Ace Vinayak

When to Self-Host an Open Source LLM vs Use API

Sun, 02 Nov 2025 07:29:29 +0000

The question I get asked most frequently these days is: should we build our own LLM infrastructure or just use an API? It’s a deceptively simple question with a complicated answer. I’ve seen teams spend hours/days setting up self-hosted infrastructure for use cases that would have been perfectly served by an API, and I’ve seen teams hit API rate limits and cost ceilings that make their product unviable. The decision isn’t just technical—it’s strategic, financial, and often existential for your product.

Let me be clear upfront: there’s no universal right answer. What makes sense for a startup validating an idea is different from what makes sense for an enterprise handling sensitive data. The trick is understanding when each approach aligns with your actual needs, not just your aspirations.

Understanding the Trade-Offs

Before we dive into when to choose what, let’s be honest about what you’re really comparing. This isn’t just about cost or control—it’s about a fundamental choice in how you want to operate. 2025-01-17-when-to-self-host-an-open-source-llm-vs- Self-hosting means: You own the infrastructure, the models, the data flow, and the responsibility. You get complete control but also complete complexity. You’re not just running software—you’re managing GPU clusters, optimising inference pipelines, handling model updates, and dealing with scaling challenges. I’ve watched teams underestimate this complexity and end up with a system that costs more and performs worse than just using an API.

Using an API means: You’re trading control for convenience. You get state-of-the-art models, automatic updates, built-in scaling, and someone else to handle the infrastructure headaches. But you’re also dependent on a third party, subject to their pricing changes, rate limits, and availability. Your data might leave your infrastructure, and you’re building on someone else’s platform.

The key is recognising that both are valid choices—just for different situations. The mistake I see most often is choosing based on ideology (“we must control our own tech”) rather than actual requirements (“we need X, Y, and Z”).

When to Self-Host

Self-hosting makes sense when the benefits of control and customisation outweigh the costs of complexity (tbf it is a lot easier these days!) and infrastructure. Here are the situations where I’ve seen self-hosting pay off:

Data privacy and compliance requirements: If you’re handling sensitive data — medical records, financial information, legal documents etc data—self-hosting gives you complete control over where your data lives and how it’s processed. In these cases, self-hosting isn’t a nice-t2025-01-17-when-to-self-host-an-open-source-llm-vs-o-have—it’s a requirement.

High-volume, predictable workloads: If you’re making millions of API calls per day with predictable patterns, the economics often tip in favour of self-hosting. API pricing is designed to be profitable for the provider, which means at scale, you’re often paying a premium. If you can amortise (the finance person in me loves this aspect!) the cost of infrastructure across enough usage, self-hosting can be significantly cheaper. But be realistic: you need to account for not just the hardware, but the engineering time to build and maintain (huge factor here!) the system.

Need for customisation and fine-tuning: Open source LLMs can be fine-tuned on your specific data, adapted for your domain, and modified for your use case. If you need models that understand your industry’s terminology, follow your company’s style guide, or integrate deeply with your existing systems, self-hosting gives you the flexibility to customise. Note - APIs offer some customisations though.

Latency requirements: For some applications, every millisecond counts. If you’re building real-time systems where API latency would create noticeable delays, self-hosting can give you better performance (if done correctly) by keeping everything in your own infrastructure. But this only matters if latency is actually a problem—most applications don’t need sub-100ms response times. Also, this is a tricky one, many providers who main business is offering the API has done a great job here already.

Cost predictability: This is the key one in my opinion. API costs scale with usage, which can make budgeting difficult. If your usage is unpredictable, API costs can spike unexpectedly. Self-hosting gives you fixed infrastructure costs (plus the cost of scaling when needed), which can be easier to budget for if you have predictable growth patterns.

2025-01-17-when-to-self-host-an-open-source-llm-vs- And a minor point - Reducing vendor lock-in: Building on APIs means you’re dependent on that provider. If they change pricing, alter terms, or shut down, you’re stuck. Self-hosting gives you more control over your technical destiny, though you’re still dependent on open source projects and your own ability to maintain the system. If you design your systems in such way you can make this plug and play when you move to self-hosting from API - so not a huge deal in my view.

When to Use an API

For most teams, most of the time, an API is the right choice. Here’s when it makes sense:

Speed to market (factor 1): If you need to ship quickly and validate an idea, an API gets you started in days, not months. Self-hosting requires significant engineering investment before you even get to your first inference. I’ve seen teams spend weeks building self-hosted infrastructure when they could have shipped an API-based prototype in few days and learned much more from real users.

Low to moderate volume (factor 2 in my view): If you’re making thousands or even tens of thousands of API calls per day, the cost of self-hosting infrastructure (hardware, engineering time, operational overhead) usually exceeds API costs. The break-even point varies, but for most startups, you’d need to be processing hundreds of thousands of requests daily before self-hosting becomes economically attractive.

Limited engineering resources: Self-hosting isn’t just about running models—it’s about building and maintaining an entire infrastructure stack. You need engineers who understand GPU optimisation, model serving, monitoring, scaling, and all the operational complexity that comes with it. If you’re a small team or your engineers’ time is better spent on product features, an API makes more sense.

Access to latest models: API providers constantly update their models, giving you access to the latest improvements without any engineering effort. With self2025-01-17-when-to-self-host-an-open-source-llm-vs–hosting, updating models requires you to download, test, and deploy new versions—work that adds up over time. If having the latest model capabilities is important, APIs give you that automatically.

Handling complexity you don’t want: Running LLMs at scale is genuinely complex. There’s model optimisation, GPU management, batching strategies, caching, monitoring, error handling, and a dozen other concerns. APIs handle all of this for you, which is valuable if you’d rather focus on building your product than becoming experts in LLM infrastructure.

Variable or unpredictable usage: If your usage patterns are spikey or unpredictable, APIs handle the scaling automatically. With self-hosting, you either over-provision (wasting money on idle resources) or under-provision (failing under load). APIs scale with your needs without you having to think about it.

Experimentation and prototyping: When you’re still figuring out what you’re building, APIs let you experiment quickly and cheaply. You can try different models, test various approaches, and pivot based on what you learn. Once you’ve validated your approach and understand your requirements, you can always migrate to self-hosting if it makes sense.

The Hidden Costs

One of the biggest mistakes I see is teams only comparing the obvious costs—API pricing vs hardware costs—and ignoring the hidden costs that make self-hosting more expensive than it appears.

Operational overhead: Self-hosting means you’re responsible for uptime, performance, debugging, and all the operational concerns that come with running infrastructure. This creates ongoing operational burden that APIs handle for you. If your team is already stretched thin, adding this operational load might not be worth it.

Engineering time: The biggest hidden cost of self-hosting is engineering time. Someone needs to set up the infrastructure, configure the models, build monitoring, handle scaling, and maintain everything. This is time not spent on product features. I’ve seen teams spend 30% of their engineering capacity maintaining self-hosted LLM infrastructure when an API would have freed that time for product work. 2025-01-17-when-to-self-host-an-open-source-llm-vs- Opportunity cost: Every hour spent on infrastructure is an hour not spent on building features that drive your business. If you’re a startup trying to find product-market fit, spending months on infrastructure optimisation might mean missing the window for your product. APIs let you focus on what matters for your business.

Model updates and improvements: With self-hosting, you need to actively track, test, and deploy model updates. APIs handle this automatically. The gap between what’s available via APIs and what you’re running can grow quickly if you’re not actively maintaining your self-hosted setup. This is a huge issue and should be factored in when making the call.

Scaling complexity: Scaling self-hosted LLMs isn’t just about adding more GPUs—it’s about optimising inference pipelines, managing load balancing, handling failures, and all the complexity that comes with distributed systems. APIs abstract this away, which is valuable if you don’t want to become experts in distributed LLM serving.

A Practical Decision Framework

Over time, I’ve developed a simple framework for making this decision:

Start with APIs if:

You’re validating an idea or building an MVP
Your team is small or engineering time is limited
Your usage is low to moderate (under ~100K requests/day)
You want to ship quickly and iterate fast
You don’t have dedicated ML infrastructure expertise

Consider self-hosting if:

You have strict data privacy or compliance requirements (you can work around this even with API)
Your usage is very high (millions of requests/day) and predictable
You need custom models or deep customisation
API costs are becoming a significant portion of your expenses (this is key here!)
You’ve validated your product and understand your requirements

The hybrid approach: Sometimes the answer is both. Start with APIs to validate and learn, then migrate to self-hosting for production workloads that make economic sense. I’ve seen teams use APIs for development and experimentation, then self-host for production systems that need customisation or scale. 2025-01-17-when-to-self-host-an-open-source-llm-vs-

Real-World Examples

When API make sense: Building a customer support tool that used LLMs to draft responses. They can start with an API, ship in two weeks, validate the concept with real customers, and only later you need to consider self-hosting when they reached significant scale. By that point, they would have understood their actual requirements and could make an informed decision.

When self-hosting make sense: Building a legal document analysis tool for a regulated industry. They need to process sensitive documents, couldn’t send data to third-party APIs (due to contractual requirements), and required models fine-tuned on legal terminology. Self-hosting wasn’t just cheaper—it was the only option that met their requirements.

When the decision is wrong: Building self-hosted infrastructure for a product that is not market tested. If they use an API, they could validate the pivot in weeks and save weeks of engineering time.

The pattern I see is: teams that succeed start with the simplest solution that works, validate their approach, and then optimise based on real requirements rather than hypothetical ones.

Key takeaways

The choice between self-hosting and APIs isn’t about which is objectively better—it’s about which aligns with your specific situation. Most teams should start with APIs if they can, validate their product, understand their actual requirements, and only then consider self-hosting if it makes economic or technical sense.

Self-hosting gives you control but adds complexity. APIs give you simplicity but reduce control. The right choice depends on your priorities: if you need to move fast and learn, APIs win. If you need control and customisation, self-hosting might make sense—but only if you’re ready for the operational complexity that comes with it.

You can always migrate!! Starting with an API doesn’t lock you into it forever. Many successful products started with APIs and moved to self-hosting when they reached scale or developed specific requirements. The key is making the decision based on your current situation, not your aspirational future.

The best LLM infrastructure decision is the one that lets teams focus on building products users want rather than becoming experts in LLM operations. Sometimes that means self-hosting. More often, it means using an API and spending your engineering time on what makes your product unique. Choose based on what you actually need, not what sounds impressive.

Technical Debt: When to Pay It Down vs When to Ignore It

Thu, 16 Jan 2025 07:29:29 +0000

Why did the technical debt go to therapy? Because it had too many unresolved dependencies!

Every engineering team I’ve worked with has faced the same question: should we refactor this now or push it to later? Technical debt is one of those concepts that everyone understands but few agree on how to handle. I’ve seen teams spend months perfecting code that never ships, and I’ve seen teams ignore obvious problems until they become existential threats. The reality is that not all technical debt is created equal, and knowing when to pay it down versus when to strategically ignore it can be the difference between moving fast and moving nowhere.

Let me start by saying that I’m not here to tell you that technical debt is always bad—or always good. The truth is far more nuanced. Some technical debt is like a high-interest loan that compounds daily, while other technical debt is more like a 0% APR offer that you can ignore indefinitely. The challenge is learning to tell the difference.

Identifying Technical Debt

Technical debt comes in many forms, and not all of it is immediately obvious. I’ve learned to recognise several common patterns:

Obvious debt: This is the kind that everyone knows exists. Maybe it’s that legacy system that’s held together with duct tape and hope, or the code that makes senior engineers wince when they look at it. This debt is usually documented (or at least whispered about in corridors), and the cost of maintaining it is visible.

Hidden debt: This is more insidious—code that works but is poorly structured, documentation that’s out of date, or dependencies that are one security patch away from being vulnerable. This type of debt doesn’t scream at you, but it compounds quietly in the background.

Architectural debt: This happens when you make design decisions that work now but will limit your ability to scale or adapt later. Perhaps you chose a database that works for 10,000 users but will struggle at 1 million. Or maybe you built a feature in a way that makes it difficult to extend. Architectural debt often seems like the right decision at the time, which is what makes it so dangerous.

Process debt: Sometimes the debt isn’t in the code at all—it’s in how you work. Missing automated tests, manual deployment processes, or lack of monitoring can create debt just as real as bad code. I’ve seen teams spend more time fighting fires than building features because they skipped the infrastructure work.

The key to identifying technical debt is developing a sense of what “good enough” looks like versus what “will bite us later” looks like. This comes with experience, but there are patterns to watch for: code that multiple people avoid touching, features that break frequently, or systems that require specialist knowledge to maintain.

Calculating Cost of Delay

Once you’ve identified technical debt, the next challenge is understanding its true cost. This is where most teams get it wrong—they either overestimate the cost (leading to premature optimisation) or underestimate it (leading to crisis management).

Direct costs: These are the easiest to measure. How much time do engineers spend working around this debt? How many bugs does it cause? How much slower is development because of it? I once worked on a codebase where a poorly designed data layer added an extra day to every feature development cycle. That’s a direct, measurable cost that compounds over time.

Opportunity costs: This is trickier but often more significant. What could your team be building if they weren’t maintaining this debt? What features are you not shipping because you’re spending time on workarounds? What business opportunities are you missing because your technical limitations prevent you from moving fast enough?

Risk costs: Some technical debt creates real risk. Maybe it’s a security vulnerability, or a system that could fail catastrophically under load. I’ve seen teams ignore these risks until they become actual incidents, at which point the cost becomes not just time but reputation and customer trust.

Compound interest: This is the sneakiest cost of all. Technical debt doesn’t just sit there—it compounds. Every feature built on top of shaky foundations makes the problem worse. Every developer who learns to work around the problem embeds the workaround deeper into the codebase. The debt that costs you 5% of your engineering time today might cost you 20% in six months.

The framework I use is simple: if the monthly cost of the debt (in engineer time, bugs, or missed opportunities) is greater than the cost of fixing it, you should probably fix it. But if the debt is static—it exists but doesn’t actively cost you anything—then it might be okay to leave it for now.

Strategic Refactoring

Not all refactoring is created equal. The goal isn’t to have perfect code—it’s to have code that serves the business effectively. Strategic refactoring means choosing what to fix based on impact, not just aesthetics.

Fix what’s actively hurting: Start with debt that’s causing problems today. Is there a system that’s breaking frequently? Code that multiple engineers struggle with? A bottleneck that’s slowing down development? These are high-impact fixes that will make a real difference.

Refactor during feature work: One of the most effective approaches I’ve found is to refactor as you build. If you’re already touching code for a new feature, that’s the perfect time to improve it. This doesn’t mean rewriting everything—just making the code you’re working on a bit better than you found it. Over time, this approach compounds into a much cleaner codebase without the big-bang refactoring projects that never seem to finish.

Create technical milestones: Sometimes you need to dedicate time specifically to technical improvement. The key is to do this strategically—choose what to fix based on what will unlock future velocity, not what looks prettiest. I’ve had success setting aside 20% of engineering time for technical improvement, but only if that time is spent on high-impact work.

Measure the impact: After you refactor, measure whether it actually helped. Did it reduce bugs? Speed up development? Make onboarding easier? If you can’t measure improvement, you might have optimised the wrong thing. I’ve seen teams celebrate beautiful refactors that didn’t actually change outcomes—which means they wasted time they could have spent on features.

Know when to stop: Perfect is the enemy of good. I’ve watched teams refactor the same system three times because they kept finding ways to make it “better.” At some point, you need to accept that the code is good enough and move on to building features.

When Technical Debt is Actually OK

This might be the most controversial part of this post, but not all technical debt is bad. In fact, sometimes it’s the smart choice.

Debt that enables speed: Sometimes taking on technical debt lets you ship faster and learn from real users. If you’re validating a product idea, shipping imperfect code might teach you more than perfect code that never ships. I’ve seen startups spend six months building the perfect system for a product that nobody wanted. A bit of technical debt in the early days can be a smart trade-off.

Debt with low interest rates: Some technical debt just sits there. It’s not great code, but it works, it’s stable, and it doesn’t cause problems. Refactoring this might make you feel better, but if it doesn’t improve outcomes, why bother? I’m not suggesting you ignore all technical debt, but if the code works and isn’t actively costing you anything, there might be higher-value work to do.

Debt you’ll outgrow: Some technical decisions make sense for your current scale but won’t work at 10x scale. The question is: will you ever reach 10x? If you’re a small team with uncertain growth, optimising for scale you might never reach is premature optimisation. It’s okay to have code that works for now and might need rethinking later.

Debt that’s cheaper to rewrite: Sometimes the best way to pay down technical debt is to throw it away and start fresh. If a system is so tangled that refactoring would take months, building a replacement might be faster and better. I’ve seen teams spend years trying to fix legacy systems when they could have built something new in six months.

Strategic shortcuts: Not every shortcut is a mistake. Sometimes the quick implementation is good enough for the problem you’re solving. Perfect code for a throwaway prototype is wasted effort. Code that ships and generates revenue is more valuable than perfect code that never sees the light of day.

The key is being honest about whether the debt is a strategic choice or an accident you’re too lazy to fix. Strategic debt is intentional—you know you’re taking it on and why. Accidental debt is just poor engineering, and that will compound until it becomes a crisis.

A Personal Framework

Over the years, I’ve developed a simple framework for deciding what technical debt to tackle:

Is it actively costing us time or money? If yes, prioritise fixing it. If no, it can wait.

Will fixing it unlock future velocity? Some refactoring pays for itself by making future development faster. This is usually worth doing.

Is it creating risk? Security vulnerabilities, systems that could fail under load, or code that’s one wrong change away from breaking—these need fixing.

Can we work around it effectively? If the debt is contained and easy to work around, it might be lower priority than debt that infects everything you build.

What’s the opportunity cost? Every hour spent refactoring is an hour not spent building features. Make sure the refactoring is worth that trade-off.

I’ve found that most technical debt falls into one of three categories: debt that’s actively hurting (fix it), debt that will hurt later (plan to fix it), and debt that’s just ugly but harmless (maybe ignore it). The art is in correctly categorising your debt.

Key takeaways

Technical debt isn’t inherently good or bad—it’s a tool. Like any tool, it can be used well or poorly. The teams that succeed are the ones that learn to take on debt strategically and pay it down when it makes sense, not the ones that either ignore it completely or obsess over eliminating it entirely.

The goal isn’t zero technical debt. The goal is technical debt that serves your business objectives. Sometimes that means taking on debt to move fast. Sometimes that means paying it down to avoid future pain. The skill is in knowing which is which.

Remember: code that ships and generates value is better than perfect code that never sees users. But code that constantly breaks and slows you down is worse than both. Find the balance, make strategic choices, and don’t let perfectionism—or laziness—drive your technical decisions.

The best codebases I’ve worked with aren’t the ones with the prettiest code—they’re the ones where the technical decisions align with business needs, where debt is taken on intentionally and paid down strategically, and where engineers can move fast without breaking things constantly. That’s the sweet spot worth aiming for.

Remote Work Boundaries: Creating Structure When Work and Home Blend

Wed, 15 Jan 2025 07:29:29 +0000

Remote work has transformed how we approach our professional lives, blurring the lines between where we work and where we live in ways we never imagined. I’ve spent significant time working remotely, both as an individual contributor and as a leader managing distributed teams, and I’ve learned that creating boundaries isn’t just nice to have—it’s essential for maintaining both productivity and wellbeing.

When your kitchen table becomes your conference room and your bedroom doubles as your office, the traditional structures that once separated work from life disappear. Without these boundaries, work can bleed into every hour of your day, and personal time can feel like stolen moments. The key is to create new structures that work for remote settings, recognising that boundaries aren’t about building walls—they’re about creating clarity.

Physical Boundaries

The most obvious challenge with remote work is that your physical space serves multiple purposes. I’ve worked from kitchen counters, sofas, and even my bed (not recommended), and I can tell you that having a dedicated workspace makes all the difference.

Create a designated workspace: This doesn’t mean you need a separate room, though that’s ideal. A dedicated corner with a desk or even a specific chair that you only use for work can help signal to your brain that it’s time to focus. I set up a small desk in the corner of my living room, and just sitting at that desk immediately shifts my mindset into work mode.

Separate work and personal devices: If possible, keep work applications on a separate device or at least in separate browser profiles. This physical separation helps create mental separation. When I close my work laptop at the end of the day, I’m not tempted to check Slack notifications on my personal phone.

The commute ritual: One of the most effective techniques I’ve adopted is creating a “fake commute”—a short ritual that marks the transition between work and personal time. For me, this means a 10-minute walk around the block after I finish work, which gives my brain time to decompress and transition. It’s not about the physical distance; it’s about the mental space.

Temporal Boundaries

Time boundaries are perhaps more critical in remote work than physical ones. Without the natural cues of leaving an office, it’s alarmingly easy to work from morning until night.

Set clear work hours: Decide on your work hours and communicate them clearly with your team. I typically work from 9 AM to 6 PM, and I make it clear that I won’t be checking messages outside these hours unless it’s a genuine emergency. This isn’t about being inflexible—it’s about setting expectations and protecting your personal time.

Use calendar blocking: Block out your personal time in your calendar just as you would block out meetings. I schedule my lunch break, exercise time, and even my “end of day” transition time. This prevents work from creeping into these slots and signals to colleagues when you’re available.

Create morning and evening routines: Start your day with a routine that doesn’t involve immediately opening your laptop. Whether it’s exercise, meditation, or simply making a proper cup of coffee, these rituals help signal the start of your workday. Similarly, an end-of-day routine—perhaps reviewing what you accomplished, planning tomorrow’s priorities, and then physically closing your laptop—helps mark the boundary between work and personal time.

Managing Energy in Remote Settings

Remote work requires a different approach to energy management than office work. The lack of social interaction, the monotony of the same environment, and the challenge of maintaining focus all take their toll.

Schedule based on energy levels: Pay attention to when you’re most productive and schedule your most important work during those times. I’m a morning person, so I tackle my most challenging tasks before noon and save meetings and lighter work for the afternoon. This isn’t just about productivity—it’s about working with your natural rhythms rather than against them.

Take intentional breaks: In an office, breaks happen naturally—chatting with colleagues, grabbing coffee, walking to meetings. At home, these moments don’t exist unless you create them. I set reminders to take a 5-minute break every hour, and I actually step away from my desk. Even just standing up and looking out the window can reset your focus.

Create variety in your day: One of the challenges of remote work is the monotony. I combat this by varying my work environment when possible—working from a different room, taking video calls while walking, or even occasionally working from a local café. This variety helps maintain energy levels throughout the day.

Recognise the difference between being busy and being productive: It’s easy to feel busy when working from home—constant notifications, the ability to multitask, the temptation to “just quickly check” something. But being busy isn’t the same as being productive. I’ve learned to focus on outcomes rather than activity, which helps me manage my energy more effectively.

Communication Practices for Remote Teams

Boundaries aren’t just personal—they need to be respected by your team as well. Clear communication practices help everyone work effectively while maintaining healthy boundaries.

Establish communication norms: Set expectations about response times, preferred communication channels, and what constitutes an emergency. In my team, we have a clear policy: Slack messages don’t require immediate responses, emails can wait until the next working day, and texts are only for genuine emergencies. This clarity helps everyone respect each other’s boundaries.

Use async communication effectively: One of the biggest advantages of remote work is the ability to work asynchronously, but this requires discipline. I write detailed messages, use threads to keep conversations organised, and document decisions clearly. This reduces the need for constant back-and-forth and allows people to respond when it works for them.

Respect time zones: If you’re working with a distributed team, be mindful of time zones. Just because it’s 2 PM for you doesn’t mean it’s a good time to schedule a meeting for someone else. I always check time zones before sending calendar invites and try to rotate meeting times so the burden doesn’t always fall on the same people.

Create space for non-work communication: Remote teams can feel disconnected, so it’s important to create space for the casual interactions that happen naturally in an office. We have dedicated Slack channels for non-work conversations, and I make a point of checking in with team members about how they’re doing, not just what they’re working on.

Personal Experiences and Practical Tips

When I first transitioned to remote work, I made every mistake in the book. I worked from my sofa, checked email constantly, and felt guilty about taking breaks. It took me months to realise that this approach wasn’t sustainable—or productive.

The power of “done for the day”: One of the most liberating realisations I had was that there’s always more work to do, and that’s okay. Setting a clear “done for the day” time and sticking to it—even when there are tasks left unfinished—has been crucial for maintaining my boundaries and avoiding burnout.

Boundaries are about respect, not rejection: I used to worry that setting boundaries would make me seem uncommitted or unhelpful. But I’ve learned that boundaries actually enable better work. When I’m well-rested and have time for personal activities, I bring more energy and focus to my work. Plus, my team respects my boundaries because they have their own to protect.

Flexibility within structure: Having boundaries doesn’t mean being rigid. Some days, I need to work late to meet a deadline or start early for a time-sensitive project. The key is that these are exceptions, not the rule. I communicate these exceptions clearly and make sure to compensate with time off later.

Learn to say no: Remote work makes it easier to say “yes” to every request—after all, there’s no commute, so why not take on that extra project? But capacity is still capacity, whether you’re in an office or at home. Learning to say no professionally is even more important when working remotely.

Key takeaways

Remote work boundaries aren’t about creating rigid rules—they’re about creating structures that allow you to do your best work while maintaining your wellbeing. The physical, temporal, and energetic boundaries you set today will determine how sustainable your remote work arrangement is in the long term.

Remember that boundaries benefit everyone: they help you maintain focus and energy, and they help your team understand when and how to communicate with you. Most importantly, they allow you to fully disconnect from work, which is essential for recharging and bringing your best self to your job.

The beauty of remote work is its flexibility, but that flexibility requires discipline. By creating clear boundaries—physical, temporal, and communicative—you can enjoy the benefits of remote work without sacrificing your personal life or professional effectiveness. So, take the time to design boundaries that work for you, communicate them clearly, and then stick to them. Your future self will thank you.

Navigating the Financial Mind Maze Using Prospect Theory - The Biases that Shape Our Decisions

Sun, 09 Jul 2023 07:29:29 +0000

How did the economist-turned-baker describe their bread-making skills? “I ‘prove’ that I can ‘rise’ to the occasion and knead the dough’mestic market!”

You’re strolling through a bustling marketplace, surrounded by things you can buy at every turn. Should you invest in that tempting stock? Is it time to splurge on a luxury vacation? Or maybe you’re contemplating whether to save for retirement or indulge in that irresistible new gadget. In the realm of personal finance, our decisions can sometimes feel like a game of chance.

Let’s dive into the fascinating world of Prospect Theory and the biases that influence our financial choices. So buckle up and get ready for a rollercoaster ride through the human mind!

The Tale of Prospect Theory

Let’s start by unraveling the mysteries of Prospect Theory (proposed by Daniel Kahneman and Amos Tversky), this theory challenges the traditional notion that humans are rational decision-makers. Instead, it suggests that our choices are influenced by two key factors: the potential gains and losses associated with each option and more importantly - our perception of these gains and losses.

The Allure of Loss Aversion: Ah, the human brain’s fascinating love affair with loss aversion! You’re more likely to experience a stronger emotional response when losing $100 than winning the same amount at a casino. Why? Because the pain of losing feels more intense than the pleasure of gaining. Our minds are wired to avoid losses at all costs, leading to conservative financial decisions and missed opportunities. (Think about the number of times you decided not to invest in the stock market because of events going on at the time).

Anchoring Bias: Imagine you’re shopping for a brand new car. You’ve done your research and narrowed it down to two options, but you find yourself irresistibly drawn to the more expensive model. That’s the power of the anchoring bias at play! We tend to rely heavily on the first piece of information we encounter when making decisions, using it as a mental anchor. This bias can skew our perceptions, leading us to make choices that may not align with our best interests.

The Bandwagon Effect: Have you ever jumped on a trend simply because “everyone else is doing it”? We’re all guilty of succumbing to the bandwagon effect, and our financial decisions are no exception. Whether it’s investing in a hot stock (remember the meme stock craze) or joining the cryptocurrency frenzy, we often find comfort in following the herd. But beware! This bias can cloud our judgment and cause us to overlook critical factors like risk and personal financial goals.

Overconfidence Bias: Did you know that 90% of drivers consider themselves above average? That’s the overconfidence bias for you! When it comes to finance, we often overestimate our abilities and believe we possess superior knowledge or skills. This bias can lead to excessive risk-taking, speculative investments, and a painful reality check when the market takes an unexpected turn. Remember, a little humility can go a long way in the world of personal finance!

The Impact on Financial Wellbeing

These biases, rooted deep within our cognitive processes, have a profound impact on our financial wellbeing. By understanding how Prospect Theory and its associated biases influence our decisions, we can strive for greater self-awareness and make more informed choices.

When we recognise the allure of loss aversion, we can better balance risk and reward, allowing ourselves to seize opportunities without succumbing to fear. Anchoring bias can be counteracted by seeking diverse perspectives and taking the time to explore alternative options, ensuring our decisions are grounded in reason rather than a single anchor point.

Similarly, avoiding the bandwagon effect means resisting the urge to follow the crowd blindly. It’s crucial to maintain a critical eye, evaluate risk factors, and make choices that align with our personal financial goals and values.

Lastly, taming the overconfidence bias requires a healthy dose of skepticism. Remember, financial decisions are a journey, not a destination!

Prospect Theory and its associated biases shed light on the intricate dance between human psychology and decision-making. By understanding these biases, we can become more aware of the traps our minds set for us and take steps to overcome them. So, the next time you find yourself at the financial crossroads, take a moment to reflect on the invisible biases that may be steering your decisions. Trust yourself, but don’t forget to question your instincts and make choices that align with your long-term financial wellbeing. After all, it’s your money, and you’re the one who gets to ride the rollercoaster!

As legendary investor Warren Buffett once quipped, “The stock market is a device for transferring money from the impatient to the patient.” Stay patient, stay informed, and enjoy the ride!

Disclaimer: The information provided here for educational purposes only and should not be considered financial advice.

Stock Market Experts: When Drama Trumps Accuracy

Mon, 13 Mar 2023 07:29:29 +0000

Why did the investment advisor visit a psychic? He wanted to know his clients’ futures.

Stock market experts, ah yes, the supposed purveyors of stock market information - why the market is up or down on a give day or predicting the market / individual stocks. How could one not trust these knowledgeable experts that hold the keys to the mysteries of the stock market and the economy at large? After all, they are always so on point and never, ever get anything wrong, right?

What they thrive on is nothing more than drama, only interested in stoking controversy, creating sensational headlines, and stirring up fear and uncertainty in their readers / viewers. And the sad part is, people actually fall for it. It’s as if they forget that the stock market is an unpredictable entity (yes, both Shiller & Fama are right - there is a reason why they won the Nobel Prize in Economics together) and that no one, not even the so-called stock market experts, can accurately predict its movements.

Let’s start with a prime example of their expertise (read: trying to understand why Mr. Market behaves in a certain way on a particular day or what will he do next). Remember that time when they were all in a frenzy over the impending economic collapse, warning us to sell all of our investments and hide our money under a mattress? And then, lo and behold, the market rebounded and reached new highs, leaving those who took the expert advice feeling foolish. Or how about when they touted a particular stock as a sure thing, only for it to tank, leaving investors feeling burned?

The talking heads many news channels bring on as experts simply spout off grandiose predictions, pontificate on the latest trends and events, and then have the audacity to claim that they “got it wrong” when things don’t go according to plan. It’s like a never-ending game of financial charades, where everyone is just guessing and no one has any real answers. I have to say there are very few experts who don’t do this.

Some channels and magazines have dedicated space allocated these experts on a regular basis. They constantly seek out the latest financial scandal or controversy, and then blow it out of proportion, creating a sense of panic and fear in their readers / viewers. There are shows that play up the drama by using flashy graphics, ominous music, and of course, their experts to add their two cents or in some cases an expert host whose primary objective is to keep viewers by talking $h*t. All of this just for the sake of getting higher ratings - because let’s be real, who wants to watch a boring, factual show when you can watch one filled with sensationalism and drama?

And what’s the result of all this drama-mongering? A public that is misinformed, scared, and more often than not, taken advantage of. These news shows don’t provide real, actionable advice that can help people make informed financial decisions. Instead, they feed on the public’s fears and uncertainties, exploiting them for their own gain.

Next time you’re tempted to tune into a “ finance show” or read a newspaper column on stock recommendations, remember this: they are not a reliable source of information. It is pure drama - plain and simple, more interested in creating sensational headlines and stoking controversy than providing accurate, helpful information. If they could actually predict what was going to happen in the financial markets, they’d be doing it themselves, not just talking about it on TV or writing it on a newspaper.

What does the data say about professional experts

Let’s review another group - investment fund managers who actively manage your money. You might imagine these group should be better than experts you see on TV - in fact it’s their duty to produce the best returns for their clients.

The S&P Indices Versus Active (SPIVA) reports are widely respected studies that compare the performance of actively managed funds to their benchmark indices. The SPIVA results consistently show that actively managed funds underperform their benchmark indices. This is true across all asset classes and markets. The underperformance is not limited to just one or two years but has been consistent over the long-term. In fact, the SPIVA reports have consistently shown that the majority of active fund managers underperform their benchmark indices over the long-term.

This means that investors who are seeking to achieve market returns are better off investing in low-cost index funds or ETFs. Investors who are considering investing in actively managed funds should be aware of the potential risks and limitations of these funds, including higher fees and potential tax implications.

However:

The importance of data in the investment world cannot be overstated. Data allows investors to make informed decisions based on historical performance and trends. It also helps investors to understand the risks and potential rewards of different investment strategies.

One important concept related to the use of data in the investment world is the Grossman-Stiglitz Paradox. This paradox suggests that the market may not be efficient if investors have different levels of information. In other words, if some investors have more or better information than others, the market may not be able to accurately reflect the true value of an asset. This can create opportunities for some investors to earn outsized returns by exploiting the information asymmetry.

In this context it is worth mentioning that despite the criticisms leveled against specific financial news shows and stock market experts, there are some channels that produce good content. These channels do shows based on pure news reporting, investigative analysis, and data-based documentary to provide viewers with accurate and unbiased information. For example: FT & The Wall Street Journal are two financial news sources that are known for their in-depth reporting and analysis. Bloomberg often relies on data and research to provide viewers with accurate information. CNBC provides viewers with financial market updates, analysis, and interviews with CEOs and industry experts. The channel has a reputation for producing quality content that is based on accurate data and research. Just stay away from the stock market experts and drama, you will be fine.

Prioritisation: Why It is Not Effective Until It Hurts

Sun, 12 Mar 2023 07:29:29 +0000

Why did the manager prioritize the stapler over the pencil? Because it was the staple of the office!

Everyone at work talks about prioritisation. It’s a concept that is often cited as a key factor in success, productivity, and effective time management. However, the truth is that many people don’t fully understand what prioritisation really means or how to put it into practice. In this blog post, I’ll explore my views on prioritisation, why it’s not effective until it hurts, and how to prioritize effectively in both your personal and professional life.

What is Prioritisation?

At its core, prioritisation is simply the process of deciding what is most important and should be done first. I am not good at multitasking. So I rely heavily on prioritisation to get sh*t done.

It’s a way of making choices about what to focus on; and more importantly what to ignore. Whilst, the idea of prioritisation is simple, but the execution can be challenging.

One of the key challenges in prioritisation is that there are always more things to do than there is time to do them. We all have limited time, energy, and resources, so we must be selective about where we invest them. Otherwise, we won’t able to complete those tasks that actually move the needle. It requires us to be intentional about where we put our time and effort, and to make difficult decisions about what we can and cannot do (The Subtle Art of Not Giving a F*ck by Mark Manson is a book I would recommend).

Why It’s Not Prioritisation Until It Hurts

One of the most common mistakes people make when it comes to prioritisation is trying to have multiple priority lists. We think we can prioritize everything, and as a result, we end up with a bunch of different lists and priorities that are all competing for our attention. The problem with this approach is that it dilutes our focus and makes it difficult to make progress on anything.

There is only one of you, so you shouldn’t need to have two priority lists.

And the truth is, prioritisation isn’t effective until it hurts. To truly prioritize, we must be willing to make sacrifices and say no to things that are not essential. This means making difficult decisions about what we can and cannot do, and being willing to accept the consequences of those decisions (I have written a blog post before on how to say no without feeling guilty).

It’s only when we start saying no to things that we can truly focus on what’s most important. When we have too many things on our plate, we end up spreading ourselves too thin, and we don’t make meaningful progress on anything.

Why We Should Say No

Saying no is one of the most important skills one should develop when it comes to prioritisation. It’s also one of the most difficult. Many of us struggle with saying no because we want to be helpful, we don’t want to disappoint others, or we fear missing out on opportunities (I have discussed these topics in detail in the above blog post).

Saying no is about setting boundaries and being clear about our priorities. Saying no is not about being unhelpful or selfish, it’s about being honest and realistic about what we can realistically accomplish.

Tips for Effective Prioritisation

So, how can we prioritize effectively? Here are some tips:

Start with a Single List: The first step in effective prioritisation is to create a list of everything you want/need to do. This includes both short and long-term tasks, as well as personal and professional responsibilities. This list serves as a way to get everything out of your head.

Identify Your Top Priorities: Once you have this list, the next step is to identify your top priorities. These are the tasks and responsibilities that are most important to you and require the most attention. You can have several top priorities, but try to limit them to no more than three or four. These are the things that should be at the top of your priority list. When prioritizing, it’s important to consider both urgency and importance. Urgent tasks are those that require immediate attention, while important tasks are those that contribute to long-term goals and objectives. Ideally, you want to focus on tasks that are both urgent and important, but sometimes you may need to prioritize one over the other.

Be Realistic: When prioritizing, it’s important to be realistic about what you can accomplish. Don’t try to take on too much or set unrealistic deadlines for yourself. This will only lead to frustration and burnout. Instead, be honest about what you can realistically accomplish and prioritize accordingly.

Say No: We have covered this in detail before.

Review and Adjust: Always keep in mind that effective prioritisation is an ongoing process. You should regularly review your priorities and make adjustments as needed. This may mean adding or removing tasks from your list or adjusting your timelines. The key is to be flexible and adaptable as your priorities and circumstances change.

Remember to start with a single list.

The Importance of 'No Meetings Days' in the Workplace

Sat, 11 Mar 2023 07:29:29 +0000

What did the employee say when his boss asked him how he managed to get so much done on “No Meetings Day”? “I guess I was just meeting my deadlines!”

With endless meetings, emails, and distractions, it can be difficult to focus and get things done. That’s why companies should promote a Get $#!t Done Day - a day dedicated to no meetings, no interruptions, and maximum productivity.

Studies have shown that interruptions can have a major impact on productivity. According to a study by the University of California, Irvine it takes an average of 23 minutes and 15 seconds to get back on track after an interruption. That’s a lot of time wasted!

Of course, some may argue that taking a day off from meetings and other distractions is not feasible in today’s world. But I would argue that it’s precisely because of such demands that such a day is needed. In fact, many companies have already implemented similar policies with great success.

Asana has a policy known as No Meeting Wednesdays (NMW) where everyone knows not to schedule meetings on Wednesdays, unless absolutely necessary. Basecamp famously has their Work Can Wait feature, where employees are encouraged to focus solely on their work without interruptions. Similarly, Buffer, a social media management company, where employees are given the opportunity to work without distractions.

Here’s why every company should adopt this concept:

Increased focus & productivity: Without the distractions of meetings and emails, employees can focus on completing important tasks and projects. This can lead to improved accuracy and higher quality work. With a Get $#!t Done Day, employees are able to make the most of their time and increase productivity. This can lead to greater efficiency and a more productive workforce.

Better time management: By dedicating a specific day (or two) per week to getting things done, employees can manage their time more effectively and avoid the feeling of being overwhelmed.

Improved morale: Allowing employees to have a day dedicated to getting things done can boost morale and increase motivation. It can also promote a sense of ownership and accountability, as employees are able to take charge of their own workload.

Better communication: By dedicating a specific day to getting things done, companies can improve communication by reducing the number of meetings and emails. This can lead to more focused and effective communication.

Get $#!t Done Days can be a game-changer for companies looking to improve productivity and efficiency. By implementing a policy that facilitates this, companies can help employees stay focused and productive, while also promoting a healthier work-life balance. It’s a small change that can have a big impact on both employee well-being and the bottom line.

So, why not give it a try and see the results for yourself?

The Retirement Savings Crisis: Why Younger Generations are Falling Behind

Sat, 04 Mar 2023 08:29:29 +0000

Why did the piggy bank go to the psychiatrist? It was feeling a little empty inside.

⚠️NOTE⚠️ This blog post is for informational purposes only and should not be considered as financial advice. Before making any financial decisions, readers should consult with a regulated finance professional and do your own research (DYOR).

The issue of retirement savings has become increasingly prevalent in recent years, particularly amongst the younger generation. Despite being faced with the prospect of longer life expectancies and a changing job market, many young people are not saving enough for their retirement. This is a cause for concern, as it will likely result in financial instability for many individuals in their retirement period.

Problem: The average working household has virtually no retirement savings.

Research has consistently shown that younger generations are falling behind when it comes to retirement savings. According to a recent survey conducted by the National Institute on Retirement Security, nearly 40 million working-age households in the United States have no retirement savings at all - whether in an employer-sponsored 401(k) type plan or an IRA. 62% of working households with age range of 55-64 have retirement savings less than one times their annual income.

It’s a global problem - According to a report by the World Economic Forum, the global retirement savings gap is projected to reach $400 trillion by 2050, with the largest gaps seen in Asia and North America.

Why is this happening now?

One of the main reasons for this is the lack of access to traditional pension plans. For example in the UK, a fair number of people working in public sector had a defined pension which is based on the years you have been an employee and the final salary at the time you retire. These types of pension plans were once the main source of retirement income for many people, but they have become increasingly rare in recent years.

Many younger workers are now relying on individual retirement accounts (IRAs or SIPPs) and other types of savings plans, which can be harder to manage.

Additionally, the changing job market has made it less likely for people to stay with one employer for a long period of time. This has reduced the number of people who are eligible for pension plans.

Solution: Change our approach to saving for retirement

It is important for policymakers, employers, and individuals to take action to address this issue and ensure that younger generations are able to secure their financial futures. This could include increasing access to a wide range of retirement plans, improving financial education, and encouraging young people to start saving for retirement as early as possible.

Many employers are now offering automatic enrollment in their retirement plans, which means that employees are automatically enrolled in the plan unless they opt out. This can increase participation rates and make it easier for employees to start saving for retirement.

Retirement plans can be overwhelming with too many investment options, making it difficult for individuals to make informed decisions. Using tools that would simplify this for people should translate into a higher amount of saving.

More importantly, as a society we need to have better relationship with money. It involves being mindful of one’s financial goals and taking steps to achieve them while also maintaining a healthy balance between spending and saving. It also involves being mindful of one’s financial situation and taking proactive steps to achieve financial security and stability. By doing so, individuals can reduce financial stress and anxiety and make informed decisions that support their long-term financial well-being.

Ways to optimise

Start Early: The earlier you start saving for retirement, the more time your investments have to grow. By starting early, you can take advantage of the power of compounding, which can significantly increase your retirement savings over time.

Automated saving: Ensure that your savings go out of your bank account within a day of you receiving your salary. Humans are bad at these tasks. You want to have minimal friction to increase regular savings.

Reduce debt: Paying off debt can help you save money in interest charges and free up money each month to put towards savings.

Use tax wrappers to save: In the US and the UK Individual Retirement Accounts (IRAs) and Self-Invested Personal Pensions (SIPPs) are two popular savings schemes that can be used effectively to achieve the goal of a secure retirement. There are similar account available in most western countries.

Maximize Contributions: Accounts such as IRAs and SIPPs have contribution limits, and maximizing these limits can help you reach your retirement savings goals more quickly. Consider increasing your contributions each year, or taking advantage of catch-up contributions. IRAs and SIPPs offer tax benefits, which can help you save more for retirement. For example, contributions to a traditional IRA may be tax-deductible, and the investment earnings grow tax-deferred. SIPPs also offer tax benefits, including the ability to claim tax relief on contributions.

Diversify Investments: Diversifying your investments is key to reducing risk and maximizing returns. Both IRAs and SIPPs offer a wide range of investment options, including stocks, bonds, and mutual funds. Consider creating a well-diversified portfolio that includes a mix of low-risk and high-risk investments. You may want to explore how index investing can help you save on fees.

Remember, small changes can add up over time, so be patient and stay focused on your goals.

Balancing Compensated and Uncompensated Risks in Business: A Historical Perspective

Tue, 28 Feb 2023 07:29:29 +0000

What do you call an entrepreneur who takes a lot of risks and always succeeds? A lucky duck!

Risk is a constant companion in life and business, but not all risks are created equal. From a business perspective, every strategy taken by a company carries with it the potential for reward and failure. Some risks can be anticipated, calculated, and even controlled, while others are unpredictable and outside of our control - which is part and parcel of running a business (particularly a scale-up).

So if taking calculated risks is necessary for any business, how can we effectively take compensated risks?

The human brain is not very good at distinguishing between compensated and uncompensated risks. We tend to focus more on the potential consequences of a risk than the probability of it occurring. We are also more likely to perceive risks that are unfamiliar or that evoke a strong emotional response, such as fear. There is also the optimism bias - the tendency to believe that one is less likely to experience negative events - this encourages us to over-index on the likelihood of encountering positive events. While optimism bias can have some disadvantages, such as leading individuals to underestimate risks, it also has some advantages (particularly when we are starting a business).

To succeed in this complex and ever-changing environment, businesses must balance the need to pursue opportunities with the need to mitigate the impact of negative outcomes. This balance is achieved by weighing the trade-off between compensated and uncompensated risks.

What does this mean in practice? Compensated risks optimises for a potential reward that compensates for the risk the business is taking. This reward can come in the form of increased profits, market share, or brand recognition. For example, companies that invest in research and development (R&D) often take on compensated risks. This is the reason why one needs to be careful of curring R&D costs when times are tough. You may invest significant amounts of resources into new products or technologies that may not yield results for several years. However, if the product is successful, the rewards can be substantial. In this case, the company is compensating itself for the risk it is taking by investing in something that has the potential to pay off in the future. They are risks that are calculated and planned for, rather than risks that are taken blindly. In other words, compensated risks are risks that are worth taking because the potential reward outweighs the potential downside.

On the other hand, uncompensated risks are those that carry potential consequences but do not offer any offsetting rewards. For example, the 2008 financial crisis was an example of an uncompensated risk that had a profound impact on the global economy. Companies that were heavily invested in mortgage-backed securities (MBS) saw the value of their investments plummet overnight, leaving them with massive losses and no offsetting rewards. The one who did tail-hedging were rewarded in the end.

In order to effectively manage risk, businesses must have a clear understanding of both compensated and uncompensated risks and develop strategies that balance the two. Let’s take a look at some strategies that can help you effectively take compensated risks in business.

Start Small and Test Your Ideas: One way to take compensated risks is to start small and test your ideas before committing a large amount of resources. This approach is often referred to as the “lean startup” methodology, and it involves creating a minimum viable product (MVP) that fulfills the minimum viable experience (MVE) so that you can test your idea with customers.

Conduct Thorough Market Research: In their book Blue Ocean Strategy, authors Renée Mauborgne and W. Chan Kim (both professors at INSEAD Business School) explain that conducting market research can help you identify untapped market opportunities and create a unique value proposition that sets you apart from competitors. By taking a calculated risk on a new market opportunity, you can potentially capture a larger market share and grow your business. For scale-ups, market research is still important. As a business grows, it is important to continue to stay informed about industry trends and customer needs. By doing so, you can identify new opportunities for growth and continue to take calculated risks.

Develop a Risk Management Plan: Taking risks in business is necessary, but it is important to have a risk management plan in place to mitigate potential downsides. A risk management plan should identify potential risks and develop strategies for managing them. By identifying potential risks and developing strategies for managing them, entrepreneurs can take calculated risks with more confidence.

One famous example of a company that successfully managed compensated and uncompensated risks was Johnson & Johnson. In 1982, the company faced a major crisis when seven people died after taking Tylenol, a painkiller drug produced by the company. Johnson & Johnson responded to the crisis with a well-coordinated, transparent, and compassionate response that demonstrated its commitment to safety and quality. The company immediately pulled all Tylenol products from store shelves, launched an investigation into the cause of the contamination, and developed tamper-resistant packaging. By handling the crisis by putting the customers first, Johnson & Johnson was able to not only mitigate the impact of the crisis but also establish itself as a trusted and responsible corporate citizen.

Risk is an inevitable part of doing business. However, companies that are able to balance the trade-off between compensated and uncompensated risks are more likely to succeed in the long run. Whether through diversification, risk management technologies, or a commitment to responsible corporate citizenship, businesses can manage risk and achieve their goals. By understanding the historical examples of companies that have successfully navigated these challenges, we can gain valuable insights into the best practices and strategies for managing risk.

What about asymmetric risk?

Asymmetric risks are risks where the potential reward is higher than the potential risk. They are rare to find, but they can be great for any business if identified and executed properly. These types of risks are more likely to be found in emerging markets or industries where there is little competition and innovation. We will be discussing this in detail in a future blog post.

Minimum Viable Experience: Why it is crucial to achieve product-market fit before optimizing technical infrastructure and codebase

Sat, 25 Feb 2023 07:29:29 +0000

Businesses, especially startups, need to move quickly and be willing to experiment and learn from their failures. This requires a willingness to pivot your business model or strategy if necessary, and to make decisions based on data and feedback rather than assumptions.

By adopting an iterative approach, startups can continuously refine and improve their product or service, incorporating customer feedback and responding to changing market conditions. This allows them to stay ahead of the competition and adapt rapidly to new challenges as they arise.

Whilst technical advancements have made it easier for startups to create and launch new products, the key to success lies in achieving product-market fit (PMF) - i.e. the product should not only solve user problems but also generate a sustainable revenue stream. However, in the quest to achieve perfection, some start-ups often make the mistake of over-investing in technical infrastructure and software architecture, which in fact can hinder their ability to achieve product-market fit quickly. In this post, we will discuss the concept of a Minimum Viable Experience (MVE) and why it’s crucial to achieve PMF before optimizing technical infrastructure and software architecture.

What is Minimum Viable Experience (MVE)?

MVE is aimed at creating a product or service that provides the minimum level of experience required to meet the needs of their customers (rather than just a viable product). In other words, the MVE is the simplest version of a product that can be launched in the market to test a core user experience and gather feedback. The MVE approach allows us to validate assumptions, learn from mistakes and make necessary changes before investing significant resources in optimizing their technical infrastructure and codebase.

An MVP (Minimum Viable Product) is a product that has just enough features to be launched in the market and solve a specific problem for a specific set of customers. The goal of an MVP is to test a product concept in the market, validate customer demand, and gather feedback to improve the product. An MVP can be a rough prototype, a beta version, or an early release of a product that is limited in scope and features.

An MVE (Minimum Viable Experience) is an extension of the MVP concept. The MVE approach is focused on creating a minimum viable experience for customers, rather than just a minimum viable product. The idea behind an MVE is to provide customers with a satisfactory user experience, rather than just a functional product. An MVE is a product that meets the basic needs of customers and provides them with an enjoyable (better) user experience.

In other words, an MVP focuses on delivering a product that solves a specific problem, while an MVE focuses on creating an enjoyable user experience along with solving the problem. An MVE takes into account factors such as usability and design, in addition to functional features.

Note that the concept of MVE is rooted in the Lean Startup methodology, which is based on the principles of continuous innovation and learning. The Lean Startup methodology encourages companies to focus on creating a Minimum Viable Product (MVP) that can be launched in the market quickly and at a low cost. However, viewing an MVP from the lens of an MVE strategy can allow us to test the right assumptions. Based on feedback, we can then make necessary changes to the product or service to improve the user experience even further.

Why is it important to achieve product-market fit before optimizing technical infrastructure & codebase?

PMF is the key to the success of any product or service. Achieving PMF is a gradual process that requires a deep understanding of your target users and their needs. It involves identifying the pain-points of your users, creating a product or service that addresses those pain-points, and validating your assumptions through constant user feedback.

When companies over-invest in their technical capabilities and processes (there should be just enough processes to ensure that they can move rapidly_) before achieving PMF, they run the risk of building a product or service that does not meet the needs of their users. This can result in wasted resources, time, and effort. You might even chase “vanity metrics” that do not move the needle such as total users (instead of total active users) Moreover, optimizing technical infrastructure and the codebase before achieving product-market fit can also limit the company’s ability to adapt and make necessary changes to their product or service based on user feedback quickly making it a competitive disadvantage.

Examples of famous tech companies that followed the MVE approach

There are many famous companies have followed the MVE approach to achieve PMF. Let’s take a look at some of these examples.

Dropbox: When the company was founded in 2007, its founder, Drew Houston, created a simple prototype that allowed him to access his files from anywhere. He then shared the prototype with a few early adopters and gathered feedback. Based on this feedback, he made the necessary changes to the product and launched an MVP. In this scenario, the MVE was creating a system that was easy enough for people to access files from everywhere (not a long onboarding process or a subscription management system to sort out user billing).

Airbnb: The founders, Brian Chesky and Joe Gebbia, started by renting out air mattresses in their apartment to make some extra money. They then created a simple website that allowed people to rent out their homes and apartments to travelers. They then launched their MVP in 2008 and tested the concept by renting out their own apartment to three travelers.

Instagram : When the company was founded in 2010, its founders (Kevin Systrom and Mike Krieger) created a simple photo-sharing app that allowed users to share photos with their friends. This allowed Instagram to test the concept and gather feedback from early adopters.

The benefits of the MVE approach

Cost-effective: The MVE approach is a cost-effective way of testing a product or service in the market. Companies can test the concept and gather feedback from early adopters without investing significant resources in optimizing their technical infrastructure & codebase. This approach allows companies to validate their assumptions and learn from their mistakes before investing significant resources in scaling up their infrastructure and optimising their codebase.

Time-efficient: Companies can test the concept and gather feedback from early adopters quickly. This approach allows companies to make the necessary changes to their product or service and iterate quickly based on customer feedback without over-indexing on technological complexity.

Customer-focused: The MVE approach is a customer-focused way of testing a product or service in the market. By launching an MVE based MVP, companies can focus on creating a product or service that meets the needs of their customers.

Key takeaways

Minimum Viable Experience (MVE) approach allows companies to validate their assumptions, learn from their mistakes, and make the necessary changes before focusing on technical scaling. Whilst scaling is a key factor for growth, there is no point in focusing on this if your business doesn’t take off, or if you don’t have PMF.

By achieving PMF before optimizing their tech, companies can focus on creating a product or service that meets the needs of their customers and generates a sustainable revenue stream- and could make the business more attractive to potential investors.

It’s also important to note that whilst this is a good rule of thumb, there are companies (such as in pharmaceutical industry or in many regulated segments of the market) where having strong technical infrastructure is the right thing to do from the beginning. However, the good news that vast majority of start-ups do not fall into this category.

MVE is a cost-effective, time-efficient, and customer-focused way of testing a product or service in the market. Companies that follow the MVE approach can increase their chances of success by creating a product or service that meets the needs of their customers first, before scaling tech.

Ace Vinayak

When to Self-Host an Open Source LLM vs Use API

Understanding the Trade-Offs

When to Self-Host

When to Use an API

The Hidden Costs

A Practical Decision Framework

Real-World Examples

Key takeaways

Technical Debt: When to Pay It Down vs When to Ignore It

Identifying Technical Debt

Calculating Cost of Delay

Strategic Refactoring

When Technical Debt is Actually OK

A Personal Framework

Key takeaways

Remote Work Boundaries: Creating Structure When Work and Home Blend

Physical Boundaries

Temporal Boundaries

Managing Energy in Remote Settings

Communication Practices for Remote Teams

Personal Experiences and Practical Tips

Key takeaways

Navigating the Financial Mind Maze Using Prospect Theory - The Biases that Shape Our Decisions

The Tale of Prospect Theory

The Impact on Financial Wellbeing

Stock Market Experts: When Drama Trumps Accuracy

What does the data say about professional experts

However:

Prioritisation: Why It is Not Effective Until It Hurts

What is Prioritisation?

Why It’s Not Prioritisation Until It Hurts

Why We Should Say No

Tips for Effective Prioritisation

The Importance of 'No Meetings Days' in the Workplace

The Retirement Savings Crisis: Why Younger Generations are Falling Behind

Problem: The average working household has virtually no retirement savings.

Why is this happening now?

Solution: Change our approach to saving for retirement

Ways to optimise

Balancing Compensated and Uncompensated Risks in Business: A Historical Perspective

What about asymmetric risk?

Further Reading

Minimum Viable Experience: Why it is crucial to achieve product-market fit before optimizing technical infrastructure and codebase

What is Minimum Viable Experience (MVE)?

Why is it important to achieve product-market fit before optimizing technical infrastructure & codebase?

Examples of famous tech companies that followed the MVE approach

The benefits of the MVE approach

Key takeaways