Most people read Meta’s acquisition of Manus as another step in the AI agent arms race.

Yes and no.

From a VC lens, this was not a bet on intelligence.

It was a bet on execution scar tissue — something that can’t be rushed, simulated, or cheaply rebuilt.

This was never about “the best model”

Meta already has:

• Strong foundation models
• Massive global distribution
• hardware endpoints (mobile, VR, wearables)

What Meta does not have the luxury of doing is learning from execution failures publicly across billions of user interactions.

Manus had already done that.

The real question isn’t “why agents?”

It’s “why Manus?”

Here’s the non-obvious answer:

Manus crossed a path-dependent threshold where execution reliability — not reasoning quality — became the moat.

Once a company reaches that point, the ‘build vs. buy’ debate stops being a technical decision and becomes a time-risk and reputational-risk decision.

What Manus learned that others can’t shortcut

Most AI agents work in controlled environments:

clean prompts, trained users, bounded workflows, human-in-the-loop recovery.

Manus appears to have learned how agents behave in hostile, real-world environments — the kind Meta operates in.

Also Read: How SMEs can compete like big corporations with the right financial intelligence platform

Three lessons matter:

• Failure recovery matters more than first-pass intelligence: Real users are ambiguous. Tools break. Instructions are incomplete. Manus learned how to recover without hallucinating or escalating to humans.
• Long-horizon execution is harder than reasoning: Execution requires memory, intent persistence, and recovery across sessions — where most agent demos collapse.
• Trust collapses faster than models improve: In consumer platforms, silent failure isn’t bad UX — it’s a trust breach.

Manus learned how to fail visibly, explain minimally, and recover credibly.

None of this is benchmarkable.

All of it is learned the hard way.

Why the acquisition was inevitable

Meta could rebuild these capabilities.

What it couldn’t afford was:

• Relearning failure inside WhatsApp, Instagram, or wearables
• Exposing billions of users to that learning curve
• Absorbing the reputational risk of agents behaving badly at scale

So the real decision wasn’t “can we build this?”

It was “Can we afford to relearn this?”

The answer was no.

The signal for founders and investors

General-purpose AI agents are now a platform game.

Venture-backable paths narrow to:

• Deep vertical agents with real domain lock-in
• Infrastructure layers (orchestration, observability, compliance)
• Acquisition-grade teams with real execution scars

The era is shifting from model competition to execution control.

And the hardest asset to replicate isn’t intelligence — it’s the accumulated cost of being wrong in the real world.

That’s what Meta bought.

—

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Private equity has a religion: operational excellence through systematic value creation. The data appear unassailable. McKinsey reports that operationally-focused GPs generate IRRs two to three percentage points higher than peers. Bain finds that structured value creation delivers 3.0x returns versus a 1.9x industry average—a 58 per cent performance premium.

Here’s the heresy nobody wants to admit: the same discipline that creates outperformance is now destroying more value than it generates.

The numbers behind the orthodoxy’s failure

Simon-Kucher’s 2025 study reveals what consulting firms won’t tell clients: two-thirds of private equity (PE) value creation initiatives fail to deliver expected outcomes. One in three business improvement programs produces zero measurable return. In value-destructive deals, more than 10 per cent of employees depart immediately post-close, with the worst transactions losing 21-30 per cent of key talent.

Most damningly: 75 per cent of portfolio company CEOs are replaced within two years—not because they’re incompetent, but because they resist the new owner’s systematic playbook. When AlixPartners surveyed PE practitioners, 75 per cent reported direct experience with portfolio failures caused by CEO-investor misalignment. Yet only 13 per cent conduct cultural evaluation during diligence.

The industry identifies the problem, then systematically engineers the conditions that produce it.

What actually kills value

Simon-Kucher dissected why value creation initiatives fail:

• Poor implementation: 53 per cent
• Unrealistic business cases: 37 per cent
• Portfolio company resistance: 35 per cent

Notice what’s absent? Insufficient KPIs. Inadequate governance. Too little systematisation. The failure mode isn’t under-management—it’s over-management imposed before organisations can absorb it.

I’ve watched this pattern destroy dozens of companies across Southeast Asia. A founder-led B2B software company generating 40 per cent annual growth gets acquired by a PE firm deploying its “proven playbook.” Within six months, board decks balloon from 15 to 60 slides. Hiring approvals stretch from days to three weeks. The product roadmap freezes pending “strategic review.”

Twelve months later, revenue growth has halved, the CTO has quit, and the PE firm convenes an urgent off-site to diagnose “execution challenges.” The playbook wasn’t wrong. The timing destroyed the business.

Also Read: The culture conundrum: Why private equity’s best CEOs still fail and how Moneyball thinking can fix it

The elite firm counter-strategy

Here’s what separates genuine 3x performers from systematisation zealots: they treat frameworks as tools to amplify momentum, not replace it. They recognise that premature systematisation in high-growth companies is value destruction wearing the costume of best practice.

Top-quartile firms do something radically different in year one. They watch. They resource. They remove obstacles. They preserve the operational momentum that justified the multiple acquisitions. Only after stability is achieved do they introduce frameworks—selectively, where they enhance rather than constrain performance.

Bain’s research inadvertently proves this. The 3.0x performers engaging in “structured value creation” aren’t imposing rigid KPI frameworks. They’re making surgical interventions: replacing one genuinely inadequate executive, funding a capital-constrained growth channel, and implementing pricing discipline where none existed. These aren’t cookie-cutter implementations—they’re strategic decisions executed with restraint.

Contrast this with 1.9x performers who arrive with 100-day plans and systematic frameworks deployed identically across portfolio companies regardless of context. Their religion is a process. Their blind spot: process imposed before momentum is established kills the growth they acquired.

“At the end of the day, it’s people and culture that decide whether a system succeeds or fails.”

The advent international lesson everyone misses

The industry loves citing Advent’s ownership of BSV, which doubled revenue growth to 20 per cent annually and expanded EBITDA margins from 20 per cent to 30 per cent. What case studies omit: Advent didn’t impose comprehensive frameworks on day one. They made two interventions—international expansion and pricing optimisation—then resourced them aggressively while leaving the operational engine intact.

This is surgical execution, not systematic transformation. The discipline came from knowing what not to systematise—preserving the sales culture and product velocity that created value in the first place.

Why this matters now

Private equity faces its harshest environment in 15 years: US$3.6 trillion in unrealised value across 29,000 unsold companies, distributions at historic lows, and acquisition multiples at 12x EBITDA. In this context, the industry’s reflexive answer has been more systematisation—more frameworks, more governance, deployed earlier and more uniformly.

The data says this orthodoxy is failing. CEO turnover approaches 75 per cent within two years. Performance gaps between top-quartile and median funds continue widening—not because median managers lack frameworks, but because they’ve mistaken process for performance.

Also Read: Why private credit is becoming the hottest alternative for smart investors

McKinsey’s organisational alignment research remains valid: culture explains 58.6 per cent of variance in execution outcomes. But here’s the inversion consultants won’t acknowledge: you cannot systematise culture into existence. Culture precedes systems, not vice versa.

The firms generating genuine alpha have learned what the rest refuse to accept: systematic value creation is timing-dependent, not universally applicable. Deploy frameworks too early, and you destroy growth. Deploy them when leadership is stable, baselines are established, and organisations have absorption capacity—and systems amplify performance.

The uncomfortable truth

As Bain observes, the cost of market-beating returns continues rising as fees compress. Winners won’t be those with the most sophisticated frameworks but those with judgment to know when frameworks enable versus suffocate performance.

The industry sold the world on systematic value creation. The uncomfortable truth is that the system itself has become the primary destroyer of value. The competitive advantage has become a vulnerability.

Elite firms have discovered that the hardest discipline isn’t imposing rigour—it’s having the restraint to preserve entrepreneurial velocity when every instinct says to systematise faster. That judgment, unglamorous and maddeningly contingent, is now the true source of private equity alpha.

The beatings will continue until morale improves. Or until the industry learns that its most sacred principle requires the one thing PE hates most: patience.

This article is part of David Kim’s Value Creation column. It sits alongside the Asia Value Creation Awards, which aim to recognise PE and VC teams driving long-term, fundamentals-led value creation across the region.

—

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We talk about technology as if it separates us. Phones are replacing conversations. Screens replacing faces. AI is replacing humans.

But maybe the real question is not whether AI makes us lonely. Maybe it is how we use it to feel less alone.

The quiet kind of loneliness

Loneliness today does not always look like being alone. It can happen in crowded rooms, busy offices and even online communities. We scroll, we watch, we like, but we do not always feel seen.

That is why connection has become the new happiness. And that is where AI, surprisingly, can help. Not by pretending to be human, but by helping humans rediscover each other.

When AI becomes a mirror

I have watched many learners, especially midlifers, use AI for the first time. At first, they are shy. They talk to it softly, like a stranger they are not sure they can trust.

Then something shifts. They begin to write. They begin to share. They begin to remember. They tell stories they had forgotten,
describe feelings they had never spoken about, and rediscover parts of themselves they thought were lost.

It is not because AI understands them perfectly. It is because AI listens without judgment. That kind of listening gives people courage to speak again, and that is where healing begins.

Connection through creation

A dear friend once told me about a project she started with her ageing mother. Her mother had always dreamed of running a small shop, but life, family and time never allowed it.

When her health began to fade, my friend helped her create that dream online. They built a simple e-shop together using free digital tools. They took photos, wrote short product descriptions and posted them on social media. Soon, friends began to notice, comment and buy small items.

Also Read: Why Singapore startups are sleeping on their secret weapon (spoiler: it’s not AI)

It was not powered by complex AI systems. It was powered by love, curiosity and technology made simple by AI in the background. The shop gave her mother a sense of purpose. It gave her daughter a memory she will never forget.

For a short while, they lived their mother’s dream together. That is what connection through creation truly means. Technology is not only about efficiency. It is about giving people one more way to feel alive, seen and connected.

AI and emotional literacy

AI cannot replace empathy, but it can remind us how to practice it. It can help us reflect, write and reach out. It can turn thoughts into voice, ideas into visuals and memories into legacies.

Used with intention, it becomes a tool for emotional literacy, a way for people to understand what they feel and express it safely.

When I see participants use AI to share stories about their lives, they often say, I did not know I still had so much inside me.
That is not technology at work. That is humanity reawakened.

The gentle reminder

We were never meant to compete with machines. We were meant to grow with them.

AI can help us create, express and connect, but it is still our emotions that give it meaning.

So do not fear it. Use it to find your voice, your joy and your people because the future of happiness is not artificial. It is amplified.

—

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Every year, new reports flood LinkedIn proclaiming the “Top Skills for the Future.” AI literacy. Digital fluency. Strategic thinking. Emotional intelligence. Cross-cultural communication.

The lists grow longer. The outcomes remain the same.

Despite record investment in training, many organisations still face leaders who avoid difficult conversations, sales teams who struggle to handle objections, and managers who lack the confidence to lead through change.

Why?

Because the future of work is not being limited by which skills people know about — it is being limited by which skills people have actually practised in real-life conditions.

The real bottleneck: Transfer to action

The hardest part of learning has never been access to information. We live in the most knowledge-rich age in human history.

The real challenge is turning insight into action:

• Saying the difficult thing when emotions run high
• Navigating uncertainty when there is no playbook
• Leading inclusively when values clash
• Building trust across distance, cultures, and hierarchies

These moments do not come with slides or pause buttons. They demand human fluency — presence, judgment, emotional regulation, persuasion, and empathy — expressed in seconds, not theories.

Why content is not enough

Most training still optimises for content delivery. But the skills of the future are not cognitive alone — they are behavioural and emotional.

No one becomes persuasive by watching a video on persuasion. No one becomes resilient by reading a resilience article. No one becomes a strong negotiator by ticking boxes in a quiz.

These competencies require experience, but experience in real life is risky, expensive, and inconsistent.

This is the core contradiction of modern learning: Skills require practice, but workplaces make failure unsafe.

So learners retreat into passive learning — understanding what to do intellectually, but never integrating it into behaviour.

Also Read: The future of work is microlearning: How bite-sized education is transforming the workplace

The rise of safe practice

The next decade of skills development will not be defined by what people watch or read, but by what they repeatedly practice.

Safe, immersive practice environments will become the standard for developing:

• Leadership under pressure
• High-stakes communication
• Negotiation and conflict management
• Cross-cultural and inclusive leadership
• Decision-making in ambiguity

This is where AI-powered experiential learning enters the stage.

AI roleplay allows learners to step into realistic future-work scenarios — testing language, tone, judgment, and emotional intelligence — without social risk. They can pause, reflect, restart, try different approaches, and gradually build confidence through safe exposure.

Learning shifts from passive intake to active rehearsal. From knowledge tests to capability building.

Depth will matter more than speed

As microlearning and social video accelerate bite-sized content consumption, there is a hidden danger: speed without depth produces surface competence.

Future skills are not superficial hacks. They involve:

• Emotional nuance
• Cultural complexity
• Ethical judgment
• Relationship-building

Developing them requires academic rigour and psychological safety, not dopamine-driven quick wins.

Learners need realistic scenarios designed with the complexity of real leadership challenges, not simplistic chatbots that reward short responses.

The skill of the future is practice itself

Ironically, the single most important future skill may not be persuasion, negotiation, or empathy.

It may be developing the ability to learn experientially — to enter challenging simulations, reflect honestly, take feedback seriously, and try again.

As volatility increases and job roles evolve faster than course content can update, real competitiveness will come from learning velocity — the speed at which individuals can build new behaviour under changing conditions.

From learning to becoming

The future of work does not require people who know more theories.

It requires people who are ready to:

• Speak when conversations get uncomfortable
• Lead when answers are unclear
• Decide when outcomes are uncertain
• Connect when differences emerge

These are not knowledge challenges.

They are practice challenges.

The organisations that win the next era will be the ones that move beyond training employees to consume content and instead empower them to become capable through experience.

Because the future does not belong to those who study skills — it belongs to those who practice them.

—

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In Game of Thrones, there’s a classic line: “Chaos isn’t a pit; chaos is a ladder.” This metaphor perfectly captures the current state of retail. As market structures fragment, traditional rules are shattering, creating opportunities for new, more efficient models to emerge.

In China, the most powerful new rung on that ladder is Instant Retail.

The promise of “everything delivered in 30 minutes” has become a daily standard in Chinese cities. It has forged new consumer habits: no going downstairs, no stockpiling, and no planning. This shift is also forcing retailers to fundamentally re-examine their supply chains, store layouts, and operational models.

As one veteran supermarket operator in China lamented, “My competitor is no longer the supermarket down the street. It’s every single app on consumers’ phones.”

Does this sound familiar? It should.

From the chaotic vibrancy of Jakarta to the vertical density of Singapore, Southeast Asia is mirroring China’s trajectory. As super apps like Grab, GoTo, and Shopee pivot from aggressive expansion to sustainable profitability, they are approaching the same operational inflection point that has just reshaped China.

By analysing China’s roadmap, Southeast Asian players can see their own future and prepare for the inevitable operational challenges ahead.

Beyond Supercharged Delivery

Many mistake Instant Retail for a simple upgrade of food delivery. Superficially, they’re right. The same riders who deliver food and drinks now deliver groceries, cosmetics, and iPhone chargers within 30 mins. But to see it as just “do-it-all delivery” is to underestimate its ambition.

To grasp its true meaning, consider the specific use case. When the cat food runs out, or you need medicine late at night, the moment you click “buy,” you aren’t just purchasing a product. You are purchasing instant gratification and certainty.

Instant Retail fills the time gap left by traditional e-commerce’s “next-day delivery” and shatters the spatial constraints of “must-visit” physical stores. It shifts shopping behaviour from pre-planned events to impulse-driven “micro-demands.”

Also Read: The canary in Singapore’s retail coal mine is ‘kiasu’

While Southeast Asia has seen the rise of “Quick Commerce” (Q-Commerce) via capital-intensive dark stores, China has evolved into a more sustainable, asset-light phase: the Store-as-Fulfilment-Centre (SFC) Model.

Instead of building expensive new warehouses, the Chinese model involves the digital transformation of existing retail terminals, such as supermarkets, convenience stores, and pharmacies, turning them into dual-purpose hubs. This pushes inventory closer to the consumer without the heavy capex of building new infrastructure.

A perfect storm: Why now?

The rise of Instant Retail in China was not accidental. It was driven by a convergence of structural shifts, conditions that are now replicating across Southeast Asia.

Market saturation and the quest for growth

In China, as traditional e-commerce saturated and customer acquisition costs skyrocketed, Instant Retail emerged as the new engine for growth. A similar pattern is unfolding in Southeast Asia. As the region’s digital economy matures, super apps are pivoting to high-frequency, essential categories (like groceries and pharma) to drive user retention and strengthen unit economics.

Technological maturity

This is more than just “putting a supermarket online”; it is a complex systems engineering project where AI, Big Data, and IoT form the operational backbone.

Take the intelligent TMS (Transportation Management System) as a prime example. By leveraging algorithms to analyse historical sales, real-time traffic, and store demand, retailers can dynamically optimise logistics. Industry data from retail tech provider Dmall indicates that such systems can boost vehicle load rates from 65 per cent to 85 per cent. For the end consumer, this back-end intelligence translates into reliability—a standard that SEA shoppers increasingly value over mere speed.

Urban density

Just as China’s “15-minute convenient living circles” policy catalysed this model, Southeast Asia’s vertical urban density and robust two-wheel logistics networks provide the perfect fertile ground for Instant Retail to thrive.

From point of sale to point of fulfilment

The core of this revolution is the redefining of the physical store.

Under the Instant Retail model, a brick-and-mortar store is no longer just a place to shop; it is a local fulfilment centre. Its service radius expands from 1km to 5km, allowing a legacy retailer like 7-Eleven to capture revenue from customers who never walk through its doors.

However, this opportunity comes with a massive “Digital Divide.” Whether it is a convenience store in Guangzhou or a supermarket in Bangkok, the operational pain point is identical: how do you manage orders from multiple apps without creating inventory chaos?

When a single store must process orders from its own app, Grab, Foodpanda, and Shopee simultaneously, backend complexity explodes. Without real-time synchronisation, inventory data lags, leading to overselling and customer cancellations.

To survive this race against time, a unified backend infrastructure is no longer optional. It is operational bedrock.

The industry solution to this fragmentation is the adoption of a “unified commerce operating system”. The technical logic focuses on centralisation: channelling orders from disparate external platforms into a single internal processing stream. Instead of juggling multiple devices, store staff utilise one standardised app for picking and packing. Crucially, once an order is fulfilled, the system triggers an immediate, automated inventory update across all sales channels.

Also Read: The future of retail is autonomous: Securing agentic AI for smarter, safer growth

A clear deployment of this strategy can be seen at 7-Eleven South China. Operating a network of nearly 2,000 stores, the retailer leveraged Dmall OS as its digital backbone to integrate third-party giants like Meituan and Douyin (TikTok) with its own private mini-program. This integration enabled real-time synchronisation of inventory, pricing, and promotions, effectively transforming each physical convenience store into a digitised, high-efficiency distribution hub.

Conclusion

China’s Instant Retail story serves as a blueprint for Southeast Asia’s next chapter.

The path to profitability lies not in building more dark stores, but in empowering existing brick-and-mortar retailers to become efficient nodes in the digital network.

For traditional retailers, the “moat” of physical location is drying up. To survive, they must stop viewing online orders as a disruption and start viewing their stores as digitally connected fulfilment centres.

In the end, retail evolution is not about geography; it’s about efficiency. Whoever can first integrate the fragmented network of people, product, and place—whether in Beijing or Bangkok—will climb the ladder of chaos and win the future.

—

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So, you’re on the hunt for that mythical creature, the “unicorn” talent. That 10x Engineer who codes in their sleep and single-handedly turns your ramen-fuelled dream into a market-dominating reality. This article is for you.

But it’s also about something more profound: Ownership, diversity, and the soul of your company – its culture. If you’re a leader with actual skin in the game (and not just a vested interest in the kombucha tap), read on. This is where the real magic happens.

On ownership: The gospel of ‘skin in the game’

Let’s be honest. There are two types of people in the startup world: those who are better at explaining than doing, and those who just get it done. The latter possesses what we might call the “startup spirit”. It’s a scrappy, self-driven, and sometimes undefinable combination of hunger, curiosity, and the ability to bite the bullet for the daily grind. They are the ones who lower entropy, bringing order to the beautiful chaos of creation.

“When I cast actors, I cast eyes.” – Guillermo del Toro

The great filmmaker Guillermo del Toro doesn’t look at CVs; he looks for a certain fire in the eyes of his actors. He’s looking for the soul of the character. We should hire in the same way.

When you have skin in the game, you develop an instinct for this.

You look for that spark of extreme ownership, not just in your leaders, but in every member of the team, including your interim hires. It’s those teams where everyone, from the intern to the CEO, feels that sense of ownership that truly makes your startup become unstoppable.

Diversity, your competitive advantage

As your startup begins to scale, a funny thing happens. You look around one day and realise that everyone looks… remarkably similar. You’ve accidentally created a monoculture. This is not just a social failing; it’s a catastrophic business error. Research shows that on complex, innovative tasks, diverse teams don’t just outperform homogenous ones – they lap circles around them.

Also Read: A founder’s field guide to managing performance and giving feedback that lands

Here are a few unpopular, yet essential, decisions you can make to build a truly diverse team:

• Mandate the 50:50 rule: For every male candidate you meet in the final round, make it a rule to meet with one more female candidate. Yes, it’s more work for your recruitment team. Yes, it might slow you down. But it’s the way to ensure you are truly hiring for merit, not just for pattern recognition.
• Sanitise your job description: By default, job descriptions are riddled with unconscious bias. Words have power, and the ones you choose might be inadvertently turning away entire demographics. I’ve used text analytics tools like Textio to scrub our JDs and create a more gender-neutral tone. We did this for over 100 job descriptions while hiring across Asia for a tech unicorn, and saw a significant shift in our applicant pool.
• Break the monoculture cycle: It’s tempting to hire a bunch of people from that one big tech company down the road. They all have the right skills, right? But before you know it, you’ve created a clique. Factions form, groupthink sets in, and innovation dies. We experienced this personally and had to put a hard stop on hiring from a single company once it reached a certain percentage of our team. It was a tough call, but it saved our culture.

The Glassdoor mirage and the vicious circle

Ah, culture. That nebulous, all-important thing. Does it really matter?

And let’s talk about the elephant in the room: those glowing five-star Glassdoor reviews. We all know it’s shady to ask your most agreeable employees to write them to drown out the one-star rants from disgruntled employees. We also know that almost every startup has done it.

Also Read: The art and science of feedback: A guide for first-time founders and new managers

Here’s the thing: smart candidates see right through it. They read every single review, good and bad, and they can smell a cover-up a mile away. The real question for a founder with skin in the game is not how to game the system, but whether the system is even worth gaming.

Organisational psychologist Adam Grant has a surprising take on this. He found that while founders who are passionate about “culture fit” are more likely to IPO, their companies often grow at a slower rate afterwards. I think this means that an obsessive focus on “fit” can lead to a dangerous level of homogeneity. This brings us to the Polish painter Jacek Malczewski and his haunting masterpiece, Vicious Circle.

In the painting, a whirlwind of figures, some ecstatic, some melancholic, some grotesque, dance in a dizzying circle around a central figure, the artist himself, perched on a ladder; he seems to be both the conductor of this chaotic symphony and a prisoner within it.

The circle is a representation of the creative imagination, a vibrant, powerful force.

But it is also a trap – a self-referential loop that, once entered, is nearly impossible to escape.

This is my analogy for a startup company’s culture. It can look like a cheerful dance of collaboration and innovation. But when it becomes a monoculture, when “culture fit” becomes a euphemism for hiring people who look, think, and act just like you, it becomes a vicious circle. The dance becomes a death spiral of groupthink, stagnation, and, ultimately, irrelevance.

Also Read: Fractional executive hiring: Break the vicious cycle, build the virtuous one

A Founder’s final revelation

At the beginning of the hunt for the 10x talent, you should know that it was never about finding a mythical creature of your dreams and desires; your goal should be about building an ecosystem where such talent can thrive.

This chapter begins with leaders who have real skin in the game, who understand that true ownership is the bedrock of any legendary team.

Then, it is fortified by the kombucha on tap and your singular commitment to diversity (not as a box-ticking exercise but as an imperative determination to fuel innovation and shatter that echo chamber of groupthink).

Then, only when you start to hire, you need to remember two things:

• Find the true 10x-ers who will not only drive performance but also elevate your culture.
• Create an environment that makes them want to stay – An environment that breaks the vicious circle and is a home for true innovation.

The goal is not to find people who ‘fit’ into a pre-existing mould, but to assemble a mosaic of brilliant minds who will challenge, elevate, and redefine what is possible.

This is how you will build a legacy.

—

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I have sat through hundreds of pitch decks. I have seen countless presentations from founders brimming with passion and caffeine. And in almost every single one, there is the inevitable slide labelled TAM (Total Addressable Market).

It is presented as the cornerstone of the investment thesis. Look at this huge number! Look at the billions we could capture! It is meant to inspire confidence, but to a seasoned eye, it often signals one thing: a profound lack of imagination.

Let me be clear: in the current economy, obsessing over a predetermined, static market size is intellectual laziness. It represents a fundamental misunderstanding of how exponential value is actually created. Your market-size slide is useless. It is the metric of the incremental thinker—the person who assumes the world today is the final, finished product.

The tyranny of the existing pie

The typical market analysis starts with an established industry, slices it up into tidy segments, and then claims a tiny percentage of the existing revenue stream. This approach is profoundly limiting. It commits the entrepreneur to a war of attrition where one fights aggressively over the same customers that two dozen well-funded competitors are already fighting for.

This mindset forces you to think vertically: How can I get ten per cent more of the market already defined by my incumbent rival? It anchors your ambition to the current state of affairs, assuming that customer behaviour, technology, and needs will remain exactly as they are right now.

The largest, most enduring companies of the last two decades — the true titans of value creation — did not win by taking a tiny slice of an existing, defined market. They won by performing a strategic judo move: they created entirely new markets that were invisible to the old way of thinking. Before these companies existed, their market size was functionally zero.

Also Read: Gold hits US$4,500 while Bitcoin bleeds: The year-end market disconnect explained

Lateral movement: The key to invisible markets

The strategic move that matters is lateral movement. This is the ability to look at an existing, painful problem and solve it by linking two previously unrelated concepts, thereby defining a whole new category of demand.

Consider the example of the modern smartphone. Its initial market size wasn’t based on the “mobile phone market,” which was finite. It’s true, a massive market size was created by linking three separate, previously unconnected markets: mobile communication, digital photography, and personal computing. The market was created in the overlap, not claimed from the existing carriers.

Lateral thinkers use the existing market size only as a base, a launchpad for understanding the current customer’s frustration. They don’t see the figure as a ceiling; they see it as a springboard. They ask: What is this customer trying to achieve today, and how can I invent a solution that makes their current behaviour obsolete?

From analysis to strategy

This is the main strategy of entrepreneurship: transforming a rigid, defined need into a fluid, limitless opportunity. It requires moving the focus from the external metric (the size of the market) to the internal insight (the depth of the customer pain).

The strategic conversation should not be: Our TAM is US$50 billion. The strategic conversation must be: We are solving a problem that is so severe, so expensive, and so pervasive that it will compel the creation of a new, US$100 billion category of spending.

Also Read: Holiday liquidity warning signs emerge across stocks gold and crypto markets simultaneously

For the founder, this means abandoning the easy comfort of benchmarking against rivals. It means looking for the latent demand, the unvoiced frustration, and the structural inefficiency that no one has dared to tackle because it required combining resources in a way the old industry structure deemed impossible or illogical.

So, the next time you are building a pitch deck, use the existing market size figure for two purposes only: context and contrast. Use it to show the investors what the existing, poor solution looks like, and then immediately pivot to demonstrating how your lateral strategy will invalidate that entire number, compelling customers to flow into the vibrant, wide-open space you have just engineered.

If your sole competitive strategy is to capture five per cent of a market that already exists, aren’t you just admitting you plan to be marginally better, rather than truly indispensable?

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Meta has announced the acquisition of Manus, confirming that the Singapore-based artificial intelligence company is joining the US tech giant to scale its autonomous agent technology to billions of users and businesses worldwide.

In a joint announcement, Meta stated that Manus has built “one of the leading autonomous general-purpose agents,” capable of independently executing complex tasks such as market research, coding, and data analysis.

The Manus service will continue to operate and be sold as a standalone product, while also being integrated into Meta’s consumer and business offerings, including Meta AI.

Meta said Manus is already serving the daily needs of millions of users and businesses globally. Since launching its first General AI Agent earlier this year, Manus has processed over 147 trillion tokens and enabled the creation of more than 80 million virtual computers. Meta added that it plans to scale the service to reach many more businesses across its platforms.

As part of the acquisition of Manus, the Manus team will join Meta to help deliver general-purpose agents across Meta’s products. Meta said the combination of Manus’s tech and talent would help unlock new opportunities for businesses and improve the lives of billions of people who use its services.

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Manus, in a separate statement, described the deal as a significant milestone and a validation of its work on General AI Agents. The company said it has focused on building a general-purpose agent designed to help users tackle research, automation and other complex tasks through continuous product iteration.

The company positioned itself as an “execution layer” for AI, transforming advanced capabilities into scalable and reliable systems that can perform end-to-end work in real-world settings. It reiterated that its agent has already processed more than 147 trillion tokens and powered over 80 million virtual computers in just a few months.

Manus stressed that the acquisition would not disrupt its customers. The company will continue to offer and manage its subscription service through its app and website, and it will maintain its operations in Singapore.

Manus said its solution is already driving value for millions of users worldwide and that, over time, it hopes to expand its subscription offering to millions of businesses and billions of people on Meta’s platforms.

Also Read: Navigating the trust labyrinth: My perspective on ethical AI marketing

“Joining Meta allows us to build on a stronger, more sustainable foundation without changing how Manus works or how decisions are made,” said Xiao Hong, CEO of Manus. “We’re excited about what the future holds with Meta and Manus working together, and we will continue to iterate on the product and serve users who have defined Manus from the beginning.”

Both companies framed the Manus acquisition as a step towards accelerating the adoption of autonomous agents across consumer and enterprise use cases, while maintaining continuity for existing Manus users.

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Image Credit: Manus, Meta

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The playbook is getting clearer every year. Sell into the U.S. and other mature markets, build using Southeast Asia’s talent engine. It’s not just about lowering costs anymore. It’s about creating leverage, speed, and scale by combining global revenue opportunities with regional execution advantages.

As founders, we’re watching the geography of tech shift in real-time. And those who understand how to bridge this gap—between customer and creator, headquarters and build hub, AI strategy and human capital—will win the next decade.

From cost centre to growth engine

For years, Southeast Asia was viewed primarily as a cost-saving destination. Offshoring, outsourcing, and BPOs dominated the narrative. But what’s changed is the quality of talent. Whether it’s engineers in Ho Chi Minh City, product managers in Manila, or designers in Jakarta, the region has grown a mature, hungry, and technically fluent workforce.

What’s more, countries like Singapore have positioned themselves as financial and regulatory gateways, helping global companies establish local HQs while tapping regional labour. Government incentives, English-speaking populations, and increasing venture capital activity have all accelerated the trend.

At NewCampus, we scaled our learning experience and delivery teams in Cebu and Manila to build a high-quality, cost-efficient training engine rooted in local expertise. Our Philippines team adapted content and operations for regional nuance, while our coaches in Vietnam and Indonesia delivered programs in local languages.

By hiring locally and thinking globally, we deepened engagement, boosted learner outcomes, and scaled delivery without sacrificing quality. This approach turned Southeast Asian talent into a competitive edge, enabling us to serve global clients with authenticity, agility, and cultural fluency from the ground up.

What used to be a back office is now a growth office. Product teams. Growth squads. Customer success pods. These aren’t secondary, they’re integral. And increasingly, they’re led from Southeast Asia.

Also Read: From lead generation to pipeline hygiene: What startups often miss

Global ambition, local execution

Take Canva for example. A multi-billion-dollar design platform built with deep Australian roots, but with a heavy operational and engineering footprint in the Philippines. Their support and design operations run lean but powerful, giving them the scale to service a global base while retaining product velocity.

Then there’s Xendit, the Stripe of Southeast Asia. Headquartered in Indonesia, they’ve used their deep regional knowledge and infrastructure to serve both local and international businesses. Their growth is a case study in how local teams, armed with global playbooks, can outcompete bigger, slower players.

Another standout is Deel. While not SEA-born, Deel has leveraged Filipino, Vietnamese, and Malaysian teams across operations, sales, and customer support. It’s a key part of how they scaled to a $12B valuation while offering 24/7 service and onboarding customers globally.

The takeaway here isn’t just that you can build cheaply in Southeast Asia. It’s that you can build well—with speed, quality, and cultural fluency that rivals any major tech hub.

The future is distributed (and competitive)

With AI reshaping how we work, there’s a misconception that geographic labour advantages will disappear. But the reality is more nuanced. AI is great at scaling what you already do well. That includes well-run, geographically diverse teams.

A support agent in Manila using an AI co-pilot will outperform one in San Francisco, still toggling between tools. A product manager in Kuala Lumpur working async with a design team in Bali can ship faster than an under-resourced team co-located in NYC.

Also Read: Startups, is your email strategy driving growth, or just gathering dust?

But only if the systems are in place. Founders need to think deeply about documentation, time zone overlaps, tooling, and most importantly, culture. Distributed teams don’t work by accident. They work because leaders design for clarity, autonomy, and shared rituals.

That means building AI literacy into onboarding. Investing in good managers who can lead without micromanaging. And recognising that time zones don’t kill productivity, unclear priorities do.

Moving forward

The arbitrage between Western revenue and Eastern execution is narrowing, but it’s not gone. In fact, it’s becoming more valuable as companies are forced to become more capital efficient, more globally aware, and more operationally excellent.

If you’re a founder today, you don’t just have an opportunity, you have an edge. The ability to tap top-tier developers in Vietnam, growth hackers in Singapore, or CX leads in the Philippines is no longer reserved for Fortune 500s. It’s accessible at Seed, Series A, and beyond.

And as the next wave of tech companies emerge—those built on crypto, AI, climate, and commerce—the ones who master this balance will win. Build globally. Sell globally. Operate locally. That’s the new startup stack.

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We live in an age defined by paradox.

The world has never been more connected — yet opportunity has never been more unevenly distributed. Technology has lowered the barriers to entry, yet raised the bar for participation. Knowledge flows freely, yet economic mobility feels increasingly restricted.

Economists once used the phrase “islands of modernity in a sea of underdevelopment” to describe colonial economies: pockets of advanced activity built for exports and foreign capital, surrounded by a much larger local population trapped in low-productivity subsistence sectors. Two economies exist side by side, with almost no bridge between them.

Today, that pattern has returned — only now, these islands are digital.

The K-shaped economy: One country, two systems

It’s not just inequality; it’s economic bifurcation.

A modern dual economy, unfolding in real time.

On one side, you have the tech-enabled class: remote workers earning in USD, SMEs using automation to scale, founders leveraging AI, and professionals selling their skills globally rather than locally. They belong to a borderless economy where geography matters less than capability, and where global demand rewards speed, skill, and systems.

On the other side, you have the local economy, where opportunity remains limited by geography, wage ceilings, and the slow pace of traditional industries. Here, jobs are replaced faster than they are created. Retail, F&B, manual labour, and low-skill office roles face both automation and competition. The hardest hit are the young — university graduates entering a job market where entry-level roles are disappearing, replaced by AI or consolidated into senior roles requiring experience they never had the chance to gain.

This divergence forms what economists now call a K-shaped economy — an economy where some groups accelerate upward while others stagnate or decline. The upper arm of the K rises: tech workers, global freelancers, AI-enabled founders, cross-border teams. The lower arm falls: retail, hospitality, local services, admin-heavy roles, SMEs struggling with digital adoption.

These two economies operate in the same country, but rarely interact. They use different tools, speak different economic languages, and respond to different incentives. One ascends; the other treads water.

Also Read: How to thrive in digital entrepreneurship in Asia today

The uncomfortable truth

The uncomfortable truth is this: The digital revolution was supposed to close gaps, but instead, it has deepened them.

Technology increases productivity, but only for those who know how to use it. Remote work increases income, but only for those with global-facing skill sets. AI amplifies talent, but only for those who are trained to leverage it.

Everyone else is left running on a treadmill that only gets faster, as they compete for limited opportunities in slower, smaller, and more fragile markets.

And this is where the danger lies. The gap is not personal — it is structural.

The technological trends of the 2020s have recreated a dual economy, accelerated by digital transformation. The globalised class becomes more mobile, more valuable, more connected. The localised class becomes more fragile, more replaceable, and more exposed to shocks.

What we’re witnessing is not merely different income groups. It is two different economies living in the same country, the same industry, sometimes the same company, but moving in opposite directions.

The digital “islands” have systems, tools, and global connectivity. The “sea” around them has talent, ambition, and potential, but lacks infrastructure to turn it into mobility.

Yet this divide is not inevitable.

Also Read: Asia’s digital gold rush: How to win in the US$600B digital economy

Bridging the digital divide

The gap widens when people and SMEs cannot access the tools that plug them into global markets — when they are trapped behind information barriers, trust barriers, and capability barriers.

The solution isn’t charity: It is access, systems and infrastructure.

It’s giving traditional businesses and workers the means to participate in the modern economy rather than watching it from the sidelines.

This is where market infrastructure matters. Not platforms that merely facilitate transactions, but systems designed to bridge structural economic divides. To give SMEs the same leverage, data, and operational discipline as the global players. To transform local businesses into regional ones. To bring clarity where the market runs on opacity. To give talent, vendors, and entrepreneurs the infrastructure to compete on merit, not connections.

Because if the world is splitting into islands of digital prosperity surrounded by seas of stagnation, then the real work — the necessary work — is to build the bridges.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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