Comfort Is Costly: The Hidden Price of a ‘Modest’ Retirement

Most of us picture a “modest” retirement in Singapore as coasting around an HDB flat, hopping into a taxi now and then, and taking a couple of regional getaways each year. It feels within reach. Yet a survey conducted by OCBC paints a different reality: 75% of Singaporeans aren’t on track for their desired retirement lifestyle, 37% have no plan at all, and only a quarter are fully aligned with their goals. On average, people underestimate their nest-egg needs by 32%, and millennials miss by nearly 39%. Clearly, something deeper than financial ignorance is at play

As we move through our careers and into midlife, subtle psychological shifts alter how we view time, risk and resources, often to our detriment.

1. Present Bias Deepens

With age, the temptation to prioritise today’s comforts over decades‐ahead needs grows stronger. We tell ourselves “I’ll start saving more next month,” yet next month never truly arrives.

2. Positivity “Filter” Intensifies

Experience teaches us to seek out feel-good moments and avoid bad news. That positivity effect dulls our willingness to confront harsh realities: rising inflation, medical bills, or extended long-term care.

3. Risk Aversion Rises

After years on steady payrolls, many retreat to the safety of cash, CPF and fixed deposits. But with inflation at 2–3% annually, sitting on low‐yield assets quietly erodes real wealth.

4. Status Quo Bias Strengthens

Habits harden. Once we routinely check our CPF statements or stick with a single insurance plan, changing course feels unsettling, even when our current path no longer serves us.

5. Overconfidence in “Safety Nets”

A healthy CPF balance or years of salary credits can breed false security. We overestimate how far these fixed sources will carry us and underestimate episodic costs like major home repairs or eldercare.

6. Cognitive Simplification

Our working memory and numeracy tighten with time. We rely on mental shortcuts, “I just need 70% of my last salary”, which rarely account for longer lifespans or volatile market returns.

Together, these forces leave most Singaporeans blissfully underprepared, shaving off nearly a third of the wealth they’ll actually need. For the 25% of individuals on track to meet their retirement goals, the strategy is often an open secret: they diversify their investments and don't rely solely on CPF Life.

However, knowing the solution is one thing; taking concrete steps to execute it is another. The fear of losing money is a significant emotional barrier, causing many to procrastinate on starting their investment journey. I'm no stranger to this feeling. It took me nearly six months of personal research before I finally made my first investment.

The best advice is to take small, manageable steps. Dedicate time to reading and learning first. Then, open a brokerage account to get the administrative part out of the way. When you're ready, invest a small initial amount and simply observe how you react when the market gets volatile. This process is as much about understanding yourself as it is about understanding the market.

In my previous article, I wrote about the example of a Taiwanese lady who earned just S$1,300 a month but started planning at 29. Through fierce discipline, tracking every dollar, living below her means, and funneling tiny sums into diversified investments, she managed to retire at 43. There was no windfall, no exotic strategy. She simply harnessed the power of early compounding and kept her biases in check. Retirement security isn’t about luck or high salaries, it’s about early planning, discipline, and making tough trade-offs. The real danger isn’t dreaming too big; it’s underestimating the cost of living “just enough.

The Unlikely Nomad: How a 57-Year-Old Woman Retired at 43

I recently came across a CNA programe where a self proclaimed 57 year old Taiwanese lady with having "no advantages" due to a low educational background, low income, and not being tall or pretty was able to retire at 43 years old. The lady, named Fanny started her retirement planning at age 29 years old with a starting salary of just 30,000 TWD (around $1300 SGD), so it took her only 14 years to achieve FIRE which to me is quite amazing. The usual stories I heard of early FIRE achievers were either working in tech, investment bankers or working in some high paying industry, so Fanny's story was kind of refreshing since I also have the same goal to achieve FIRE. I strongly suggest fellow readers who aim to achieve FIRE to view the video at this link.

 

Here is a summary of how she managed to retire at 29 years old:

 

1. Early Planning and Discipline: At age 29, Fanny made two crucial decisions: she began saving as much as she could, and she decided on a minimalist international nomad lifestyle. She emphasizes that financial management is a long-term endeavor, not a quick path to wealth. She travels frequently and most of her belongings can fit readily into a backpack and she has developed several money saving skills over the years such as cooking simple meals using only a microwave.  Along the way, it does take a lot of discipline to also prevent yourself from falling into the lifestyle inflation trap, hence her financial discipline is really admirable. 

2. Aggressive saving and strategic investment: She mentioned she saved more than 50% of her savings and invested in mutual funds and insurance policies and her investments managed to generate about 600,000 TWD (around $26,000) annually for her. Sometimes you don't really need to over complicate your investments or chase the hottest stock. You just need a lot of discipline and patience to stay the course.

3. Decision Against Property Ownership: Fanny faced a choice between saving for a home and saving for retirement. She realized that buying a home might leave her with no cash and no retirement fund in old age, potentially needing social worker assistance. Instead, she chose to prioritize saving for retirement and chose to stay in co-living hostels which are more affordable as it's a pretty well known fact that Taiwanese face an uphill battle to own a property due to high property prices and stagnant wages. So after coming back from overseas, she will stay in the hostel for a few months before taking flight again. Another advantage of living in a hostel is that she doesn't need to sign landlord contracts and pays no management fees or utility bills. I think her decision not to own a home is the biggest reason she was able to reach FIRE so early. 

She has also identified a wellness village where she plans to settle once she's ready to end her nomadic lifestyle. Her story offers several valuable insights, particularly the importance of starting retirement planning early and maintaining discipline to stay on track. While her decision to forgo homeownership and live in hostels represents a creative approach to achieving FIRE, it wouldn't suit my lifestyle as an introvert who values personal space. However, the most compelling takeaway from her journey is the freedom it provides which is having complete control over your life and the ability to pursue whatever path you choose.

The Company That Built ChatGPT's Brain (But Forgot to Use It): Is Google Still Worth Investing

I have been a Google investor for some time and with all the hype in recent times on AI, I couldn't help but wonder what if Google had fully capitalized its considerable advantage in the early stages; it would have been miles ahead of the AI race. 

Well before ChatGPT burst onto the scene, Google had already staked its claim as a leader in artificial intelligence. In fact, it declared itself an “AI-first” company as early as 2016. Below are some of the foundational initiatives that shaped Google's approach to AI long before generative chatbots became mainstream:

Google Assistant

Launched in 2016, Google Assistant marked a pivotal moment in voice recognition and natural language processing. Embedded across Android devices, smart speakers, and other platforms, it allowed Google to deploy conversational AI at massive scale—collecting real-world data to refine its dialogue systems.

TensorFlow

Released in 2015, TensorFlow is Google’s open-source machine learning framework. It quickly became a staple for AI developers worldwide, fostering innovation both within Google and across the broader research community. This move helped cement Google's influence in the global AI ecosystem.

Magenta

Part of Google AI, the Magenta project explored deep learning in creative contexts—generating music, visual art, and more. Started in 2016, it signaled Google’s intent to push AI beyond analytical functions into expressive, artistic domains.

LaMDA (Language Model for Dialogue Applications)

Unveiled internally in 2021, LaMDA was Google’s conversational AI designed for fluid, open-ended dialogue. While its capabilities were on par with ChatGPT, it wasn’t made widely available due to concerns around safety, ethics, and potential misuse—highlighting Google’s cautious stance on public deployment.

Google Brain & DeepMind

Google Brain (founded in 2011) and DeepMind (acquired in 2014) formed the bedrock of Google’s AI research. DeepMind’s AlphaGo famously defeated top human players in 2016, showcasing breakthroughs in reinforcement learning. Both divisions were instrumental in pioneering neural networks and machine learning long before generative models gained attention.

AI in Search & Advertising

Google had already been baking AI into its core products for over a decade. A prime example is BERT (Bidirectional Encoder Representations from Transformers), introduced in 2018, which improved Search by better interpreting user queries. This technology was an early application of the transformer architecture that later powered models like ChatGPT.

The Transformer Breakthrough

In 2017, Google introduced the Transformer architecture through the landmark paper “Attention Is All You Need” by Vaswani et al. In my view, this is perhaps Google’s most important AI innovation as this innovation revolutionized natural language processing and became the backbone for modern AI models including ChatGPT, LaMDA, and BERT. Without the transformer, there would probably be no ChatGPT. This was such a waste because the creation of the transformer gave Google a massive head start which they failed to capitalize. 

Despite having an enviable portfolio of AI research and product, chose to hold back rather than go full steam ahead. Below are some possible reasons the tech giant held back: 

Ethical and Safety Caution

Past controversies cast a long shadow. Google faced backlash after its 2018 Duplex demo, where its AI made lifelike phone calls, sparked privacy concerns. Project Maven, a military AI initiative, triggered employee protests. The high-profile departures of AI ethicists like Timnit Gebru further raised internal and public scrutiny. With LaMDA nearing launch, Google chose restraint over risk, wary of ethical pitfalls and reputational damage.

Protecting Its Core Business

Google’s advertising empire relies on users clicking search links. A chatbot offering direct answers could short-circuit this model, threatening the very foundation of Google’s profits. That kind of disruption, even in the name of innovation, was too risky to accelerate unchecked.

Bureaucracy and Risk Aversion

Google’s vast size came with internal inertia. Product decisions were subject to intense scrutiny from legal, PR, and policy teams. In contrast, OpenAI, with its leaner structure and singular focus, could experiment and iterate faster, turning bold ideas into viral breakthroughs.

LaMDA: A Missed Opportunity

LaMDA had the tech to challenge ChatGPT, but Google paused its public release. LaMDA was based on the transformer architecture as mentioned earlier so the moment for dominance slipped away while competitors seized it.

Q2 Performance

Alphabet reported strong results for Q2 2025, with revenues, profits, and growth across all key segments exceeding analyst expectations.

Key highlights:

Revenue: $96.4 billion, up 14% year over year (13% in constant currency), beating consensus estimates.

Net Income: $28.1–$28.2 billion, up 19% year over year.

EPS: $2.31, up 22% year over year and well above the $2.18 expected by analysts.

Segment performance:

Google Services: Revenue up 12% to $82.5 billion, driven by Google Search (up 12% to $54.2 billion), YouTube ads (up 13% to $9.8 billion), and subscriptions/platforms/devices (up 20% to $11.2 billion).

Google Cloud: Revenue up 32% to $13.6 billion, supported by strong enterprise demand for AI and cloud services. Cloud backlog and profitability both reached records.

Advertising: Total ad revenue was $71.34 billion, surpassing expectations.

Profitability and cash flow:

Operating income: Up 14%; operating margin at 32.4%.

Free cash flow: $5.3 billion for the quarter; $66.7 billion trailing twelve months.

Cash & securities: Ended Q2 with $95 billion on hand.

Strategic and product updates:

AI impact: AI features like Gemini and AI Overviews were cited as major growth drivers, positively impacting all businesses, especially Search and Cloud. 

Key factors include:

Explosion in user base: The Gemini app surpassed 450 million monthly active users in Q2 2025, up from 400 million in May and showing over 50% daily request growth quarter-over-quarter. This massive adoption has been fueled by its integration within Android, Search, and launch as a standalone app.

Product integration and reach: Gemini has been embedded across many core Google products, Search, Maps, Workspace, YouTube extended its reach to billions of users. In Search alone, features like AI Overviews (AI-generated summaries) now serve over 2 billion monthly users, making AI assistance a default part of routine search behavior.

Cloud growth and enterprise AI: Gemini also powers much of Google Cloud’s enterprise AI offerings, driving 32% year-on-year Cloud revenue growth as over 85,000 businesses integrated Gemini AI tools for productivity and automation.

Content creation: AI-enabled tools like Veo (video generation) and Workspace smart features, built on Gemini, saw explosive content creation, for example over 70 million AI-generated videos since May 2025.

Driving monetization: High engagement and time spent with AI features increased stickiness and opened pathways for future monetization, such as premium subscriptions, upselling in Cloud, and AI-powered advertising improvements.

Increased capital expenditure: Alphabet raised its 2025 CapEx outlook by $10 billion to $85 billion, reflecting surging demand for AI infrastructure and cloud services.

Stock reaction and outlook:

Results beat expectations, but the stock saw a modest drop in after-hours trading, possibly due to concerns over higher spending plans for AI and infrastructure.

CEO Sundar Pichai emphasized continued investment in AI and described broad momentum in all core business lines.

Overall, Alphabet’s strong top- and bottom-line growth was primarily driven by continued strength in Search, significant gains in Cloud/AI, and robust performance in YouTube and subscriptions. The company is spending aggressively on AI infrastructure to sustain and expand this momentum

Breakup risk

The potential breakup of Google, driven by U.S. and EU antitrust actions, is a landmark case targeting its monopolies in search and ad tech, with regulators proposing divestitures of Chrome, Android, or ad tools like AdX to curb its dominance; this threatens Google’s $237 billion ad revenue and AI strategy, which relies on integrated data from its ecosystem to power innovations like Gemini and AI Overviews, while also setting a precedent for regulating Big Tech, with a final ruling expected by August 2025 that could reshape Google’s business and the broader tech industry.

This case would likely drag on for years and could result in stock price volatility. Hopefully Google's case would end up like the anit-trust case faced by Microsoft from 1998 to 2000 which Microsoft eventually won. 

Ending thoughts

Although Google failed to fully capitalize on their earlier head start, I still believe it's still a dominant player in the AI space. I have been dabbling with Google AI products like Google AI Studio and Notebook LM and I have been impressed so far. Google AI Studio is a cloud-based platform that lets users interact with Gemini, Google’s family of advanced multimodal generative AI models. Notebook LM is one of their latest offerings and it’s an AI-powered research and note-taking tool that allows users to interact deeply with their own documents. One of its cool features even allows the user to convert the documents into podcast-style summaries for on-the-go learning. 

I feel the stock is still undervalued at this stage and I have been steadily adding shares during the dips. There is nothing I can do regarding the antitrust case but just wait and see how the situation unfolds. Please note this is not investment advice, so please do your own diligence before investing.

Investing Off the Beaten Path: Scandinavia Big Gun Kongsberg Gruppen

 Today, l’m exploring something a little different: an interesting Norwegian defense company. If defense stocks or European markets aren't your cup of tea, feel free to skip this one. Please note this is not investment advice and do your own diligence when investing.

1. Company Overview

Kongsberg Gruppen began in 1814 as a state arms factory, earning global acclaim with its Krag–Jørgensen rifle before diversifying into marine equipment and automotive components. By the 1950s, it was producing advanced air-defense cannons and, in 1972, the Penguin anti-ship missile. A 1987 export-control scandal prompted the defense arm’s spin-off as Norsk Forsvarsteknologi, which listed publicly in 1993 and reclaimed the Kongsberg Gruppen name in 1995. The Norwegian government has a 50% stake in the company and it operates three core divisions—defense & Aerospace, Maritime and Discovery—leveraging stable state backing and robust R&D to deliver high-margin missiles, naval systems and industrial software, well positioned for growth amid rising defense budgets and industry digitalization.

2. Business Model & Strategy

Kongsberg operates through three primary business areas: Kongsberg Maritime, Kongsberg defense & Aerospace, and Kongsberg Discovery.

Kongsberg Maritime delivers advanced systems for automation, propulsion, navigation, and remote vessel operations. It is a pioneer in autonomous shipping, notably through its collaboration with Yara International on the Yara Birkeland, the world’s first autonomous and fully electric container ship. KM also supports offshore energy ventures with solutions for dynamic positioning, subsea robotics, and hybrid power systems, serving key clients in shipping, offshore wind, and naval sectors.

Kongsberg defense & Aerospace is a leading supplier of advanced defense technologies, particularly remote weapon systems and precision-guided missiles. Its Naval Strike Missile (NSM) and Joint Strike Missile (JSM) are widely adopted by NATO allies, including the U.S. Navy and Royal Norwegian Navy. The division is also a key subcontractor in the F-35 fighter jet program and provides satellite technology through its Kongsberg NanoAvionics unit. Strategic partnerships with Lockheed Martin, Raytheon, and the European Space Agency further anchor its international presence.

Kongsberg Discovery, established in 2023 following a spin-off from the Maritime division, specializes in ocean exploration, seabed mapping, and subsea monitoring. It is the industry leader in high-resolution multibeam sonar systems, and its technologies are used globally in deep-sea research, offshore energy, and fisheries management. Notably, the division has supported major initiatives like the Seabed 2030 project, which aims to map the entire ocean floor by 2030.

3. Financial Analysis

Below is a summary of the financial performance:

2024 Financial Performance:

Revenue Growth: Operating revenues increased 20.3% to NOK 48.9 billion from NOK 40.6 billion in 2023.

Order Intake Surge: Rose 34.3% to NOK 87.8 billion, boosting order backlog by 44.5% to a record NOK 127.9 billion.

Profitability Boost: Net profit grew 38% to NOK 5.1 billion from NOK 3.7 billion, with a strong return on equity at 32%.

Cash Flow Strength: Generated NOK 12.9 billion in free cash flow, reflecting high operational efficiency.

Q2 2025 Results:

Revenue Increase: Revenues up 20% year-on-year to NOK 13.9 billion.

EBIT Growth: EBIT rose 32.5% to NOK 1.92 billion, with an operating margin of 13.8%.

Maritime Division: Revenue grew 7% to NOK 6.39 billion; order intake at NOK 7.52 billion (book-to-bill ratio 1.18); EBIT margin fell to 11.2% due to offshore wind and mineral market pressures.

Discovery Segment: Revenue up 21% to NOK 1.23 billion; EBIT margin expanded to 18.8%, driven by subsea acoustics demand and Sonatech acquisition.

Defense & Aerospace: Revenue surged 38% to NOK 6.12 billion, fueled by missile and air-defense contracts (e.g., with Germany); new orders at NOK 9.84 billion; EBIT margin slightly down to 14.3%.

Despite posting strong growth  and a record order backlog, the stock crashed more than 10% due to concerns on rising costs, a dip in cash reserves, and quarterly revenue that fell just short of analyst expectations. Mixed analyst sentiment and the stock’s high valuation also contributed to the sell-off, as some investors took profits after a strong run-up.

4. Risks & Challenges

Kongsberg Gruppen faces several operational and macroeconomic risks. Its reliance on NATO-aligned defense contracts exposes it to shifting geopolitical priorities and potential budget cuts. As a high-tech manufacturer, it depends on complex global supply chains, making it vulnerable to component shortages and logistical disruptions. 

Currency fluctuations, especially between the NOK, USD, and EUR, can also affect profitability. Lastly, the rapid pace of innovation in defense, AI, and autonomy requires constant R&D investment to maintain competitiveness and avoid being outpaced by faster-moving rivals. Another point to note is that despite Norway being a resource rich and fiscally stable country, the NOK is not a safe haven and its value is often tied to energy markets and can be volatile in market downturns. 

5. Conclusion 

Currently I do have a small position in Kongsberg Gruppen via IBKR (Oslo Stock Exchange ticker KOG)  as I look to diversify my investments away from the US market. I also added on my position when the stock plunged around 10% after the announcement of Q2 results. Honestly even with the 10% drop, I still feel the stock is still overpriced but this is an investment which I’m comfortable to hold long term due to the Norwegian government holding a 50% stake.

Buying the Dip or Dipping Too Deep? Lessons from a PayPal Investment Ride

Over the past few years, I’ve had a wild ride with PayPal stock. I bought in during the highs, averaged down through the lows, and sold near the bottom. This journey has been humbling, and more importantly, educational.

Below are some key lessons which I learned.

Lesson 1: Random Buying and Selling Without a Framework

I started buying PayPal in early 2021 at $245.50, believing it had dipped from its highs and was a bargain. Then I added more at $271, only to watch it nosedive as Wall Street turned sour on fintechs. Instead of stepping back and reassessing, I doubled down multiple times—buying more at $205, $188, $167, and so on, all the way to $67.50. Along the way, I also sold some holdings at $131 and $91, which totally reflected my ignorance. Eventually, I panicked and decided to sell off most of my holdings at $57.55 in Feb 2024.

The mistake: I let emotions dictate my trades. I bought because prices were falling, not because I had high conviction in the business. I sold out of frustration when prices hit a new low, not because the fundamentals had changed for the worse.

The lesson: Don’t fly blind. Every trade needs a mental framework: Why am I buying or selling? What’s the long-term view? What would change my mind? Without these, it’s too easy to fall into the trap of “buy the dip” and “sell in despair.”

Lesson 2: Averaging Down Without Understanding the Business

Averaging down can be powerful, but only when you truly believe in the business. In my case, I didn’t.

PayPal was and still is under immense competitive pressure from the likes of Apple Pay, Google Pay, Block's Cash App, and even new platforms emerging globally. When eBay phased out PayPal as its default payment processor, it raised a red flag. Despite all this, I kept buying.

Why? Because the price kept dropping, and I wanted to “recover” my losses.

The mistake: I was speculating, not investing. I didn’t truly believe PayPal had a strong economic moat. I didn’t study its financials, customer retention metrics, or innovation pipeline. I was just hoping for a rebound.

The lesson: Before you buy a stock, ask yourself: Do I understand this company? Do I believe it can grow and compete over the next 5–10 years? If the answer is “not really,” it’s speculation not investment.

Lesson 3: Chasing Hype and Valuation Disconnects

In hindsight, my initial purchases were fueled by pandemic-era hype. PayPal surged as online spending exploded. The narrative was compelling: digital wallets, touch-free payments, e-commerce boom.

But the valuation became stretched and I didn’t question it. I bought at elevated prices without thinking, Is this growth sustainable?

When economies reopened, PayPal's user growth slowed. The post-pandemic world looked different, and the company's prior momentum faded.

The mistake: I bought into the narrative, not the numbers. I assumed the good times would continue and didn’t question whether the price reflected future potential.

The lesson: When a stock is surging, pause and assess: Is this growth real and sustainable? Or is it driven by temporary trends and market excitement? Always weigh hype against fundamentals.

The most painful mistake: Selling at the Bottom

I have since divested my entire Paypal holdings at a loss of almost 40%.

I didn’t have an exit strategy and I let frustration and fatigue guide me.

The lesson: Selling should be as intentional as buying. Exit based on valuation, business deterioration, or better opportunities not emotion.