. And if I want a third opinion, I can always ask Codex.

With the release of Claude CoWork earlier this year, AI has also entered my administrative workflow.

CoWork is a more user friendly desktop app that lets you manage your files and perform simple automations. You can easily set up connectors to interact with external services like email, calendar and messaging apps.

It comes with a collection of plugins, each bundling skills and connectors designed for specific tasks. The Data plugin turns your CoWork into a data analyst capable of exploring datasets and building dashboards. The Finance plugin helps read financial statements and manage book keeping.

But the plugin that got me hooked is the Productivity plugin, which helps manage tasks, plan your day and gradually build memory and context around your work.

Supercharge your productivity with AI

When you first setup the plugin by running the /productivity:start command, it creates task and memory files along with an HTML dashboard. The dashboard visualizes your task list and provides an easy way to navigate your memory files, which is surprisingly powerful despite its simplicity.

After connecting CoWork to my email, calendar, Slack and Granola for meeting notes, I ran the /productivity:update command. It scanned my recent interactions and began tracking the projects, work streams and people I interacted with, storing them as structured memory files.

When it encounters terms that requires clarification, it prompts me to define them and saves the definition into memory. Over time, this allows the system to better understand the terminology and context specific to my work.

CoWork also supports scheduled tasks, so I created a Morning Brief automation. Each morning, it runs the update command and generates a summary of my day: upcoming meetings, items needing attention, team blockers, and sends it to myself on Slack.

What surprised me was not the automation itself, but how quickly the system began forming a working memory of my job.

Supercharge your AI with AI

CoWork plugins are essentially packages of skills designed to accomplish specific goals. The Productivity plugin includes skills for task and memory management and the start and update commands. Under the hood, these skills are simply prompts that instructs the AI what to do.

In other words, the behaviour of the assistant is not fixed. It is editable.

While you can't directly modify the plugin's built-in skill files, you can add additional instructions through scheduled tasks or your CLAUDE.md. For example, I added a preference that automatically converts blockers raised by my team into tasks.

Since Claude is also great at coding, I asked it to modify the dashboard HTML file to add features like automatic memory refresh, fix a scrollbar issue and introduce a dark mode that is easier on my eyes.

AI is no longer just a tool that improves your workflow. It is increasingly a tool that can improve itself.

I don't believe the current generation of LLMs will become sentient anytime soon. But l’m constantly surprised by what becomes possible when you simply ask AI to figure things out.

Working with AI increasingly means working through AI, alongside AI and sometimes even letting AI improve the systems that power other AI.

Doing more and more with AI

Slowly, I realized I was no longer using AI occasionally. I was delegating more and more work to it.

• Read all emails, meeting notes and conversations for a project and generate a status report.
• Locate documents sent by someone and summarize their content.
• Generate my daily standup updates and post them to my team’s Slack channel.
• Retrieve recent interactions with someone, draft a follow-up message and remind me when to send it.

None of these tasks are groundbreaking but it frees me from doing them manually. I can just ask CoWork to work on it while I focus on something else.

It makes me feel more productive, although I’m not entirely sure whether that is objectively true. I can also see how this could lead to burnout if I try to keep all my agents running at full capacity all the time.

A Day without AI

Then I got hit by the dreaded "You've hit your limit" message from Claude CoWork.

I had burned through my monthly allocation and had to wait more than a week for it to reset.

This was the moment I realized how dependent I had become on AI for organizing my daily tasks and calendar. I felt less productive and oddly annoyed doing things manually even though that was exactly how I used to work before CoWork.

It felt similar to withdrawal. I started to look for alternatives to fill this unexpected gap in my workflow. The inconvenience wasn’t technical. It was cognitive.

Replace AI with AI

I experimented around with OpenClaw and similar tools, but they felt too autonomous. Their real power comes from having full access to your computer, and I was uncomfortable granting that level of access to my work accounts.

Then I realized the plugin was really just skills plus connectors, I could port the system elsewhere.

I began moving the setup into Claude Code while using Kimi 2.5 as the model. I converted connectors like Gmail, Google Calendar and Slack into skills, then copied the task and memory management skills along with the HTML dashboard and adapted everything to work together.

It worked surprisingly well. I started improving the workflow further by adding a skill for daily sync updates and another skill that backs up memory files into Git repository for versioning.

I also moved to OpenCode, which allow me to connect to and switch between different LLM models. This means I can always keep my assistant running regardless of platform limits.

Working with Nexus

My assistant now acts as the central point of communication and holds the working context of my day-to-day activities.

This is why I named it Nexus.

Nexus is essentially a collection plugins that replicate the core functionality of CoWork's Productivity Plugin.

Workflow Skills

• work-start - Set up the productivity system by creating TASKS.md, dashboard and bootstraping memory files
• work-update - Syncs work context from external sources, manages tasks and enriches memory
• daily-sync - Collects the three daily standup updates and post them to Slack
• memory-backup - Backs up CLAUDE.md , TASKS.md and memory/ folder to a Git repository
• task-management - Provides simple task management instructions and workflows.
• memory-management - Implements a two-tier memory system: compact CLAUDE.md hot cache paired with a detailed memory/ knowledge base

Connector Skills

• gmail - Reads and searches Gmail using gog (CLI tool)
• google-calendar - Reads Google Calendar via gog
• google-drive - Reads and searches Google Drive folders and files via gog
• slack - Reads and sends Slack messages using @slack/web-api
• granola - Reads local meetings notes and transcripts
• notebooklm - Manages NotebookLM notebooks, sources, chats and generated artifacts via notebooklm-py (contributed by John)

With just a dozen skills, all of them built with the help of AI itself, I'm able to stay on top of my work while continuously improve the system through daily use.

To view the memory files on my iPhone, I sync them through iCloud Drive and open them in Obsidian. The graph view turns the memory system into something visible and navigable.

Whenever Nexus struggles to complete a task or encounters a new scenario, I simply ask it to brainstorm possible solutions, then implement the improvements together. Over time, the assistant evolves alongside my workflow.

Build your AI with AI

Nexus might not fit your workflow, but since it is ultimately just a collection of skills written in markdown files, you can easily adapt it to your own needs. You can tweak existing skills, remix them, or start from scratch by prompting AI to build the exact workflows and capabilities you want.

With free tools like OpenCode, you have access to a range of free models, so hitting usage limits is rarely a concern while experimenting. And if you don’t feel like building everything yourself, you can explore skills.sh, a directory of thousands of community-created skills that you can reuse and customize.

The barrier to building your own AI assistant is no longer technical complexity. It is simply deciding how you want to work and asking AI to help you build it. The tools exist, models are accessible, and the barrier to entry has never been lower.

If you haven’t started working with AI yet, now is the time to start building the AI that works with you. Your workflow can evolve from a series of manual tasks into a dynamic system where AI organizes, plans, and even improves itself alongside you. Working with AI is no longer just about using tools. It is about designing intelligence that evolves alongside how you work.

Don’t just use AI—build the AI that works with you.

One of the aspects of my work as an executive in Mindvalley that I’ve come to value over the years is the art of setting targets, building forecasts, and running projections to hit those numbers.

These three concepts often get mixed up, so let’s do a quick refresher on what they mean.

🎯 Target - This is the goal you set for a specific time period. For example: “Hit $1.5M in revenue by year-end.” A good target is ambitious enough to inspire action, and it gives you a benchmark for performance, motivation, and accountability.

📈 Forecast - Once you have a target, you need to continually forecast the most likely outcome based on the current data and trends. This is your best prediction of where things are heading. The more data you have, the more accurate your forecast will be.

Example based on target set above:

Target: $1,5000,000 by year end

Revenue so far (first 6 months): $600,000

Average Monthly Revenue (first 6 months): $100,000

Forecast Revenue based on current trend: $100,000 X 12 months = $1,200,000

Forecast Revenue Gap to Target: $1,500,000 - $1,200,000 = $300,000

Average Monthly Revenue for next 6 months to hit target: ($600,000 + $300,000) ÷ 6 = $150,000

From this forecast, if current trend continues, you’ll end up $300k below target. You will need to boost current monthly revenue in the second half of the year to close the gap.

🔮 Projection - This is where you create “what-if” scenarios to close the gap between the forecast and the target. Projections are not predictions, they are simulations.

Example projections to close the gap:

1) Increasing prices while maintaining current sales volume

Current Average Monthly Revenue: $100,000

Number of Customer per month: 10

Average Revenue per Customer: $100,000 ÷ 10 = $10,000

Increase price by 50% per Customer: $15,000

Projected Average Monthly Revenue: $15,000 X 10 = $150,000

2) Launching a lower-priced product to boost customer volume

Current Average Monthly Revenue: $100,000 (10 customers @ $10,000)

Lower-priced product: $5,000

Projected New Customer for Lower-priced product: 10

Projected Revenue for Lower-priced product: $5,000 X 10 = $50,000

Projected Average Monthly Revenue: $100,000 (existing) + $50,000 (lower-priced product) = $150,000

3) Opening a new channel or campaign to increase reach

Current Average Monthly Revenue: $100,000 (10 customers @ $10,000)

Projected New Customer from new campaign: 5

Projected Revenue from new campaign: $10,000 X 5 = $50,000

Projected Average Monthly Revenue: $100,000 (existing) + $50,000 (new campaign) = $150,000

Each projection explores a different path to the target. By testing multiple scenarios, you can choose the strategies with the highest likelihood of success.

A useful analogy: the target is your destination. While on the journey, your forecast is the estimate of how long it will take to get there based on current road conditions. Projections are the alternative routes you could take to arrive faster or more efficiently.

Now that we’ve clarified the difference between targets, forecasts, and projections, let’s walk through how to put them into action so you can hit and even exceed your goals.

Start looking at your numbers

It sounds obvious, but the first step is to truly know your numbers. Whether you’re trying to grow business revenue, lose weight, or save more money, you can’t start improving until you know exactly where you stand and where to find that information.

Get into the habit of reviewing these numbers regularly. At Mindvalley, I set up our reporting system so company revenue figures arrived in my inbox every morning. As the saying goes, you can’t improve what you don’t measure.

If you’re unsure which numbers matter most, start with the ones directly tied to your targets. These are your performance yardsticks, showing whether you’re getting closer to your goal or drifting off course.

Dig deeper into your numbers

Topline figures like total revenue or total sales are a good starting point, but they rarely tell the whole story. To understand what’s really happening, break your numbers down and see how different parts of the business connect.

In a subscription business, for example, total revenue comes from two streams: new subscription revenue and recurring revenue from existing customers. New subscription revenue might be influenced by your customer acquisition cost, while recurring revenue depends heavily on retention rates.

By segmenting, dissecting, and looking for patterns in your data, you’ll get a clearer picture of current trends. The more granular your view, the more accurate your forecasts will be and the more confident you’ll feel in making decisions.

Understand what drives your numbers

Once you’ve broken your numbers down, focus on the levers that have the biggest impact. These are the variables that, when changed, can significantly move your results for better or worse.

In a sales-driven business, this might be lead volume, conversion rate, and average order value. In a subscription business, it could be acquisition cost, churn rate, and customer lifetime value. Knowing these drivers means you can forecast with greater accuracy and design projections that directly address your gaps.

By identifying the metrics with the highest leverage, you can focus your energy on the initiatives and strategies most likely to achieve your goals instead of spreading effort across less impactful areas.

Run your numbers

The entire point of understanding your numbers is to help you achieve the targets you set. Clearer numbers give you better visibility on where you stand right now. A deeper understanding lets you forecast more accurately, and knowing the levers with the biggest impact helps you build stronger projections toward your target.

Run through the steps below to continuously move closer to your goal.

1. Review your numbers to see where you stand
2. Forecast the likely outcome based on current performance
3. Project scenarios to improve that outcome
4. Act on the most promising scenarios
5. Repeat as new data comes in

This decision-making loop keeps your strategy grounded in reality while giving you the agility to adjust quickly, incorporating feedback from each action and refining your approach until you reach (or exceed) your target.

But as powerful as it is, numbers alone can't tell you everything, which is why the next step is to look beyond them.

Go beyond your numbers

Numbers are powerful, but they're not the whole picture. They may tell you what's happening, but not always why it's happening or what's about to change. They give you a window into your business but it shouldn’t be the only one you look through.

You can’t run a business by living inside a spreadsheet. Targets, forecasts, and projections all rely on numbers, but they also need the context that numbers alone can’t capture. Market shifts, team morale, competitive moves, and customer sentiment can all shape your outcomes in ways your data may not yet reflect.

Use your numbers as a solid foundation, then layer on real-world observation, conversations, experience, intuition and market awareness. This balance of data and unique context is what transforms raw figures into a strategy that actually works.

And while targets, forecasts, and projections are often tied to business performance, their value reaches far beyond the spreadsheet. You can apply the same thinking to personal goals, creative pursuits, or any situation where you want to turn intentions into results.

The process stays the same, set a clear target, forecast your likely outcome, and explore projections to bridge the gap but the magic happens when you pair these tools with real-world context, lived experience, and an understanding of the human factors at play.

That’s when numbers stop being just data points and start becoming the backbone of strategies that truly deliver. In the end, it’s not just about hitting the numbers, it’s about using them to create results that matter.

Twelve years ago, my co-founder John and I joined Mindvalley after years of building products for other startups through our software consultancy, Flexnode. We were builders at heart but we wanted to go deeper. We didn’t just want to launch things, we wanted to grow them. We wanted to experience the full arc of what it meant to take something from idea to impact.

What began as a two-person team in a small office in Kota Kinabalu became a journey of scaling products, people, platforms but also scaling up in a more personal sense. Mindvalley is a personal growth company, and in many ways, my 12 years there were as much about growth as they were about building. I went from writing code to leading teams, from managing systems to managing myself.

Here are some of the things I built and how they built me back.

Building Products

The first product we worked on was the web version of Omvana, a meditation app. Not long after, we shifted our focus to Quests, which would go on to power the core learning experience on Mindvalley.

What quickly became clear was this, a product’s success depends on much more than clean code or great design. It has to work across the entire company. Content teams needed intuitive tools to manage and structure learning materials. The marketing team needed ways to track, test, and iterate on messaging and funnels. Customer support needed the ability to assist users quickly when things broke.

Building a product meant building with others. It required deep cross-functional collaboration and a shared understanding that everyone played a role in the user experience.

And the work didn’t stop at launch, in many ways, that was just the beginning. What followed were countless cycles of iteration, improvement, and learning. That experience shaped how I think about product development to this day, not as a one-time act of creation, but as an ongoing commitment to service and evolution.

Building a Team

As our workload grew, we decided to expand the team in Kota Kinabalu. We reached out to people we’d worked with before and gradually assembled a small but capable group to join us.

This was my first real experience as a manager. And like many first-time leaders, I had to make a shift from getting things done myself to achieving results through others. It wasn’t easy. The urge to jump in and solve problems directly was strong. But I knew my real job was to create the conditions for the team to succeed without needing me in the loop for everything.

Over time, we developed a few principles to guide how we worked together:

• We are here to serve
• We communicate often and intentionally
• We constantly adapt and learn new things
• We bring out the best in each other.

To reinforce these values, I occasionally wrote internal emails to the team. Some of them ended up becoming shared reference points for how we work and grow together. A few of those titles still make me smile:

• An Unexpected Journey
• There and back again
• The Never-ending Quest

Building a team, I realized, isn’t about assembling talent. It’s about building a shared culture, a common language, and a foundation of trust. And it’s one of the most rewarding things I’ve ever done.

Building an Office

With a bigger team, moving into a larger space became a natural next step. We looked to the Mindvalley headquarters in Kuala Lumpur as inspiration—an award-winning workplace that hosted events, sparked collaboration, and reflected the company’s energy. We wanted to bring a slice of that to Kota Kinabalu.

Our version had to be built for a team of engineers. That meant desks with dual monitors, chairs with proper lumbar support, and writing surfaces everywhere. We also included a projector and a large open area, not just for team gatherings, but to host events and community meetups.

Over the years, the office became more than a place to work, it became a hub. We hosted events like WebCamp KK for years, welcoming local developers, students, and tech enthusiasts. Every now and then, colleagues from other parts of Mindvalley would drop by while visiting the region. The space helped us stay connected not just with each other, but with the broader ecosystem.

We also kept things simple. With a small team and minimal admin overhead, we treated the office like a second home. Everyone pitched in to take care of it. Ten years later, I’m proud to say it still looks and feels just as good as the day we moved in.

Building a Division

Eventually, I was given the opportunity to step into the role of CTO and it turned out to be one of the biggest challenges of my career. Not just technically, but personally.

Scaling products and platforms is hard. Scaling people is harder. But scaling yourself, your mindset, your leadership style, your emotional bandwidth. That’s a whole other level. When the stakes are high, it’s hard not to second-guess yourself. Imposter syndrome has a way of showing up, especially when everyone’s looking to you for answers you may not yet have.

As an engineer, I used to think in terms of designing systems to meet clear requirements. But leadership doesn’t work like that. When the “systems” you’re building (hiring frameworks, performance reviews, or team structures) directly affect people’s careers and well-being, the job starts to feel a lot heavier. That’s when I began to understand the real weight of leadership. And the importance of empathy.

This chapter wasn’t smooth sailing. There were moments I thought I finally had things under control only for everything to shift again. Priorities changed. People moved on. New challenges emerged. I learned to stop expecting stability and started focusing on adaptability. Progress wasn’t about perfection. It was about continually pushing to make things a little better than they were yesterday.

Looking back, the most valuable lessons weren’t in strategy or systems. They were in staying grounded, listening better, and learning to lead in uncertainty.

Building Myself

One of the most important steps in my growth at Mindvalley was choosing to step down from the CTO role. As someone in that position for the first time, I knew I had a lot more to gain by having someone more experienced step in, someone I could learn from.

That transition gave me the space to strengthen my foundations in other areas of the company, like strategy, finance, and data. I started to connect the dots across teams and understand how value gets created beyond just tech. It gave me a much deeper appreciation for how the business truly works.

It also helped me reconnect with curiosity. I could explore questions I never had time for before, and learn without the pressure of needing to have all the answers. Over time, I developed a greater respect for the work being done across different divisions.

In hindsight, everything I helped build at Mindvalley (products, teams, an office, a division) was also building me. Not just as a technologist, but as a leader, a teammate, and a human being.

Twelve years at Mindvalley taught me that building and growing are deeply connected. When you build with purpose, you grow. And when you grow, you don’t just build better products, you build stronger relationships, a more thoughtful culture, and meaningful impact.

To everyone I worked with along the way: thank you. You challenged me, inspired me, and helped shape a better version of who I am today.

Let this be a reminder to myself:

Never stop building.

During dinner, my daughter said she was feeling cold. The first thought that popped into my head: Is she having a fever? I reached for the thermometer, hoping it was nothing but also mentally preparing myself for a potentially long night ahead.

This is a familiar scene for parents with young kids. You've got the paracetamol, blankets and cold patches ready. You check temperatures hourly, make sure they're properly insulated, all while keeping your own anxiety in check.

As her temperature started to climb, we gently tried to convince her to take some meds and place a cold patch on her forehead. Like always, it took some negotiation. At one point, I even showed her the thermometer as proof she was, in fact, having a fever.

Then came a question that is simple, honest and surprisingly profound:

“If I’m getting hotter, why do I feel cold?”

I paused for a moment and thought to myself: Why do we shiver when we’re burning up on the inside?

The balancing act

We have a fever because our body raises its internal temperature set point to help fight off infection. The higher temperature creates a more hostile environment for invading pathogens and gives our immune system a better chance to turn the tide.

The side effect of this shift is that everything around us suddenly feels colder by comparison.

We shiver not because our body temperature is low, but because the body thinks it needs to get even hotter to reach its new internal target. It’s trying to find equilibrium, but that balance keeps shifting as the battle rages inside.

It's all relative

This constant push for alignment between our internal state and external environment goes far beyond body temperature. It also affects us mentally, emotionally, and behaviorally, depending on the context we’re in.

Spend time with people who are getting by with very little, and you may feel grateful and fortunate for what you have. But surround yourself with millionaires spending freely on luxuries, and suddenly your own life can feel inadequate or unfair.

How we feel often has less to do with our actual circumstances, and more to do with how we compare ourselves to those around us. Our expectations shift in response to our environment, just like how our body responds to a new set point during a fever.

Curate your Environment

We can leverage this innate drive to reach parity with our environment by carefully curating where we spend our time and who we spend it with.

If you want to be more disciplined, surround yourself with people who hold themselves to high standards. You’ll naturally begin to adopt their habits as you strive to align with them.

If you’re trying to save money, spend time with people who live below their means. Frugality will start to feel normal, not restrictive.

If you want to take more risks, step into rooms where action is the default, where people are building, experimenting, and starting things. Soon, hesitation will feel out of place.

And if you feel demotivated or uninspired, take a hard look at your surroundings. Are the people around you encouraging and driven? Or are they stuck in the same patterns you’re trying to escape?

Change your Environment, Change your Life

The environment around you isn't just background noise. It's more like a thermostat. It sets the boundaries of what you see as normal and what you believe is possible.

When willpower alone isn't enough to push you forward, change your environment. Tip the balance in your favor by surrounding yourself with people and places that reflect the version of you that you're striving to become.

The next time my daughter has a fever, which I hope it's not anytime soon, I'll know the answer to both her question and a deeper one about growth:

How we feel and how we act are often less about what’s happening inside us, and more about the world we’re reacting to.

Just as we manage her temperature by adjusting her environment with cold patches and blankets, we too must shape the environments we live in to give ourselves the best chance to thrive.

In an age of side hustles and self-optimization, it seems like everyone is trying to squeeze the most out of their time. Every spare hour is a potential project, every weekend a chance to build, learn, or monetize. Rest is allowed, but only if it’s “productive” rest.

So when I look at how I’ve spent my own free time, I can’t help but feel a little uneasy. I haven’t started a new project. I haven’t chased the next big goal. And compared to the noise around me, it’s easy to feel like I’ve somehow fallen behind or missed out.

That discomfort led me to wonder: How do we actually know if our time is well spent? Do we judge it by what we manage to get done, or whether we hit the goals we set for ourselves? Or maybe by how we felt while hustling to make the best out of our time?

And perhaps the hardest part is, we only ever seem to know in hindsight.

More Output, More Utilization

The most obvious and most common way to determine whether we’ve used our time well is to measure its output. The more we get done, the better we assume we’ve spent those precious moments of free time.

There’s no denying the satisfaction of checking off tasks one by one. It gives us a clear sense of progress, a feeling that we’re moving forward. Surely that means we’ve made the most of our time by being productive, powering through an endless list of to-dos, chores, and goals.

But if you take a step back, you start to realize this isn’t so different from doing busy work. Filling your schedule doesn’t necessarily mean you’re using your time well. You can pour hours and energy into activities that ultimately lead nowhere, productive on the surface, but empty underneath.

It’s All About the Outcome

Getting things done is just a means to an end. The deeper question is whether those efforts actually led to the outcome you were aiming for. So maybe a better way to judge how we spend our time is by looking at what we achieved, not just what we did.

Instead of focusing on everything that happened over the weekend, maybe it’s more useful to ask: Did I reach the destination I set for myself before I began?

Rather than chasing productivity for its own sake, it feels more meaningful to work toward a goal and measure your time against that. At least then, your effort has direction. There’s a sense of progress, of purpose.

But that approach assumes you actually know what you want. And often, the goals we chase aren’t truly our own. They’re borrowed from expectations, trends, or other people’s definitions of success. You can reach the finish line and still feel empty, realizing too late that it was never a destination you cared about in the first place.

Orientation is Key

Perhaps it’s worth putting more thought into why we do the things we do. Do we really need to start that side project? Must we dedicate time and energy to pursue a goal we forget the moment we achieve it?  Maybe what we need first is to orient our intentions, to make sure our outcomes and outputs are aligned with what we truly desire.

Before we get pulled into the motion of constant doing, it’s wise to pause and ask: What am I actually after? Do you want to be busy and productive, or do you want to achieve results that genuinely mean something to you?

Time spent orienting—realigning your direction—is never wasted. It’s how you make sure your effort is pointed toward what matters. Moving slowly in the right direction is far better than racing forward with no idea where you’re going.

Once you orient yourself toward what truly matters, you can start defining the outcomes that align with those values and direct your output toward achieving results that actually mean something to you.

Maybe It's the Wrong Question

Looking back, maybe the entire notion of needing to spend time well is the real problem. We carry this unspoken pressure to be productive, as if time is only valuable when it’s optimized. Because it’s precious, we feel we must manage it like a resource, tracked and accounted for.

But maybe what really matters isn’t how well you spent your time, but how closely your life aligns with what you truly care about. And if that means doing nothing for a while, then maybe that, too, is time well spent.

In another life, my Friday nights were spent battling mystical monsters and casting arcane spells. Magic: The Gathering (MTG) is a collectible card game where you play as a powerful wizard, dueling opponents with a deck full of spells, creatures, and enchanted artifacts.

Deck-building is a core part of the game — it shapes the strategies you can use to defeat your opponent. In my quest to stack the odds in my favor, I came across a concept that stuck with me: the idea of Win More cards.

Since you have limited resources to play cards each turn, every card in your deck needs to matter. Ideally, you want cards that help you advance your position — whether you’re behind, at parity, or ahead.

Win More cards are the ones that only shine when you’re already winning. When you’ve got your opponent on the ropes — more creatures, more resources, more control — these cards help you press the advantage and overwhelm.

That might sound great (and it can lead to flashy, satisfying victories), but in most games, these cards are dead weight when the match is close or you’re struggling. They don’t help you stabilize or recover — and drawing one in a tight spot can cost you the game.

Because your deck has limited slots, competitive players learn to avoid Win More cards. Instead, they prioritize cards that are useful in any situation — not just the easy ones.

The more I played, the more this idea stuck with me — and not just in games. Win More thinking shows up in business too. These are the strategies, decisions, or investments that look impressive when everything is going well, but fall flat (or even backfire) when times get tough.

Just like in MTG, resources in business are limited — time, budget, energy, talent. So the strategies you choose need to help you whether you’re scaling up, holding steady, or clawing your way back from a rough quarter. The flashiest moves aren’t always the smartest ones.

Win More Strategies in Business

A classic example is over-investing in brand polish or premium PR when core operations aren’t solid. It’s like launching a slick new ad campaign or hiring a high-profile spokesperson — while your product is still buggy, or customer service is a mess.

Sure, when you’re already winning, this kind of flex can amplify momentum. But if you’re struggling to retain customers or meet demand, it doesn’t help — and can even backfire by raising expectations you can’t deliver on.

Another common move is when a business scales aggressively before truly nailing product-market fit. They hire fast, expand to new markets, or burn capital to “blitzscale.”

It works beautifully when demand is real and consistent — but if the foundation isn’t steady, you’re left with high burn, a bloated org, and not enough traction to justify the size.

Then there are businesses who focus on chasing vanity metrics — social media followers, press mentions and app downloads. These numbers look good, but don't necessarily translate to revenue, retention or product-market fit.

It's easy to celebrate when you're are on a roll, but when things get tight, they offer zero strategic value. You can't pay salaries with TikTok views or Facebook likes.

When things are going well, there’s often a temptation to over-engineer — to add more features, more tools, more complexity. But feature creep leads to bloated products that confuse customers, slow down development, and distract from what actually drives value.

Like Win More cards, these extra features are often beloved by internal teams or power users — but they don’t help you win new customers, and they won’t save you in a downturn. You’re better off with a lean, reliable deck than one packed with flashy, situational spells that only shine in ideal conditions.

Build a Resilient Strategy — in Games and Business

In Magic: The Gathering, the best players learn to build decks that can handle any board state — not just the easy ones. They avoid Win More cards in favor of those that offer flexibility, consistency, and impact whether they’re ahead or behind.

The same logic applies to business strategy. It’s tempting to pursue big, flashy moves that look great when things are going your way. But true resilience comes from focusing on what works in the messy middle — when growth stalls, competition heats up, or the market turns.

In the end, it’s not about playing to win more — it’s about playing to win no matter what. Flashy strategies might get the spotlight, but it’s the reliable plays — the gritty, unsexy ones that hold under pressure — that actually win the game.

Strong fundamentals like efficient operations, great customer service, and disciplined cost management may not be glamorous, but they’re the bedrock of every successful company.

So whether you’re building a deck or a business, ask yourself: Will this help when I’m behind? Or is it just for show when I’m ahead?

Take a moment to evaluate your current strategies. Are they built for resilience, or are they 'Win More' plays? What 'gritty, unsexy' plays can you double down on today?

Because when the game — or your business — is on the line, Win More won’t save you, but a solid foundation will.

Ever since I started being more mindful about what I eat and tracking my calorie intake, I realized the typical portions served by most restaurants aren't ideal for me.

In Malaysia, typical meals tend to be higher in carbohydrates and lower in fiber, unless you’re having a salad. If you’re on a high-protein diet like Keto or Paleo, most meals won’t have enough protein unless you order something like a steak.

This led me to some rather creative (for me) yet puzzling (for the restaurant) customizations to get the right balance of macros. I've ordered meals without rice or noodles, shared an extra portion of meat with a friend or even pieced together different dishes.

All this, however, comes at a cost. My meals are more expensive, and if the restaurant doesn't allow any tweaks, I may end up wasting food. It got me thinking —who decides the portions of these meals in the first place?

The Restaurant Decides

The obvious answer is the restaurant serving the meal. Based on their menu design, cuisine style, chef expertise and customer feedback, they determine portions that satisfy both their customers’ taste buds and their bottom line.

If I wanted the perfect ratio of protein, fat, fiber, and carbohydrates on my plate, all I’d need to do is dine at restaurants that cater to my diet. But as a Malaysian, limiting myself to a single restaurant, cuisine, or style just feels wrong.

That said, the puzzle of portion sizes extends beyond restaurants. After all, they are businesses trying to turn a profit and are not immune to the hidden hand of the market.

The Market Decides

How much you pay for a meal is ultimately driven by the unit economics of the restaurant. The cost of ingredients, rent, and staff salaries all influence both the portion size and the price of each dish.

When the restaurant across the street decides to offer more for less, it creates pressure for others to follow suit. Everyone is trying to strike the right balance between price and portion to attract the ‘average consumer’—a consumer who, in reality, doesn’t really exist.

On top of that, government policies can influence portion sizes too. Subsidies that favor certain ingredients distort the economic logic behind what ends up on your plate. So, is it really the government and the market that decide your portion?

You Decide

By now, you’ve probably realized this isn’t really about how much carbs or protein you get in a meal. It’s about how we often assume the portion served to us is the right one—without question. We’ve effectively outsourced that decision to others, trusting that they have our best interests in mind.

The reason most meals are heavy on carbohydrates is simple: carbs are more economical than meat. Assuming meals should be carb-heavy just because that’s what’s typically offered is doing yourself a disservice. At the very least, you should understand why things are the way they are.

And this mindset applies far beyond food. The salary you’re offered for a new job. The quote you receive for a paint job. Even the rate you set for your own services. It’s worth pausing to examine the assumptions behind these numbers. Who decided what’s “right”? And is it right for you?

So the next time you sit down for a meal, ask yourself what you actually want from it. Don’t take it for granted. Don’t blindly accept what’s offered.

Control your portion, control your life.

Every other day, new AI tools are launched, threatening to replace existing jobs and disrupt entire industries. The pace of innovation is relentless, and in fields like software development, AI is no longer optional but a necessity.

To remain relevant in a world increasingly shaped by AI, focus on these key principles that emphasize our uniquely human strengths while strategically leveraging the power of artificial intelligence.

Understand your value

A software developer writes code to build a product, just as a marketer launches a campaign to drive conversion. The true value lies not in the output itself but in the impact it creates.

It’s a common misconception to think you’re hired to complete tasks. In reality, your work is simply a means to achieve the results your organization values. Those who understand what truly drives outcomes will make greater impact and achieve long-term success.

Position yourself higher in the value creation chain to drive better outcomes. Your value comes from shaping the input (deciding what to do), not just in producing the output (executing tasks).

Redefine your work

Some–if not all–of the tasks you perform today could soon be handled by AI. Rather than seeing this as a threat, embrace this as an opportunity to reinvent your role.

New technologies and innovations create new careers and job opportunities, but many of these are evolutions of existing roles, now infused with AI. Reassess aspects of your work that benefit from the capabilities of AI while doubling down on the uniquely human strengths that set you apart.

Start integrating AI into your workflow to improve productivity and shift your focus to higher-value tasks to stay ahead of the curve. The future of work is AI-assisted, not AI-driven.

Sharpen your communication

AI may operate at the speed of light, but your effectiveness is limited by the speed of your thoughts. To get the most out of AI, you must be clear about the results you want. After all, the quality of AI’s output is only as good as your input.

Mastering prompt engineering is just as important as honing your interpersonal skills. You won’t just interact with AI or humans—you’ll navigate a world of AI-assisted humans and human-guided AI.

Clarity of thought is the key to unlocking AI's full potential. Whether you are working with people or AI, clear and concise communication is an essential skill.

Preserve your critical thinking

AI can retain and process information on an exponentially greater scale than humans. It's tempting to let it do all the thinking and reasoning while we passively and blindly accept its output.

Large Language Models may possess vast knowledge across countless fields, but true understanding requires human context and nuance. To guard against AI hallucination and sift through the vast amount of AI slop, we must apply critical thinking more than ever.

We must retain our agency by ensuring AI serves us, not the other way around. Use AI to enhance your reasoning, not replace it.

While we can’t predict how AI will shape the future of work, we have the power to ensure it remains meaningful and fulfilling. Focus on where you add the most value, leverage AI to boost productivity, refine your communication skills and maintain a critical perspective.

It’s been a while since I last wrote here. Given that I finally entered the 4th decade of my life here on earth, I figured it’s the perfect excuse to share some things I learned along the way. Rather than boring you with a list of 40 items, I’ll just share 4 insights that have served me well throughout the years.

1. Consistency is Everything

Practically every sort of meaningful achievements, notable successes or worthwhile endeavours in my life were the results of being consistent. It’s about showing up every single day whether you feel like it or not. It’s a cliche but it works.

Whether it’s about losing weight, accumulating wealth or just mastering a skill, the one true way up the treacherous mountain to reach the elusive summit is through the endless torture of repeatedly putting one foot in front of the other even when there’s a unrelenting fog concealing the path forward.

And of course it works the other way round too. Since I have not been consistently writing here, there’s probably not many of you who will be reading these words. You reap what you sow.

2. Learning never stops

Learning is a big part of my life given that I work for a edu-tech company (Mindvalley) and I have written some thoughts about it in the past. I don’t have any mind-shattering insights other than the fact we should continue to learn and up-level all aspects of our lives.

There are many ways to learn. You could read a book, experiencing something novel, watch a YouTube video or while grabbing a coffee with a friend. The act of reading this article itself could be a form of learning, which I hope there’s a gem or two here for you to learn from.

Try to cast a wide net for the topics you wish to be enlighten in. Put yourself in unfamiliar settings to benefit from serendipitous encounters. The best type of learning in life are those unexpected revelations gained from seemingly unrelated circumstances.

3. Say NO more often

When you are young, your parents, family or friends may have told you that you can do anything as long as you put in the effort and pay your dues. They left out one very important detail. You can only really realize a handful of your ambitions due to limited time and resources.

This means you actually have to say no to things way more than you would like to. I’m not talking about rejecting things you didn’t want to do anyway but rather really prioritizing and accept you can only realistically pursue a limited amount of goals.

There are stories of people who seem to be able to find success in drastically different fields and expertise but I would argue they actually focus on their core strengths and skilfully leverage them across many disciplines.

4. Balance is hard, really really hard

Trying to strike a balance between consistently going to gym few times a week, eating well most of the time, being there for my family and providing for them is really really hard. I strive to live a balanced life which requires constant effort and attention to keep things in check.

It may seem like I’m trying to have my cake and eat it too by balancing between various aspects of my life. The truth is that I have to learn to sometimes accept a smaller cake and not every piece of it will be palatable.

A balanced life isn’t a goal that you achieve after putting a lot of hard work and sacrifice. Rather it’s a state that you need to actively and continuously maintain like how you need to constantly shift your body weight and arms to stay upright on a unicycle. It also serves as a constant reminder that I shouldn’t go overboard pursuing something else I risk affecting other parts of my life.

Last month, I was invited by a local university (UMS) to give a talk to their students about what’s it like being in the Tech industry. I decided to share 10 insights that hopefully can help them navigate their first step into their Tech career.

1. Pay & Salary in Tech

You might have noticed that the salary range in tech industry varies quite a bit and this is influenced by the technology stack, experience and expertise required for the role. Certain skills and expertise are more sought after, thus commanding a premium. Some roles may include leadership or management responsibilities.

2. Your Value depends on the Company

Ultimately, your value will be a function of the company’s business model and your contribution. If you join a Tech company, you’ll be able to directly impact the business vs joining a non Tech company where you help improve efficiency and operations. In most cases, you get paid more when you help generate more revenue vs saving costs.

3. It’s not all about code

A common misconception is that a tech career revolve around coding and programming. This is not true and even Software Engineers spent a lot of their time doing non-coding things like documentation, meetings, collaboration and waiting.

There are also many types of roles in companies that benefits from your technical know-how. You can go into Product, Operations, Security, Data and Infrastructure just to name a few. Other than your technical skills, don’t neglect “soft” skills like communication, collaboration and leadership which are just as important.

4. Many paths to specialize

Even if you prefer to focus on coding, there are many options to choose from as technology is ever evolving. You could progress by staying on the Technical track as an individual contributor or switching over to the Management track to manage teams and departments.

5. It’s all about teamwork

In Tech, most of us will be working in a team and it may consists of people from different expertise and skill sets. These cross-functional teams tend to work better as it brings different perspectives to the table and reduce dependencies needed to get things done. Even if you do happen to work alone, always consider your superior / manager as part of your team and stay aligned.

6. Working Styles

You’ll also be introduced to concepts like Agile, Scrum and Kanban (most likely all 3), which are different ways of working together and getting things done. The idea of these frameworks are to help us adapt to change and scale up.

7. Constant Learning

With software eating the world, every company is a tech company. Coupled with consumer expectations of relentless new technological advancement, a career in tech requires you to accept that learning is the only constant. Never stop learning.

8. Priorities

Since everyone is expecting something new from tech, there will always be conflicting priorities to work on. Stay flexible, adaptable and agile. Keeping everyone on the same page will go a long way in staying aligned towards the goal.

9. It will be challenging

Almost everything in tech goes through the Hype Cycle and contributes to the struggles of the industry. Every new breakthrough goes through a cycle of inflated expectations and disillusionment before settling down. It’s very easy to get caught up with all the shiny things and drink the kool-aid.

10. Outsized Impact

Despite everything, technology have the potential to solve humanity’s biggest crisis like the climate/energy crisis. It could also help us undo the looming mental health crisis, which were caused by technology to a certain extent. If you are looking to make an impact in this world, a career in technology is one you should consider.

Working on a product is something I truly enjoy. It’s a multi-disciplinary effort juggling between technology, design and business. You have to approach things from different perspectives and when everything aligns, you’ll create something extremely valuable.

If you have attended any hackathons or business pitching competitions, you might have been introduced to the Business Model Canvas. It’s a tool to help you structure and design your startup’s business model.

It’s a powerful tool and quite often (if you do it right) you’ll discover some interesting insights about your startup. However, as pointed out by Steve Blank, it’s great for brainstorming hypotheses, but it doesn’t have much guidance in testing them.

This lead to the creation of the Lean Canvas, a variation that focuses on the problems, solutions, key metrics and competitive advantages, allowing you to deconstruct your idea into its key assumptions.

These tools have help me developed multiple products in the past (mostly failed but that’s on me not the canvas) so they definitely served their purpose. However, I’m not a big fan of the canvas format as it’s actually harder to use and maintain.

From advising and consulting first-time founders and entrepreneurs, I’ve also noticed quite a few of them struggled with the canvas as they tend to get lost trying to think about all the different aspects of their startup. Coupled with the fact that I also tend to give them pretty much the same advice at the start (focus on customer discovery first), I figured maybe there’s a better way.

So a few weeks ago, I wrote down all the usual questions I used to advice these entrepreneurs and developed a guide. It’s an action plan that walks you through the customer discovery, solution design, product iteration, product marketing and product-market fit phase of your startup.

Each step contains 4 questions and a checklist at the end. It’s designed to be answered linearly but you are encouraged to go back to previous answers and update them as you work your way down the list. Building a startup is an iterative process and you should be updating your business model and assumptions along the way.

I’ve built the MVP version of this guide on Notion.so. It’s a free tool that allows you to create powerful documents with tables and checklist. It also have a simple way for anyone to duplicate the guide for their own use.

Having used the same steps in the guide on itself and testing with a few dozen entrepreneurs, I’ve some early indicators that this might be useful. Obviously it’s still in very early stage but if you want to give it a try, please visit startupcompass.io and subscribe. I’ll email you the free template and any future updates. Hopefully, this will eventually be another resource to help entrepreneurs and founders build their product and startup.

Almost a decade ago, Marc Andreessen penned the famous “Why Software is Eating the World” essay which was amazingly prescient. His arguments on why every company needs to be a software company becomes even more evident in our post-COVID-19 reality where companies like Amazon, UberEats and DoorDash are now considered essential services.

While I was mapping out the concepts around building software, I noticed a recurring theme across the world of bits and bytes. Almost everything is an abstraction of something else and this I believe, is the reason why software is bound to permeate across every aspect of our lives.

In simple terms, abstraction allows us to ignore certain details to focus on those that we care about. An abstract version of a cat has just enough characteristics (the ears, the whiskers, the body shape etc) for us to still recognize it without being distracted by other less important details.

Similarly, in the world of software and code, you’ll see this pattern repeated over and over again. Assembly language, which is an abstraction of the underlying machine code instructions, is then abstracted by higher-level languages with easier-to-use constructs to encapsulate away the architectural details of the physical microprocessor.

Libraries, packages, frameworks and APIs provide useful abstraction for all sort of capabilities in all sort of domains. There’s also Declarative programming, a paradigm that shifts a software engineer’s focus towards the outcome rather than the steps to achieve it, abstracting the work to the language itself.

Cloud computing which has abstracted the notion of physical servers using virtualisation and containers, is abstracted further by the rise of Infrastructure-as-Code (IaC) allowing your entire cloud infrastructure be managed and provisioned through configuration files. Serverless computing then took it a step further by abstracting away infrastructure concerns so you can focus only on your code.

Even application development isn’t spared, with the No-code movement continuing to gain traction. You can leverage these tools to quickly string together a working application without writing a single line of code.

This isn’t just limited to software development by any means. Uber and Lyft turned the act of hailing a cab into an app, abstracting away the complex orchestration between logistics, scheduling and payments. With just a few clicks, you can get someone to mow your lawn, stock up on groceries and even ensure you have a lifetime supply of socks.

Software companies innately understands the power of abstraction. It allows them to hyper focus on their particular problem domain while leveraging existing technologies and services. Internally, cross-functional autonomous teams are assembled to focus on a particular subset of the problem domain, with the aim of unlocking value that’s greater than the sum of its parts.

Once they themselves are successful, they will then become the abstraction layer of that domain for others to build on. With this moat, they then expand to tackle adjacent problems while fortifying their foothold. This is also why we have startups raising millions of dollars trying solve problems that seems too narrow to the uninitiated.

As consumers, we too reward companies who are able to solve our problems with as little effort from our side, abstracting away all the complexities. Startups in early stages quite often deliver seemingly magical experiences backed by manual work, hoping to eventually codify the process if there’s a product-market fit.

The unintended consequence for turning everything into black boxes is the unfortunate exploitation of the marginalised. Opaque machine learning algorithms turn human labour into variables to be optimized and scrutinized. In fact, in a lot of cases, the existence of a human workforce is merely a placeholder that will eventually be replaced by robots, improving operating margins and efficiency.

Abstraction is a double-edge sword that if wielded wisely, let us solve difficult problems, by focusing our efforts and leveraging each other. At the same time, we need to be mindful the potential ill effects of ignoring certain details, especially when it impacts our livelihood.

Software is supposed to be the great leveller, levelling the playing field for everyone. But if we are not careful, it might end up levelling humanity off the field altogether.

Ever since I discovered Foam, I was waiting an opportunity to try it out. It’s a personal knowledge management and sharing system inspired by Roam Research, built on Visual Studio Code and GitHub. It fits nicely into my development workflow, so that’s a plus.

Over the weekend, I attempted to build a personal workspace on Foam. Currently I’m using Notion.so for my notes, journals and personal information. The Graph Visualisation in Foam (screenshot below) is the main feature I wanted to explore.

Originally, I attempted to reproduce what I have on Notion but soon realised there really isn’t much links between my information there. Then I decided to document my recent learnings from work around cloud computing, infrastructure and data architecture.

Linking Concepts

As I started to link notes between various concepts, I realised there are many more in software development in general. What started from just cloud computing and data architecture, ends up covering software architecture, development, engineering, product development and even machine learning.

These concepts are by no means the only one that matters. It’s mostly from my own experience and I’m sure there are a lot more out there to be discovered. But this is a good starting point to see how things are inter-related and realised software development is actually quite complicated.

Publish and Share

Since Foam uses GitHub as storage, it takes almost no effort to publish the workspace on GitHub Pages. Combined with the awesome Just the Doc theme, the whole project looks really great online.

I’ve also started to share this with my team and got lots of great feedback on what concepts I missed and how to use it in general. It can serve as a guide for their career growth in their respective areas.

If you are a software engineer or interested in some of these topics, check out the site at https://tslim.github.io/concepts. You are also welcomed to contribute more notes and concepts at the repo.

Ever since the Alpha release, I’ve been focusing on making it easier for users to get started. Matrices can now be shared, cloned and user can also browse the template directory for pre-made matrices.

However, there is still one obvious barrier that I’ve been ignoring from the very beginning. In order to build and edit a decision matrix, you must sign up for an account first. If I wanted anyone to be able to quickly get started, the app will need to support the ability for guest to create and edit a matrix.

Guest Mode

I built this app like a normal web application and assumed that users would want to save decision matrices in their account as reference. Even though this assumption might be true, I didn’t consider the use-case where someone may just want to quickly build a matrix without signing up.

After hearing this feedback from a few users, I decided to look into enabling Guest mode where you can basically try out the main functionality of the application without logging in. I chose to leverage the existing capability to share a matrix to the public as the basis of this feature.

Before Guest Mode, you can share a matrix publicly but it’s read-only for obvious reasons. Now I added the ability to also allow the same publicly shared matrix to be editable by anyone. This approach allows me to tackle a few features all at once.

Firstly, a guest (non logged-in user) will be able to create a new decision matrix, use a template or make a copy from a publicly shared matrix without an account. The matrix will basically be in the public and editable mode where they can then save to their account (after they signed up), if they choose to do so.

I’ve also updated the green bar on top of the matrix to reflect the current permission level and guide guest on how to save it if they want to keep the matrix for future use.

Collaboration On!

Secondly, because the matrix in this mode is basically publicly editable, it opens up the possibility of collaborating with other users. By sharing the link with others, you can basically collaborate on a matrix together.

This means not only the matrix created by a guest can be collaborated on by others. It also applies to any matrix you have in your account. Just click Share, make the decision public and allow anyone to edit the matrix. Of course, only share the link to the matrix with people you intend collaborate with.

Tracking user activity on the matrix

With collaboration enabled, I figured it’s a good idea to be able to track the activity of each collaborator in real-time. The ability to see others focus on the matrix will help guide discussion and make sure everyone is on the same cell.

There is also an indicator for the number of active users at the bottom left corner of the matrix. All these are powered by Phoenix Presence, an amazing piece of technology that’s built into the Phoenix Framework. In fact, it was so easy to setup that I actually spent most of my time messing with the UI instead.

Fun Fact: To make the GIF above, I learned that in Mac OS X, you can record your screen by pressing Command + Shift + 5. You can select the area you want to record too. Then I converted the .mov file to a GIF with EZGIF.com.

Logo and Favicon

As the application continue to mature and improve, I figured it’s about time to get a proper logo and favicon done. I engaged my sister, who is a designer to help design a logo that’s simple and professional.

We decided to retain the existing color palette of the application to reduce changes required. The concept is to mimic paper with the fold of the arrow. Traditionally, you’ll work with a decision matrix on paper and the arrow signifies that the aim of the matrix is to find a way forward.

I also wanted a logo so I can have a proper favicon for the site. I used Favicon Generator to generate all the favicon sizes for different platforms and the relevant code needed on the website. The site also helps you verify that your icons are setup correctly for the various platform. An alternative would be Website Planet’s FavIcon Generator which includes a gallery you can pick from.

Recap of the journey after feedback

• Enable Guest Mode to allow anyone to quickly build a matrix.
• Collaborate on a matrix by making them publicly editable.
• Users activity on the matrix is tracked to help with collaboration.
• New logo and favicon!

At this point, I feel the application have reached a milestone that I’m quite proud of for now. I’ll continue to collect more feedback and take some time to figure out what to build next.

I hope you enjoyed the series so far and hope to continue join me in the next phase of the journey. Subscribe to my blog below for future updates.