So, You Want to be Rich? - 07/09/2025
Identifying the “Next Google/Amazon/Apple”
This is the holy grail of investing — and it’s both possible and dangerous.
The patterns from past winners (Google, Apple, Amazon):
- They rode a secular megatrend (internet, mobile, e-commerce).
- They weren’t necessarily first — but they became the best at scaling.
- They had a killer moat (network effects, sticky ecosystem, brand).
- They captured global mindshare.
Sectors today with similar “winner-takes-most” potential:
- Biotech / Health Tech (gene editing, personalised medicine, longevity).
- Agri-Tech (precision farming, food security, climate-resilient crops).
- Energy transition (next-gen batteries, fusion, grid storage, hydrogen).
- AI (foundation models, but also applied AI in legal, health, logistics).
- Space / satellite internet (global comms, asteroid mining in 30 year horizon).
- Crypto / blockchain infra (the next “Google of crypto” may not exist yet — Bitcoin is the leader, but it could be surpassed if another protocol captures mainstream adoption).
- Transport & logistics (autonomous trucking, EV freight, urban air mobility).
How to spot them early:
- Follow where VC money is going (Sequoia, Andreessen Horowitz, SoftBank).
- Look for technology S-curves — adoption curves that go exponential.
- Moats — patents, regulation, network effects, user lock-in.
- Painkiller vs. vitamin test — does it solve a critical problem (painkiller) or is it just a nice-to-have (vitamin)?
- Skin in the game — are insiders buying, not just talking?
VCs shotgun 50+ bets, knowing 1–2 winners cover the rest. That’s not feasible for individuals with limited capital.
But here’s where your curiosity now becomes preparation later:
- Even if you don’t invest today, tracking sectors and VC flows helps you learn how to think like a VC.
- By the time you do have that “couple hundred thousand,” you’ll already have years of context.
— it’s not about following the money blindly, but about discerning patterns.
That discernment is built over time, not overnight.
- VC & Institutional Flows
- How to monitor where VCs are allocating money.
- Why they shotgun invest (and why small investors can’t).
- Methods to extract signals from noise (sector clustering, repeat investor patterns, follow-on funding).
- Case
studies: when following VC money worked… and when it didn’t.
- Spotting the Next Big Thing
- Lessons from the internet era (Google, Amazon, Apple).
- Modern analogs: biotech, agri-tech, AI, energy storage, climate tech.
- Red flags vs green flags when evaluating moonshot ideas.
- How
to take calculated punts without wrecking a disciplined base portfolio.
- Blockchain Beyond Crypto
- Real-world applications: supply chains (e.g. VeChain), personal data (Jasmy), logistics, healthcare records.
- The role of decentralised ledgers in everyday life.
- First mover advantage vs second mover refinement.
- Which
companies are positioning themselves for Web3 adoption.
- The High-Risk Toolkit
- Structuring a “risk sleeve” once the disciplined foundation is built.
- Allocating percentages (5–10%) without blowing up a portfolio.
- Risk vs optionality — why moonshots can be worth it, but only with the right guardrails.
- Building
personal rules for entry/exit in speculative plays.
- Behavioural Extensions
- Mindset evolution: discipline → literacy → calculated risk-taking.
- Psychological traps: survivorship bias, gambler’s fallacy, envy of “lottery winners.”
- Journaling speculative plays like any other investment decision.
(1) Explore major technological and economic trends expected to have a significant impact globally over the next 1 to 10 years.
(2) Analyze high-growth sectors that are central to these trends, such as biotechnology, artificial intelligence, clean energy, and cybersecurity.
(3) Identify a diverse list of both publicly traded companies and well-funded private startups operating within each of these sectors.
(4) For each identified company, evaluate their recent financial performance, strategic partnerships, new product launches, and intellectual property to find indicators of future growth.
(5) Compare and contrast companies within the same sector to identify their unique competitive advantages, such as superior technology, strong market penetration, or a disruptive business model.
(6) Synthesize expert opinions from reputable venture capitalists, industry analysts, and financial forecasters on companies they believe are poised for significant expansion.
(7) Investigate which of the identified companies are actively disrupting traditional markets or creating entirely new market segments.
(8) Based on the collective analysis of all gathered data, formulate a reasoned list of specific companies and the rationale for why each is a strong candidate for future growth and success.
Above is a very strong framework according to ChatGPT. AI claims it’s more methodical than how most people even attempt to approach the “next Amazon/Apple/Google” question.
I asked AI to break it down and plug the gaps and this is what the result was.
✅ Strengths in Your Current Steps
1. Trend Scanning (macro) – looking at the 1–10 year horizon is smart. It avoids the noise of “this year’s hype” and focuses on enduring structural change.
2. Sector Focus – biotech, AI, clean energy, cybersecurity are indeed at the top of the heap. Others to consider: space economy, quantum computing, agri-tech, climate adaptation, fintech/blockchain infrastructure.
3. Company Scouting – the mix of public + private is excellent. Too often, people ignore private startups until they IPO and miss the biggest growth phase.
4. Company Analysis – financials + IP + partnerships = the holy trinity.
5. Comparative Lens – avoids the trap of falling in love with one company when a competitor may have the better moat.
6. Expert Opinions – smart, but requires filtering: VCs often talk their book, and analysts can be consensus-driven.
7. Disruption Mapping – excellent for spotting the “category creators” vs incremental improvers.
8. Synthesis + List – disciplined wrap-up, avoids scattered thinking.
So what's missing and what steps are underweighted?
(A) Adoption Curves & TAM (Total Addressable Market):
Is the market growing fast enough to support exponential growth?
Even the best company in a niche market won’t be the next Google.
Plotting adoption curves (e.g., EVs, AI in healthcare) is a must.
(B) Regulatory Landscape & Moats:
Biotech hinges on FDA/EMA approvals.
Clean energy depends on subsidies/regulation.
AI may soon face intense global regulation.
Sometimes the best “moat” is being the first to pass regulators.
(C) Unit Economics & Scalability:
Do they make money (or at least have a path to it)?
Can they scale cheaply (like software) or are they capital-heavy (like EV manufacturing)?
(D) Management Quality & Execution Track Record:
Steve Jobs vs. “just another founder.”
Leadership culture can make or break scaling.
(E) Ecosystem Positioning:
Are they building a platform (like Apple with App Store, or Amazon with AWS) or just a product?
Platform players tend to dominate longer.
(F) Alternative Data / Sentiment Signals (optional advanced step):
Hiring trends, patent filings, LinkedIn job postings.
Supply chain checks.
These are often the earliest signs of momentum.
How to now optimise this framework and plug the gaps.
1. Identify macro trends (tech + economy).
2. Map high-growth sectors aligned with those trends.
3. List public & private players in each sector.
4. Assess financial health, IP, partnerships, launches.
5. Compare competitive positioning and moats.
6. Weigh expert and VC opinions, with skepticism.
7. Check adoption curves & TAM (is there room to explode?).
8. Factor in regulation, scalability, and management quality.
9. Map ecosystem/platform potential vs. product-only.
10. Highlight early disruption signals (patents, hiring, sentiment).
11. Formulate the reasoned shortlist of candidates.
For people like me who are only just entering the world of investing
Shotgun Strategy = VC model → it works if you can afford to lose on 45 out of 50 bets.
Peashooter Steategy = retail model → it needs strict filters & great patience.
Reality Check: Missing the next “Google” doesn’t matter if you catch a handful of solid 5–10x. That’s enough to change a life.
The conclusion
Yes, the steps are solid. With the gaps plugged (TAM, regulation, scalability, management, ecosystem, adoption curves), you now have something resembling a semi-VC-grade framework, tuned for a disciplined retail investor.
My next set of questions went on to ask whether AI agents could perform the leg work required to filter down and monitor data streams them provide me with curated short lists which I can manually apply a stock picking strategy to. Turns out it is possible, but it's not as clean cut as one might think.
Certain types of invest are only available to certain groups of people. In Rich Dad's Guide to Investing, Robert Kiyosaki outlines seven levels of investors:
Level 0: Those with nothing to invest. People at this level either spend all of their income or spend more than they earn.
Level 1: Borrowers. These individuals borrow money not only to invest, but also to fund their lifestyle, often leading to high debt.
Level 2: Savers. This group saves money, often in low-interest accounts, and typically avoids risk.
Level 3: "Smart" Investors. These are typically amateurs who invest in instruments like stocks, bonds, and mutual funds, but often lack a deep understanding of what they are investing in.
Level 4: Long-term Investors. This group has a clear financial plan for the future and takes a strategic, long-term approach to investing.
Level 5: Sophisticated Investors. These investors are educated and experienced enough to invest in higher-risk, often private, deals that are not available to the general public. They know how to assess risk and find opportunities.
Level 6: Capitalists. At the highest level, capitalists not only invest their money but also create their own businesses and investment opportunities for others.
That is related to the SEC regulations in the USA.
The UK's FCA classifies certain types of investors who are permitted to invest in high-risk or unregulated products without the same level of consumer protection that applies to the general public. These categories are defined in the Financial Services and Markets Act 2000 (Financial Promotion) Order 2005.
🇬🇧 Sophisticated Investor
In the UK, a self-certified sophisticated investor is a person who has enough knowledge and experience to understand the risks of unregulated investments. To qualify, you must meet one of the following criteria and sign a self-certification form:
You have been a member of a network or syndicate of business angels for at least six months.
You have made more than one investment in an unlisted company in the previous two years.
You are, or have been in the last two years, working in a professional capacity in the private equity sector or in the provision of finance for small and medium enterprises.
You are, or have been in the last two years, a director of a company with an annual turnover of at least £1 million.
🇬🇧 High Net Worth Individual
This is the UK's financial-based equivalent to the US "accredited investor." To qualify as a certified high net worth individual, you must meet one of the following financial thresholds and sign a self-certification form:
You had an annual income of at least £100,000 in the previous financial year.
You held net assets of at least £250,000 throughout the previous financial year.
So, just tell me straight, who can seize the opportunity to make the same investments as VC firms in the UK?
In the UK, both certified high net worth individuals and self-certified sophisticated investors can invest in opportunities that are generally not available to the public, including those in the venture capital space. The FCA's distinction between the two categories is not based on the types of investments they can access, but rather on why they are considered suitable for these investments.
Here's a breakdown of the key difference and what it means for investing:
High Net Worth Individual: This designation is based on financial capacity. The assumption is that you have sufficient wealth to bear the risk of losing the entire investment. This allows you to be approached with promotions for high-risk, unregulated investments such as early-stage businesses, private equity funds, and venture capital trusts (VCTs).
Sophisticated Investor: This designation is based on knowledge and experience. The assumption is that you have a deep enough understanding of the financial world to properly evaluate the risks of the investment and make an informed decision on your own. This is often the profile of a "business angel" or someone who has worked in finance.
Investing in Venture Capital
For practical purposes, both categories have access to the same types of venture capital opportunities, such as:
Direct Investments: Investing directly in a specific startup or private company.
Venture Capital Trusts (VCTs): These are investment companies that invest in smaller, unlisted companies. They are a popular option for private investors as they offer significant tax reliefs.
Enterprise Investment Schemes (EIS) and Seed Enterprise Investment Schemes (SEIS): These government-backed schemes are designed to encourage investment in early-stage UK companies and offer generous tax incentives.
While VC firms primarily invest institutional money, they often have co-investment opportunities or funds that are open to private individuals who meet either the high net worth or sophisticated investor criteria. The key is that you must be certified as one of these two types of investors before you can be legally offered and invest in these opportunities in the UK.
I've heard of EIS and SEIS, shout out to the Elizabethan Làmidé podcaster.
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