Most founders start the day the same way: clearing emails in the morning, moving through back-to-back meetings by midday, and making dozens of small decisions in between. By the end of the day, the calendar is full and the inbox is quieter and yet, progress feels harder to point to. Time is spent coordinating, catching up, and reprocessing information rather than doing the work that actually moves the business forward.

For solo founders, project managers, marketing teams, and small business owners who spend most of their day inside Google Workspace, this pattern is familiar. The tools are there, but the work often feels heavier than it should.

AI is often positioned as the answer, yet many tools feel disconnected from how work actually happens. They sit outside existing workflows or require teams to adopt new platforms just to get started. What’s missing is context. This is where Gemini takes a different approach, bringing AI directly into the tools teams already rely on.

Google Workspace supports everyone from solo founders to 50-person teams who run their businesses inside Gmail, Docs, Sheets, and Meet every day. This article looks at how those teams are using Gemini within their existing Workspace tools to reduce everyday friction with practical examples that show how work can become clearer, faster, and more focused without changing how teams operate.

Context-based operations support with Gemini

Rather than introducing a new tool to learn, Gemini is built directly into Google Workspace, working inside the same Gmail, Docs, Sheets, Meet (and more) environments teams already use every day. The interface stays familiar, as do file access, permissions, and sharing rules. What changes is how quickly teams can move through information.

Within each Workspace app, Gemini appears in a side panel that provides quick summaries, drafts, and contextual help without pulling users out of their task. It can surface key points from long email threads, suggest first drafts in documents, or help organise information in spreadsheets—all while staying anchored to the work already in progress.

For questions that span multiple tools, the Gemini app adds a broader layer of context. It allows teams to connect information across Drive, Gmail, and Docs—such as locating a specific proposal and summarising related conversations—without manually searching through files or inboxes.

For deeper work, tools like NotebookLM and Google Vids extend this support further. NotebookLM helps teams synthesise research and internal documents into source-backed insights, while Google Vids makes it easier to turn ideas and presentations into simple video content. Together, these tools position Gemini as an integrated layer across Workspace, supporting day-to-day execution as well as moments that require deeper focus.

Also read: AI for SMEs: Indonesia and Google partner on Gemini Academy

Case study #1: Addressing email overwhelm and the endless inbox battle

For most teams, this shift becomes most visible in the place where work begins and ends each day: the inbox. You step out of a meeting to dozens of unread emails—clients waiting on updates, internal threads needing replies. Half an hour goes into catching up, another into drafting responses, and by lunch, little of the work that actually moves the business forward has started. For many founders and small teams, email has become a daily bottleneck.

Gmail with Gemini reduces that friction. Instead of scanning long threads, teams can use smart summaries to surface key decisions, action items, and open questions in seconds. A prompt like “Catch me up on the Project Atlas emails” highlights what matters, with links back to the source for quick verification.

When replies are needed, Gemini supports context-aware drafts that draw from past emails, Drive files, and recent meeting notes. Responses reflect existing communication styles and are grounded in the latest information, saving time without sacrificing clarity or tone. Priority emails are easier to manage as well, with intelligent labeling, reminders, and follow-ups helping important messages rise to the top.

The impact is practical. Customer-facing teams may reduce drafting time while staying responsive. For most teams, it starts small. They begin the day by asking Gemini to summarise emails by project, let it adapt response templates for client replies, and use the Gmail side panel to quickly check context from Drive and earlier conversations. 

Ready to conquer your inbox? Explore what Google Workspace with Gemini can do for you.

Case study # 2: This meeting should have been an email (or document)

However, much of what fills the inbox starts earlier during meetings.

The morning inbox often reflects what happened the day before. Many of the follow-up emails waiting for attention are the result of meetings where decisions weren’t clearly captured. What felt like a productive call at midday shows up the next morning as more work to untangle.

Back-to-back meetings are often the source of a good problem; high productivity means meeting targets in the long run. However, as modern work requires coordination between cross-border teams, there is a need for reduced friction in communicating. Teams need to be more effective in multi tasking notes, tracking action items, and capturing decisions in real time. This reduces the need for follow-ups, and ensures that everyone is on the same page with next steps.

Google Meet with Gemini helps to reduce this friction at the source. With “Take notes for me” enabled, Gemini automatically captures key discussion points as the meeting unfolds, highlights decisions, and identifies action items. Instead of raw transcripts, teams receive structured summaries that reflect what mattered without relying on one person’s notes.

These summaries are saved directly to Drive and easy to share. For remote teams, real-time translated captions, available across more than 60 languages, help ensure everyone has access to the same information, regardless of location or language.

Where Gemini’s value compounds is often seen after the meeting. Summaries can be referenced when drafting follow-up emails in Gmail or pulled into project updates in Docs, reducing repetition and preserving context across tools. The same information no longer needs to be retyped, re-explained, or reinterpreted. 

As a result, teams spend less time documenting and more time listening. Participants stay present in conversations, knowing decisions and next steps are being captured accurately. More importantly, fewer meetings are needed to revisit or clarify decisions.

Make every meeting count. Try Google Workspace with Gemini features today.

Case study # 3: Streamlining expansion without the learning curve

To stay ahead, founders often need to expand their client base to unknown territories. Researching a new market or vendor often turns into a pile of industry reports, docs, and links. It often slows teams down because relevant information is scattered across too many sources.

NotebookLM functions as a personal research workspace built around your own materials. It helps by understanding dense material and synthesising data into actionable insights. Teams can upload PDFs, Google Docs, Slides, and web links—bringing together internal strategy documents, market research, competitor information, and customer feedback in one place. Each source can handle large volumes of text, allowing teams to work with full reports rather than summaries or excerpts.

What sets NotebookLM apart is that it stays grounded in source material. Every response is generated strictly from the documents uploaded and includes citations that link back to the original source. This makes it easier to verify insights, trace decisions to evidence, and avoid “hallucinated” conclusions. 

Multiple sources (with the processing power of up to 500,000 words per source) can be referenced together, allowing teams to synthesize insights across documents without manually cross-checking. When reading isn’t practical, NotebookLM can take its findings and convert it into an audio overview which offers a way to absorb complex material on the move.

In practice, teams use NotebookLM to speed up decision-making. During strategic planning, financial reports and market analyses are distilled into clear summaries backed by data. For vendor evaluations, RFPs, pricing, and compliance documents can be compared side by side. Sales teams turn product documentation and competitor materials into clear positioning points tailored to specific customer segments. 

The shift is subtle but meaningful. Instead of spending days moving between documents, teams move more quickly from research to interpretation. Research moves faster and decisions are made with clearer reference to evidence without adding a new workflow or learning curve.

Also read: Architecting AI Factories to solve the enterprise data paradox

Addressing the invisible tax on modern work with real results

Small implementation efforts can compound into tangible real results down the line. The progress becomes tangible as AI is integrated over time to real workflows. 

This is where Gemini operates quietly within Google Workspace. It supports the repetitive parts of work—summarising threads, drafting first passes, organising notes, and carrying context across email, meetings, and documents—while leaving judgment, creativity, and decision-making firmly with the team. Everything remains reviewable and adjustable, functioning as a faster starting point rather than a final answer.

In practice, this approach has supported organisations operating at very different scales. In the Philippines, Google Workspace helped a regional convenience store chain expand rapidly during the pandemic, enabling remote training for over 1,000 workers, supporting far-flung communities, and improving operational efficiency.

Further, a large logistics and last-mile delivery provider uses Workspace to coordinate a 24/7 network across tens of thousands of employees, maintaining security while improving daily efficiency.

Finally, an agricultural technology and irrigation equipment manufacturer connected teams across rural regions, allowing faster coordination between field staff and leadership and enabling more timely support for farmers.

Across sectors, the pattern is consistent: when work is clearer and better connected, teams move faster with less friction.

Start tomorrow with a small step

Adopting AI does not require a big shift or a new way of working. It can start with something small and immediately useful.

Three Gemini prompts to try today

• In Gmail: “Summarise the emails from [client name] this week and highlight any action items.”
• In Docs: “Write a one-paragraph blog post introduction about the importance of productivity for small teams.”
• In Meet: During a meeting, turn on Take notes for me to automatically capture key points, decisions, and next steps.

Pay attention to what changes when you recover even 30 minutes of your day.

Over time, the teams that benefit most will be the ones that integrate AI thoughtfully, using it to support how they already operate rather than replace it. With Gemini built into Google Workspace, the work remains yours—only with less friction, clearer context, and more time to focus on what matters most.

Ready to supercharge your Workspace? Gemini is available to Google Workspace customers on the Starter, Standard, and Plus plans. For teams looking to experience Gemini fully integrated across Gmail, Docs, Sheets, Meet, Drive, and more, the Standard plan offers the most complete balance of features. Visit their website to upgrade or learn more.

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When Malaysian edutech startup Pandai first launched in 2020, its ambition was modest but clear: help students learn better outside the classroom through personalised digital support aligned with the national curriculum. Five years on, that focus on product depth rather than aggressive marketing has helped Pandai scale to more than one million users — and earn a place in the London School of Economics’ (LSE) prestigious 100x Impact cohort.

Pandai is one of four Southeast Asian ventures selected for the latest 100x Impact programme, an LSE initiative that identifies high-impact organisations with the potential to improve the lives of one billion people. Chosen from more than 800 global applicants, the cohort spans sectors including education, health, and income inequality, and features both for-profit and nonprofit models that are already delivering measurable results at scale.

For Pandai, participation in 100x Impact represents validation of a strategy that has always prioritised educational outcomes alongside sustainable growth. “Since Pandai started, the focus has always been on personalising the offering,” says Khairul Anwar, CEO and co-founder of Pandai, in an interview with e27. “Everything in Pandai — quizzes, tests, flashcards and gamified activities — is tailored to each student’s progress and performance.”

Unlike one-size-fits-all learning platforms, Pandai dynamically adapts its content. Even students from the same class using the app will have different learning journeys, depending on their strengths and weaknesses. The platform covers the full school curriculum for primary and secondary students aged seven to 17, combining curriculum-aligned content, AI, and gamification to drive engagement and retention.

That emphasis on product quality has played a critical role in Pandai’s user acquisition strategy. In its first year, the edutech startup invested nothing in paid marketing, instead relying on organic growth driven by word of mouth and social sharing. Even today, paid advertising plays a minimal role. “Our customer acquisition cost is very, very low,” Khairul says.

Also Read: Why Southeast Asia’s edutech must go beyond chatbots to truly transform learning

Most new users discover Pandai organically through recommendations from friends, social media or search, a key factor behind its strong SEO performance as an edutech startup. Affiliate programmes, where existing students invite peers, and a network of “Pandai consultants”—typically teachers and parents—further support growth. Over the past two years, Pandai has also expanded into B2B partnerships, working with schools, corporates and foundations to subsidise access for underserved communities.

This multi-channel approach has helped Pandai reach scale without compromising its social mission. About 30 per cent of its users come from rural or underprivileged backgrounds, a figure the company is particularly proud of. To support learners with limited connectivity, Pandai has developed an offline mode that allows students to preload content and continue studying even with intermittent or no internet access.

Pandai’s business model reflects this balance between impact and growth. The platform operates on a freemium basis, offering a free version that is available indefinitely. Paid subscriptions unlock features such as deeper performance analytics, interactive content and live classes. “The small portion of students who are paying are essentially subsidising the rest,” Khairul explains. “That’s how we stay true to our mission while remaining sustainable.”

The result is a rare combination in the edutech startup space: rapid scale paired with strong retention. Pandai’s monthly retention rate has improved from 60 per cent in its early days to an average of 94 per cent today, driven by continuous improvements in content, technology and user experience.

Behind the product is a founding team deeply shaped by education. The founders were schoolmates who benefited from scholarships and supportive learning environments, experiences that informed their decision to build an education-focused company. “We saw firsthand how education can transform lives,” Khairul says. “That’s why education felt like our calling.”

Also Read: TikTok and the future of education: How Generation Alpha actually learns

Support from external organisations has also been crucial. Programmes such as LSE’s 100x Impact provide frameworks and mentorship to help Pandai refine its long-term “impact endgame” — how it can scale responsibly while deepening outcomes for learners. For Pandai, being part of the 100x Impact cohort is less about prestige and more about amplification. “We cannot take credit for everything ourselves,” Khairul adds. “A lot of organisations around us have supported us to reach more students.”

As Southeast Asia emerges as a hub for social innovation, Pandai’s journey highlights how an edutech startup can grow by staying anchored to its mission. By focusing on personalised learning, low-cost user acquisition and inclusive access, Pandai is positioning itself not just as a fast-growing platform, but as a scalable solution to education inequality — one student at a time.

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Image Credit: Pandai

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The first wave of freelancing in Asia was about independence — choosing your clients, your hours, and your projects. The second wave, accelerated by the pandemic, brought a surge of creators, solopreneurs, and portfolio careers.

Now, a third wave is coming. And this time, it is shaped by AI.

For creative freelancers, the question is no longer “Will AI take my job?” but “What will my job become?” As someone who has spent over a decade championing the freelance space through CreativesAtWork and now building GenAI production workflows at Dear.AI, we are confident that we are heading towards a future where the definition of freelance work is being rewritten. We are no longer just “gig workers.” We are becoming architects of ideas.

From gig work to intelligent work

Freelancing has always been about independence. Yet, too often, that independence comes at the cost of stability. Freelancers traded security for flexibility, managing fluctuating income, burnout, and a constant chase for the next gig.

AI is changing that equation. It is giving independent professionals especially the creatives, the ability to operate with the efficiency and capability of a small agency — but without the overheads.

Instead of competing on price or speed, freelancers can now truly compete on value — by combining human insight with AI-driven execution. We are seeing the rise of “intelligent freelancers” (ie. professionals who use AI not just to do more, but to think differently).

Freelancers must rethink revenue models

AI compresses production time dramatically. If you are still billing by the hour, it will be a bad news! Your income will shrink as projects become faster to produce. New revenue models are not optional — they are essential. The new revenue models could be a combination of the following:

• Value-based pricing: Charging for business outcomes rather than hours.
• Licensing instead of one-offs: Designers, videographers, and writers across Asia are experimenting with licensing templates, story frameworks, and reusable assets.
• Monthly creative subscriptions: Clients access a creator’s brain and capabilities, not individual tasks.
• Revenue-share partnerships: More creators are co-developing campaigns, original IP, or brand content with profit-sharing models — especially in the creator and media economy.

Insight, originality, and taste will remain premium. Freelancers need to rethink their revenue models.

Also Read: Singapore’s workforce is facing its biggest reset yet and AI is forcing the shift

The new skillsets for freelancers

Technical literacy is now the baseline. To thrive in the new freelance economy, you need to level up in areas AI cannot touch:

• Creative direction: AI generates a thousand options; you are the one who decides what has meaning.
• Cultural curation: Asia is a mosaic of nuance. AI can remix culture, but it cannot originate the “soul” of a local story. Your cultural intuition is your greatest asset.
• Workflow orchestration: Knowing which AI tools to chain together is the new “mastery of the craft.”

The human advantage in an automated Asia

Asia’s freelance economy will not be shaped by AI tools alone. It will be shaped by:

• Cultural intuition
• Lived experiences
• Empathy
• Community roots
• Multilingual storytelling
• Emotional intelligence
  

AI can replicate style, but not soul. It can remix culture, but not originate it. As AI reduces the burden of technical labour, the value of human perspective increases — especially in a region as culturally rich and diverse as Asia.

A future where freelancers lead, not follow

Asia is uniquely positioned to lead this 2.0 freelance economy. We have a young, digitally native population and a booming creator economy hungry for storytelling. But remember: AI can replicate style, but it cannot replicate soul. It lacks lived experience, empathy, and community roots. As the burden of “technical labour” decreases, the value of our unique human perspective increases.

Conclusion

The freelancers who thrive, in the future, will be those who embrace hybrid identities — blending creativity, strategy, technology, and empathy. The future does not belong to the fastest adapter of tools. It will belong to the one who uses AI to become more creative, more human, and more original. Because in the age of AI, the most powerful work does not come from automation. It comes from amplified imagination.

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When I run workshops for older adults, I see the same moment every time. A trembling hand hovers over the keyboard. Someone looks up and whispers, “Teacher, if I press this key, will it spoil the computer?”

They do not dare to touch the screen. They worry that one wrong click will destroy everything. And when I tell them gently, “You can just delete it,” they still hesitate.

It is not the machine they fear. It is embarrassment.

Many midlife and senior learners are not afraid of technology itself. They are afraid of looking foolish, of doing it wrong, of being judged by others who “know better.” They do not want to risk fun for judgment. Or as one of my learners said with a laugh, “Jude who? Why risk fun for judgment?”

That small sentence says everything. Underneath every hesitation lies the fear of being laughed at instead of supported.

Where the fear begins

For those of us who grew up in a world of pens and paper, technology feels like a foreign language. Every update changes the grammar. Every new app comes with a new accent.

When you are not fluent in that language, silence feels safer than speaking. That is why many older adults say, “I cannot learn.” They simply do not want to feel small again.

The problem is not ability. It is confidence.

Learning needs safety, not speed

When seniors enter an AI class, what they need most is not information. They need a space where it is safe to try, fail and laugh.

One of my students once said, “I did not know I was allowed to make mistakes here.” After that, she started experimenting with voice-to-text, image generation and storytelling. Her progress was not because of the tool but because of the environment.

When we remove judgment, curiosity returns. And when curiosity returns, learning becomes natural.

Also Read: The second act: How midlifers are reinventing themselves with AI

Reframing what learning means

In school, mistakes are punished. But in creativity, mistakes are how discovery begins.

Adults need to unlearn the belief that knowledge only comes from perfection. AI actually rewards trial and error. It invites us to ask, test and adjust.

You cannot break AI by asking questions. But you can break your own confidence by not trying at all.

Building bridges between generations

Younger people often forget that older learners want to participate. They just need someone patient enough to walk with them.

When a teenager teaches a parent how to use AI, both grow. The younger learns empathy and patience. The older learns courage and self-trust.

It is not about who knows more. It is about discovering together.

Creating confidence through small wins

Confidence is built through small successes. Each time an older learner writes a story, generates a picture or records their voice, they prove they can still learn.

The key is to start small. Ask one question. Try one feature. Share one post. Every attempt removes fear and builds trust, not only in AI but in their own ability to grow again.

The gentle reminder

Technology will always evolve, but our curiosity can evolve with it. If we treat AI as a bridge rather than a barrier, it can reconnect generations and rebuild confidence.

The fear of breaking something is real, but the greater loss is never pressing the button at all. It is not about perfection. It is about participation.

So go ahead. Press the key. Delete. Retry. Post. Because courage begins with a single click.

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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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The once distinct lines between creator, player, and entrepreneur are dissolving into something new that fundamentally restructures how value is created and captured in the gaming ecosystem.

Gaming began as a subversive tool for consumption where value flowed one way from player to publisher, enabling publishers to build massive empires.

Esports was the first revolution that shook up this structure and allowed a microscopic segment of players to monetise their skills. However, of the over three billion global gamers in the ecosystem, only 15,000 can earn a sustainable living through competitive play, and even fewer earn the equivalent of a “professional athlete‘s” salary. 

Streaming was the second uprising that allowed over 9.2 million active streamers and gamers to find a path to monetisation. Yet the economics remain brutal, with only the top 10 per cent able to earn well. The platform-dependent revenue model, reliant on subscriptions, tips, and ads, means most operate on economic margins thinner than graphene.

We now stand at a more significant threshold with AI that doesn’t just add another revenue stream to the existing ecosystem—it rewrites the fundamental relationship between creation, distribution, and monetisation in gaming. These are encapsulated in the three phases of AI-powered gaming entrepreneurs.

Phase 1: Asset creation and community building

For the 95 per cent of streamers who struggle with differentiation and asset creation, AI offers immediate relief. The data is clear, 82 per cent of streamers report difficulties in creating unique visual assets for their brand and content, while 74 per cent struggle to maintain consistent creative output alongside their streaming schedules.

AI asset generation solves both a production and economic problem. Streamers who incorporate real-time audience participation through interactive content show 68 per cent higher viewer retention. When AI enables streamers to generate assets based on viewer input in real-time, the para-social becomes genuinely collaborative.

This shift has already begun. The most successful creators aren’t just playing games—they’re creating within them, building distinctive visual identities and interactive experiences that transform passive viewers into active participants.

Also Read: How sailing as a teenager prepared me for a career in tech and gaming

Phase 2: Monetisation through platform ecosystems

As streamers build communities around their AI-enhanced content, the next logical step is direct monetisation of their creations within existing game ecosystems.

The platforms are already massive, with Roblox has reaching 82.9 million daily active users and creator payouts hitting US$923 million in 2024 alone.  What’s more telling is the distribution, 20,000 qualifying Roblox creators earned an average of US$46,150 each.

Compare this to streaming, where only 23 per cent of streamers use sponsorships, and just 18 per cent sell merchandise. The User Generated Content (UGC) economy represents a significant expansion of monetisation potential, yet only four per cent of streamers currently tap into digital asset sales. This gap between current utilisation and market potential won’t last.

The successful transition from streamer to platform creator doesn’t mean abandoning streaming, it’s the opposite. Streamers who involve their communities in content creation see over three times the engagement and create a virtuous cycle where streaming builds audience, audience provides feedback on creations, creations generate revenue, and revenue enables more streaming.

Phase 3: Independent development and gaming entrepreneurship

The final phase, with the most transformative potential, is independent game development enabled by AI.

The economics of traditional game development have become increasingly punitive and unsustainable. Development costs for major titles doubled to US$200 million between console generations. Marketing costs frequently exceed development budgets. The barrier to entry isn’t just high—it’s stratospheric.

AI tools fundamentally changes this equation by reducing art production costs by more than half, automatically optimising code, and generating vast game worlds through procedural systems. The capital requirements for game development has decreased by orders of magnitude.

This democratisation creates an unprecedented advantage for creators who’ve cultivated loyal communities. Those who build dedicated followings through streaming and UGC gain the ability to sell complete games directly to an established audience. The model mirrors independent music artists who spend years building fan bases before selling out concerts and releasing albums that they own the rights to—keeping the vast majority of revenue instead of settling for industry-standard royalties. When a streamer with 100,000 followers releases their own game, they’re not starting from zero—they’re launching with a pre-built audience, distribution channel, and feedback mechanism already in place.

Also Read: Blockchain gaming trends in Asia: here’s what you need to know

For entrepreneurs building at this intersection of AI, UGC, and streaming, the potential extends beyond just making games. They’re building economic systems—places where value is created, exchanged, and captured continuously rather than in single transactions.

Why this time is different

We have seen democratisation promises before, game engines became more accessible and distribution platforms open up. Yet the gap between amateurs and professionals remain vast.

The AI difference does not just lower barriers, it actively allows collaborations. It does not just make tools more accessible, it augments human creativity in ways that fundamentally change what is possible for a small team or even an individual.

The integration of AI creation tools is rapidly erasing the distinction between professional and amateur content. The successful gaming entrepreneurs of tomorrow will not be those with the largest teams or development budgets, they will be those who best leverage AI to amplify their creative vision and community engagement.

For several years, the gaming industry has undergone a quiet restructuring. The development costs for AAA titles have become unsustainable, while user acquisition costs have risen 45 per cent year-on-year in mature markets, and the return on ad spend have declined by 30 per cent since 2021.     

These economic pressures create the perfect conditions for AI-powered disruption, and the platforms sensing this shift are already making their moves. Roblox nearly tripled creator payouts since 2022, Epic has been refining engagement-based payouts in Fortnite Creative, and major modding platforms have experienced download growth of over 40 per cent. 

The gaming entrepreneurs who will dominate the next decade are already building their communities. These are the streamers with 100 to 1,000 concurrent viewers who recognise that engagement is more valuable than pure reach, and these are the rising creators who see AI not as a replacement for human creativity, but as a force multiplier for it.

The path from player to professional and to entrepreneur is not just possible, but inevitable for those who recognise what’s happening. The game has changed. The only question is who will play it best.

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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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At the end of 2025, I took on a new project: joining a startup team to launch a cruise ship.

On paper, it sounded exciting. In reality, it was one of the most uncomfortable, demanding, and emotionally intense experiences I’ve had in my career. And one that reshaped how I think about work, people, and building from the ground up, pushing me far beyond my comfort zone.

For the first time, I found myself working closely with people from vastly different backgrounds — marine engineers, F&B operators, IT teams, sales and commercial leads, gaming specialists, terminal officials, ferry operators, distributors, marketing teams, crew members, and front-of-house staff. Everyone spoke a different “language,” came with different priorities, and operated under very different constraints.

If my earlier roles helped me enter the startup world, this project dropped me straight into the deep ocean. No floaties. No shallow end.

There were days when frustration turned into tears. There were moments when exhaustion blurred judgment. But there were also moments of clarity — when you see real impact happening in real time, and you realise you’re building something that didn’t exist before.

This is the side of startups we don’t romanticise enough.

When things break, results matter more than procedures

In theory, startups talk about processes, workflows, and frameworks. In reality, when things go wrong — and they often do —  no one asks for the SOP first.

They ask: Can we fix this? And how fast?

This project gave me a full taste of what “results-oriented” really means. When a problem escalates, the priority isn’t whether the issue fits neatly into a process. It’s about ownership, speed, and outcomes. You do what needs to be done, figure out the documentation later, and move forward.

That doesn’t mean procedures are unimportant but in the heat of execution, adaptability beats perfection every time.

Also Read: Why AI startups across Southeast Asia are shipping themselves into churn

SOPs matter, but everything changes in a heartbeat

Yes, startups need SOPs. Especially when safety, compliance, and customer experience are involved.

But startups are also living systems. Things shift constantly — partners change requirements, customers behave unexpectedly, resources tighten, and timelines move overnight. What made sense in the morning may be outdated by the afternoon.

What really matters is how you keep the team moving forward with the right spirit, while juggling customer complaints, management scrutiny, partner constraints, and limited resources — all at once.

One lesson that stuck with me: don’t use an AM mindset to judge a PM situation. Context changes. Decisions need to adapt to it.

There is hierarchy, but courtesy matters more

When things move fast, it’s easy to become laser-focused on execution and forget that every person involved has their own role, responsibility, and pressure.

In startups, you often ask for help that sits right at the edge of someone else’s scope. Sometimes beyond it. That’s when gratitude matters most.

Never take support for granted — whether it comes from a junior crew member or a senior leader, a partner team or a “sister” department. A simple “please” or “thank you” goes further than most people realise, especially under pressure.

Speed does not excuse a lack of respect.

Your job title should never limit your contribution

In a real startup, job titles are guidelines at best.

On this project, everyone did a bit of everything. That doesn’t mean you personally execute every task with your own hands, but it does mean you own the problem until the loop is properly closed.

Sometimes that means finding the right person. Sometimes it means unblocking someone else. Sometimes it means stepping in temporarily, even if it’s not “your job.”

Startups reward people who go beyond defined lanes — not because they are overworked, but because they care about outcomes.

Also Read: How startups and VCs can propel Indonesia’s energy transition

Corporate vs startup: know what you’re signing up for

This journey is very different from the corporate world. Neither is better, but they are not the same.

If you’re considering joining a startup, here are a few signs to check within yourself first:

• Be ready for work that was never mentioned in your job description and often has nothing to do with your title.
  
• Learn to be a problem solver, not someone who hides behind procedures or waits for perfect clarity.
  
• Build resilience. Frustration, criticism, repetition, and emotional swings are part of the package. You fall, you stand up, and you keep going because you know you’re building something bigger with people from all walks of life.

Startups are not glamorous most of the time. They are messy, demanding, and deeply human.

But if you stay long enough, they shape you in ways no classroom or corporate training ever could.

Enjoy building — and get stronger while crushing problems along the way.

In the end, cruising the startup ocean is about learning to build without a playbook and becoming more adaptable with every wave you face.

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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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In a historic shift for Southeast Asia’s tech sector, the crown for the most funded industry has changed hands.

Enterprise infrastructure has emerged as the top-performing sector, raising a total of US$2.3 billion in 2025. According to the “SEA Tech Annual Funding Report 2025” by Tracxn, this represents a robust 70 per cent increase over the US$1.3 billion raised in 2024 and an incredible 12x increase from the US$182 million raised in 2023.

Also Read: Southeast Asia’s startup boom is becoming a closed club

The driving force behind this infrastructure boom is the region’s hunger for digital storage and processing power. Data centre providers alone accounted for US$1.9 billion of the sector’s total, led by massive rounds for Princeton Digital Group and Digital Edge. Investors are pivoting away from application-layer software and toward the physical and cloud-based foundations that allow the broader digital economy to function.

While infrastructure soared, the region’s traditional darling, fintech, faced significant headwinds. The sector saw total funding drop to US$1.5 billion, a 21 per cent decrease from 2024 and a 42 per cent collapse from the US$2.6 billion raised in 2023. Despite this decline, the vertical remains a core pillar of the ecosystem, with internet-first business payments and internet-first remittance platforms like Airwallex and Thunes still managing to attract significant late-stage capital.

The enterprise applications sector also struggled to maintain momentum, raising US$1.42 billion in 2025. This reflects a 38 per cent decline compared to the US$2.3 billion raised the previous year. It appears that the era of speculative investment in “software-as-a-service” (SaaS) platforms is being replaced by a more pragmatic focus on “hard” tech and the AI-ready infrastructure required for the next decade of growth.

Also Read: Jakarta trails as Singapore tightens its grip on tech capital

Investors are essentially moving from building the fancy rooms of the digital house to investing in the steel and concrete of the foundation itself

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Anthropic, the fast-rising artificial intelligence (AI) startup behind the Claude chatbot, is in talks to raise up to US$10 billion in fresh funding at a valuation of around US$350 billion, says a Wall Street Journal report, citing sources.

The proposed financing round is expected to be led by Coatue Management alongside GIC, Singapore’s sovereign wealth fund, with participation from existing shareholders. The discussions come amid growing speculation that Anthropic could pursue an initial public offering within the next 12 to 18 months, as leading AI players race to secure ever-larger capital war chests.

AI investment boom intensifies

The potential deal underscores the relentless investment momentum surrounding generative AI, even as concerns mount over frothy valuations and the long-term economics of AI businesses. Developing large-scale AI models is notoriously expensive, requiring massive investments in computing power, energy, and specialised data centre infrastructure.

Also Read: OpenAI announces Singapore expansion amid doubling of ChatGPT users

Anthropic’s prospective valuation would place it among the world’s most valuable private companies, trailing only a handful of AI rivals. In December, OpenAI announced a US$41 billion investment from Softbank and is currently valued at US$500 billion, while Elon Musk’s xAI announced on January 6 that it had raised US$20 billion, reportedly valuing the company at over US$230 billion.

A safety-first AI challenger

Anthropic was established with a strong emphasis on AI safety and alignment, and is structured as a public benefit corporation, committing it to public and social good alongside commercial returns. That positioning has resonated with deep-pocketed investors. In 2024, Anthropic raised US$8 billion from Amazon, its largest investor to date. Google has invested approximately US$3 billion and controls around 14 per cent of the company, according to court documents cited by The New York Times.

In total, Anthropic has raised at least US$40 billion in funding, according to PitchBook data. The company’s previous funding round closed in September at a valuation of US$183 billion, while Microsoft and Nvidia later announced plans to collectively invest around US$15 billion.

GIC’s strategic bet on responsible AI

GIC’s involvement reflects its growing conviction that AI represents a foundational economic transformation, rather than a short-term technology cycle. Sources familiar with its thinking say the sovereign fund is particularly drawn to Anthropic’s focus on reliable, interpretable, and steerable AI systems, which it views as essential for long-term enterprise adoption.

Rather than chasing hype-driven valuations, GIC is said to be taking a valuation-sensitive approach across the AI value chain, targeting enablers, monetisers, and adopters that can deliver sustainable economic impact. Its backing of Anthropic builds on earlier investments, including participation in the startup’s US$13 billion Series F round.

Also Read: Anthropic index shows AI boom risks widening global inequality

Notably, GIC has no public equity investments in OpenAI, despite the latter establishing Singapore as its Asia-Pacific headquarters. While OpenAI counts Microsoft, Nvidia, and other global players among its backers, GIC’s stake in Anthropic gives Singapore direct exposure to a safety-focused AI leader, rather than just an operational presence.

Massive infrastructure ambitions

As Anthropic pushes to commercialise its AI models for enterprises and consumers, its capital needs are ballooning. The company is spending tens of billions of dollars on the data centre infrastructure required to train and run advanced AI systems.

Late last year, Anthropic announced plans to invest US$50 billion in data centres across Texas and New York in partnership with cloud provider Fluidstack, though it has not detailed how the project will be financed. The startup is also purchasing vast amounts of computing power from Amazon and Google.

One of its most ambitious projects is a massive Amazon data centre in New Carlisle, Indiana, where Anthropic will be the primary customer. Once fully operational, the facility is expected to consume 2.2 gigawatts of electricity, enough to power around one million homes.

Implications for Southeast Asia

GIC’s potential investment could have meaningful spillover effects for Singapore and Southeast Asia’s AI ecosystem. Market observers say it may accelerate Anthropic’s expansion in the Asia-Pacific region, boost local hiring, and deepen partnerships with regional enterprises.

The move also reinforces Singapore’s position as a leading AI hub. The city-state is home to 80 of the world’s top 100 technology firms, has attracted US$1.6 billion in AI funding, and continues to promote responsible AI through initiatives such as AI Singapore. The country’s AI market is projected to grow 28 per cent to reach US$4.64 billion by 2030, underpinned by strong governance frameworks and public-private collaboration.

Also Read: Anthropic data shows businesses use AI to automate, not collaborate

For Southeast Asia’s broader startup ecosystem, GIC’s backing of Anthropic sends a clear signal: capital is increasingly flowing toward foundational, safety-conscious AI infrastructure, marking a shift from speculative software bets to the core systems powering the next decade of digital growth.

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Anthropic’s latest funding talks mark more than just another eye-popping valuation in the global AI race — they signal a deeper shift in how capital is being deployed into the sector, and why Singapore increasingly matters in that equation.

With GIC emerging as a key backer at a reported US$350B valuation, the deal underscores a growing preference for foundational, safety-first AI infrastructure over speculative application-layer bets. At a time when generative AI enthusiasm risks outrunning economic reality, Anthropic’s positioning as a public benefit corporation focused on alignment and enterprise reliability offers investors a narrative anchored in durability rather than hype.

For Singapore, GIC’s involvement delivers strategic relevance beyond headlines. Unlike OpenAI’s regional footprint in the city-state, this move provides direct equity exposure to a frontier AI company shaping global standards around safety, governance, and large-scale deployment. It strengthens Singapore’s role not merely as an operational hub, but as a capital allocator influencing how AI evolves.

The scale of Anthropic’s ambitions — from multibillion-dollar data centre investments to energy-intensive compute partnerships — also highlights a broader truth: AI leadership will be determined as much by infrastructure discipline as by model breakthroughs.

As global investors pivot from “fancy rooms” to the steel and concrete of AI’s foundations, Southeast Asia, backed by long-term capital and regulatory clarity, is positioning itself firmly in the next chapter of the AI economy.

REGIONAL

Why GIC is backing Anthropic over OpenAI: Rather than chasing hype-driven valuations, GIC is said to be taking a valuation-sensitive approach across the AI value chain, targeting enablers, monetisers, and adopters that can deliver sustainable economic impact.

X faces possible sanctions as Indonesia tightens AI rules: An investigation has been launched into the alleged misuse of Grok AI over concerns that it is being used to generate and distribute immoral content, including manipulated personal photos created without consent.

Southeast Asia’s startup boom is becoming a closed club: The number of companies receiving their first round of capital fell 62%, from 283 in 2024 to just 107 in 2025. Investors are clearly operating with a “flight to quality” mindset, favouring companies with clear paths to profitability and established market presence.

Indonesia’s crypto trading hits US$28.6B in 2025: The country’s Financial Services Authority said the number of registered cryptocurrency consumers rose to 19.6M in November 2025, up 2.5% from October. Cryptocurrency transaction value in December 2025 fell 12.2% to US$2B, compared to November.

Jakarta trails as Singapore tightens its grip on tech capital: Singapore’s US$4.7B haul dwarfed Jakarta and regional peers as late stage mega rounds reshaped funding flows. Jakarta, traditionally the second powerhouse of the region, trailed far behind with just US$212M, representing a mere 4% of the total funding pool.

8×8 acquires Maven Lab, signals shift beyond SMS in Southeast Asia: Maven Lab is best known for its solution-based messaging platforms, including Moobidesk, which enable enterprises to deploy high-volume communications quickly and efficiently across regulated markets.

FEATURES & INTERVIEWS

Infrastructure takes the throne in SEA tech: Enterprise infrastructure has emerged as the top-performing sector, raising a total of US$2.3B in 2025. As per a Tracxn report, this represents a robust 70% increase over the US$1.3B raised in 2024 and a 12x increase from the US$182M raised in 2023.

Pandai’s low-cost growth playbook puts the edutech startup on LSE’s 100x Impact radar: Pandai is selected for 100x Impact, an initiative that identifies high-impact organisations with the potential to improve the lives of one billion.

Wallets, not smart contracts, were crypto’s biggest risk in 2025:  The dominance of the Bybit breach highlights how failures in custody infrastructure can lead to substantial losses, even as decentralised protocols adopt more robust security frameworks.

INTERNATIONAL

Musk’s xAI reports US$1.5B net loss in Q3: The company’s revenue nearly doubled quarter-over-quarter to US$107M for the three months ended September 30, 2025, but sales still trail its annual target of US$500M. xAI spent US$7.8B in cash in the first nine months of 2025, mainly on data centres, talent, and software development.

Global enterprises shift AI strategies from cost savings to growth, study finds: Optimism is strongest in India and Brazil, where almost half of leaders expect more than 15% growth within five years. Germany and Australia remain more cautious, reflecting uneven maturity in AI strategies across regions.

Razorpay reportedly plans US$500M IPO: The Indian digital payments firm was last valued at US$7.5B after raising US$375M in 2021 and counts GIC, Peak XV Partners, Z47, and Tiger Global as investors. The public issue may launch by year-end, but the timing and final amount could change.

UK watchdog says Grok allegedly made illegal images: The watchdog IWF said the images meet the threshold for criminal action under UK law. These images, allegedly produced using the Grok Imagine tool, were later processed using another AI tool to create more extreme content, including graphic video.

SEMICONDUCTOR

Thailand enters the chip race, without challenging Singapore head-on: At its core is an ambition to reposition the country as a critical node in the regional and global chip supply chain, moving decisively beyond basic assembly into design-led and upstream manufacturing.

China memory chip prices surge on global supply crunch: Merchants at Huaqiangbei, a major electronics market in Shenzhen, said memory chip prices have sharply increased since late 2025, with DDR5 server memory sticks from Samsung and SK Hynix reaching over US$5,700 each.

India, Nvidia in talks on sovereign GPU development: The discussions also included edge computing systems such as Nvidia’s DGX Spark, which is designed for AI apps and can operate without internet connectivity. The talks focused on supporting secure AI model inferencing for use in sectors like railways, healthcare, and education.

Qualcomm in talks with Samsung over 2-nm chip production: The US chipmaker’s CEO Cristiano Amon reportedly said discussions are ongoing with Samsung, among other foundry firms, for contract manufacturing, with design work reportedly completed for upcoming commercialisation.

Naver builds AI computing cluster using 4,000 Nvidia GPUs: The company said the new “B200 4K cluster” will support the development of its proprietary foundation models and the broader application of AI technologies. Naver said the cluster offers computing performance comparable to the world’s top 500 supercomputers.

AI

SEA consumers demand AI that connects, not just computes: Southeast Asia’s AI adoption is accelerating, but consumers demand human-led experiences, pushing businesses to blend automation with empathy, speed, and personalisation to stay competitive.

AI human hybrid support: Why customers still prefer real conversations: Hybrid customer support blends AI efficiency with human empathy, cutting costs while preserving trust, loyalty, and satisfaction by ensuring speed for routine issues and people for complex, emotional interactions worldwide.

Why many seniors hold back from AI and how we can help them begin: Older adults fear embarrassment, not technology. Learning AI requires psychological safety, patience, and small wins that rebuild confidence, curiosity, and intergenerational connection through participation, not perfection.

THOUGHT LEADERSHIP

Singapore’s next digital leap: From connected infrastructure to intelligent ecosystems: Singapore’s digital infrastructure is evolving from connectivity backbone to intelligent ecosystem driving resilience, innovation, and business transformation.

Cruising the startup ocean: Building without a playbook: Joining a startup to launch a cruise ship revealed the unromantic reality of startups: intense pressure, blurred roles, constant adaptation, and human resilience shaping leaders far beyond comfort zones daily.

Altcoin season 2.0: Smaller rallies, bigger fundamentals, better returns: Altcoin markets are maturing as institutional capital, narrative-driven cycles, and real utility replace indiscriminate speculation, rewarding selective projects with strong fundamentals, scalable infrastructure, regulatory awareness, and measurable adoption.

The freelance economy 2.0: In the age of AI: Asia’s freelance economy is entering a third, AI-driven wave where creatives evolve into idea architects, adopting new skills and revenue models, blending insight with AI to compete on value globally.

Creativity at the heart of business growth: As consumer behaviour shifts toward emotion-led purchasing, brands must embrace creative, content-driven commerce, blending entertainment, authenticity, and technology to build trust, drive engagement, and unlock growth opportunities.

How to navigate through the vast opportunities in the finance industry: Singapore’s finance industry has transformed through digitalisation, shifting investor demographics and fintech innovation, forcing institutions to blend high-tech platforms with human trust, continuous learning and client-centric services to remain competitive.

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