November 2022 Was Another October 1492: Learn How to Live, Learn, Work, and Invest in an AI-Driven World

Creatix / September 26, 2025

November 2022 was the October 1492 of our times.

October 1492 and November 2022 each mark inflection points where a new “world” opened—one geographic, the other cognitive. Columbus’s landfall connected previously isolated continents, catalyzing centuries of exchange, empire, science, and capitalism, alongside devastating conquest, disease, dispossession, and the transAtlantic slave trade. November 2022, when conversational AI went mainstream, similarly linked previously separate domains of knowledge and labor: language became a universal computer interface, work began to speed up, and new industries began to form, while fresh risks (bias, surveillance, disinformation, and economic displacement) came into view. 1492 redrew maps and supply chains; 2022 began to redraw workflows and information flows. Both moments rewarded navigators and changed the human world forever. If 1492 launched the Age of Colonization with human conquistadors, 2022 launched the Age of Collaboration with machines. In both cases, how we govern the new frontier will define the legacy. Regardless, the human world will never be the same.

November 2022 wasn’t just an IT product launch; it was a revolutionary cognitive reframe just like Europe’s discovery of a route to a vast New World in what would become the Americas. After October 1492, the immediate winners were the Iberian crowns (Spain and Portugal) and, soon after, the Dutch, English, and French, plus the merchant-financiers and port cities of Seville, Lisbon, Antwerp, Amsterdam, and London; navigators, cartographers, shipbuilders, and the plantation/commodity houses tied to silver, sugar, and tobacco. These gains were built at catastrophic cost to Indigenous peoples and enslaved Africans. After November 2022, the early winners are the compute and cloud suppliers (GPU designers, chip foundries, and hyperscalers), foundation-model platforms and the app layer building on them, data-rich incumbents that can redeploy AI across workflows, and individuals/teams who master prompting, agent orchestration, and verification. It is yet to be seen who will bear the cost of this new AI revolution. We can begin with a few displacements here and there. Eventually, we can all be the new natives and enslaved originals.

When conversational AI left the lab and entered everyday life, the center of gravity moved from searching for answers to co-creating them. The winners in this new era won’t simply “use AI”; they’ll think with it, delegate to it, and design around it so here’s a draft playbook for adjusting your mindset, plus concrete habits to build skill in prompting, agent management, and day-to-day decision-making in the new age of generative AI.

Five Core Mindset Shifts

From tools to teammates
Stop treating AI like a fancy calculator. Treat it like a junior colleague: brief it, give examples, set constraints, review output, and iterate. You are the editor-in-chief.
From knowing answers to asking better questions
In an age of on-demand synthesis, the scarce asset is question quality. Think in hypotheses, trade-offs, and counterfactuals; ask for comparisons, failure modes, and “argue against yourself.”
From tasks to systems (agents)
Don’t just prompt; orchestrate. Chain steps, set checkpoints, and let agents run subroutines with guardrails. You become an AI product manager: define goals, success metrics, permissions, and budgets.
From certainty to probabilistic reasoning
Outputs are distributions, not decrees. Default to “trust, but verify”—triangulate sources, stress-test claims, and keep a standing habit of sampling counter-evidence.
From ownership to stewardship of data
Your competitive edge is the quality and governance of your data: notes, templates, SOPs, and examples. Curate a private knowledge base; know what you will and won’t share.

Prompting as a Modern Literacy

Use this six-lever “GIC-ECO” prompt skeleton:

Goal: the specific outcome you want.
Inputs: paste or point to the raw materials (docs, data).
Constraints: word count, tone, audience, style, compliance.
Examples: one or two gold-standard snippets to imitate.
Checks: ask for citations, edge cases, and self-critique.
Output format: table, bullets, JSON, outline, slide notes, etc.

Example mini-prompt:
“Goal: 300-word executive brief on Project Falcon. Inputs: meeting notes below. Constraints: neutral tone, Flesch grade ≈ 9, include 3 risks + mitigations. Checks: highlight unknowns; propose next 2 decisions. Output: 5 bullets + 1 paragraph.”

Habits that compound:

Maintain a living prompt library with named patterns (brief, critique, compare, simulate, translate, storyboard).
Keep few-shot exemplars—your best past outputs—so models learn your style.
Add a verification clause: “List sources and where they may be weak; offer one counter-argument.”

Managing AI Agents (Your “AI Ops”)

Think of agent work like running a small operations team.

Design loop: GEAR

Goal: outcome KPI (“book 6 qualified demos/week”).
Environment: tools/data it can access (docs, calendar, CRM).
Actions: allowed operations (search, draft, summarize, schedule).
Railguards & Review: permissions, spend caps, human approval gates.

Runbooks to write once and reuse:

SOP → API: translate your standard operating procedures into stepwise instructions agents can execute.
Maker/Checker: agent drafts; you or a second agent reviews with a checklist.
Escalation policy: when confidence < threshold, route to human.

Agent scorecard (weekly): task volume, success rate, corrections needed, time saved, incidents. Kill or retrain low-ROI automations.

Truth, Safety, and Quality: A Lightweight QA Stack

Use the FLAGS check on important outputs:

Fact-check key claims against primary sources
Links with provenance (who said it, when, where)
Agreement across models/tools (spot inconsistencies)
Grounding to your inputs (quote-back sections used)
Sanity checks (orders of magnitude, base rates, units)

Add “red-team me” clauses: “Argue against this plan in 5 bullets. What could fail? What would I wish I had checked in hindsight?”

Building Your Personal AI Stack

Foundation

A notes system (your “second brain”) with clean folders: Projects, Areas, Resources, Archive.
A private knowledge base: SOPs, templates, glossaries, exemplars.

Daily workflows to augment

Morning brief: “Summarize my calendar + draft prep notes for each meeting.”
Research: “Create a 1-pager with exec summary, sources, pro/con table.”
Writing: outline → section drafts → headline variants → fact check.

Privacy hygiene

Separate public from private contexts; strip PII from prompts.
Keep a “do-not-share” list (client secrets, health, legal matters).
Use human review for anything reputational, legal, or financial.

Career Strategy in an AI World

Be T-shaped with AI: deep domain + broad AI fluency.
Trade labor for leverage: document your best workflows, then automate the repeatable 60–70%.
Invest in human moats: judgment, taste, ethics, relationships, storytelling, strategy.

Manager tip: Treat AI like headcount. Budget time for training, evaluation, and tooling. Your job shifts from doing to designing systems that do.

Learning in Public (Without Losing the Plot)

Run micro-sprints (2–4 weeks): pick a capability (e.g., data cleanup, sales email drafts, code review), baseline it, then beat your baseline with AI.
Keep an AI lab notebook: what worked, what failed, prompts used, time saved.
Share playbooks internally; standardize wins so your team compounds.

Ethics and Etiquette

Disclose when AI meaningfully assists deliverables.
Credit original sources; link and attribute.
Consent: don’t paste private third-party content without permission.
Bias awareness: ask the model to list likely blind spots before you accept its framing.

A Calm Mind in a Fast World

It’s normal to feel displaced by sudden capability leaps. Reframe anxiety as optionality: you don’t need to master everything—only the workflows that move your goals. Start small, iterate weekly, and measure results. Curiosity beats fear; craft beats hype.

A 30-60-90 Day Personal Plan

Days 1–30 (Foundations)

Set up your notes/knowledge base; create 5 reusable prompts in your style.
Automate low-risk chores: summarizing meetings, drafting outlines, cleaning CSVs.
Establish the FLAGS checklist; never ship without it.

Days 31–60 (Agentization)

Convert one SOP into a supervised agent with guardrails and a scorecard.
Build a prompt library (10+ patterns) and a few-shot exemplar vault.
Host a “red team” session on one critical workflow.

Days 61–90 (Scale & Stewardship)

Measure ROI: time saved, accuracy improved, revenue impact.
Expand to a second agent or cross-functional use case.
Formalize privacy guidelines and disclosure norms.

Closing Thought

The world changed in November 2022 because intelligence became interactive. The adjustment we need is less about learning a new app and more about learning a new posture: designer over doer, steward over hoarder, skeptic over believer, collaborator over lone expert. Adopt that posture—and build the habits above—and you won’t just keep up with an AI-driven world. You’ll help shape it.

The Investment World Also Changed in November 2022

Historians will mark November 2022, ChatGPTs' official release month, as a fundamental milestone in human history. This was the month in which we began to chat with a machine that understands human languages, that is trained on text vastly beyond any person’s lifetime reading, that can analyze long documents much faster than a human, and that continues learning and improving every day without physical or emotional fatigue. With ChatGPT’s release, true AI jumped from research papers and niche tools into the daily lives of students, workers, creators, and executives, turning natural language into the universal interface. That moment marked the concrete beginning of a new phase in the AI revolution: not just specialized pattern recognition, but general collaboration; not just niche models playing specific games or completing specific tasks, but generative ecosystems of future assistants, agents, and copilots that write, code, reason, and design with us. Since then, generative AI has accelerated product cycles, reconfigured workflows, and reshaped debates about education, creativity, governance, and identity. In short, November 2022 is a marker between two eras.

In our view, from the ever-growing conversation between humans and generative AI machines, a new kind of intelligence may emerge. Arguably today's AI is still automated cognition devoid of true intelligence. The future may be different. In our view, once AI chatbots are given bodies (i.e. embedded or embodied into robotics) the game will continue changing and evolve into a new form of artificial life (AL). The emergence of artificial consciousness (AC) is a possibility. From there, we may see the development of what may ultimately become a new dominant species on Earth (e.g. AI Sapiens). That, of course, remains speculative sci fi for now. What is undeniably true is that since November 2022, there have been many "easy" opportunities to make money investing in AI and other trends. Back then, we recommended investing in information technology via low cost, diversified ETFs, such as Vanguard's Information Technology ETF (VGT).

VGT is a low-cost, passively managed fund that seeks to mirror the MSCI US Investable Market Information Technology 25/50 Index. It gives broad U.S. tech exposure across software, semiconductors, and hardware. It holds about 319 stocks, charges only a 0.09% fee or expense ratio, pays quarterly dividends, and is notably top-heavy today. NVIDIA (~16.8%), Microsoft (~15.0%), and Apple (~13.1%) lead the portfolio, with the top 10 holdings representing around 60% of the value of all holdings. That is, VGT gives a diversified sector coverage with meaningful mega-cap concentration in the companies best positioned to profit from the AI revolution. You are not alone investing in VGT because the fund holds almost $100B in assets under management (AUM).

Since ChatGPT’s public release on Nov 30, 2022, VGT is up about +116.0% (price-only, without counting any dividends). From a $341.08 close on 11/30/2022 to $736.83 at the Sep 25, 2025 close. This represents an annualized pace of roughly +31.4%/yr over ~2.82 years. Total return including dividends would be slightly higher.

Biggest VGT winners (price-only since Nov 30, 2022)

NVIDIA (NVDA) — roughly +950% (split-adjusted).
11/30/2022 adj close $16.92 → recent $177.69. (Investing.com)
Broadcom (AVGO) — roughly +540% (split-adjusted; AVGO did a 10-for-1 split in 2024).
Nov-2022 adj level about $52.44 → recent ~$336.

Other large winners among the current heavyweights (no exact %s here, but all big gainers over the span): Oracle, Arista Networks, Palo Alto Networks, CrowdStrike, Synopsys, Cadence, Micron, AMD, Microsoft. These names sit in VGT’s top weights today and have posted strong multi-year advances alongside the AI/software tailwind. (Investing.com)

VGT Laggards among the top-25 (few true “losers”)

Across the current top-25 holdings, almost none are actually down since 11/30/2022; the “worst” have just risen less:

Texas Instruments (TXN) — about +11% over the span (11/30/2022 close $166.24 → recent $184.99).
Cisco (CSCO) — roughly +40–50% (Nov-2022 month in the $46–$50 zone → recent ~$67).

For context, even some “old-guard” tech in VGT did very well: IBM is roughly +100% since 11/30/2022 ($135.10 → ~$281.5). (Investing.com)

AI is not the only game in town.
Since ChatGPT’s Nov 30, 2022 debut, information technology has dominated the headlines, but it hasn’t been the only winner. Hard assets and select cyclical themes kept pace or beat it: gold has more than doubled (from $1,748/oz on Nov 30, 2022 to roughly $3,770 today); Bitcoin has soared about 5–6× (from ~$17k to ~$110k); and gold miners have outpaced many tech funds (GDX from the high-$20s in late 2022 to the low-$70s now). Even outside commodities and crypto, niches like uranium miners participated (URA from about $20 in Nov 2022 to the high-$40s). Industrials also rallied, up roughly +57% (XLI from about $97 on Nov 30, 2022 to around $153 now), and international ex-U.S. equities posted solid gains of roughly +49% (VXUS from about $48.70 to $72.75), underscoring breadth beyond U.S. tech. Meanwhile, the Communication Services sector—driven by Meta and Alphabet—logged triple-digit multi-year gains across 2023–2024 that rivaled the other technology companies. In short, the post-ChatGPT bull market has been broader than just IT. (StatMuse)
And Now What?
Knowing how the human world changed in November 2022 and how are writing a significant new chapter in human history, what should we do know investment wise? Here’s our recommendation. Of course, it is not financial advice. Use it as a checklist to discuss with a professional advisor who can help you tailor it to your risk tolerance, financial goals, time horizon, and other circumstances.

Trim Exposure. Keep the AI tailwind, but don't go crazy on U.S. technology. Forward price to earning ratios are well above norms (≈22.5 vs 10-yr avg ~18.6). There has been a significant enthusiasm around AI, and reality may fall short of expectations as it is usually the case in most human endeavors. Keep core AI exposure by investing broadly in technology via diversified ETFs like VGT, but avoid chasing individual stocks, finding the next NVIDIA, or carrying any single-theme weight. Add quality/profitability and small-value tilts to counter mega-cap growth dominance. Use low-cost factor ETFs rather than stock picks.
Add global balance because foreign equities remain relatively cheaper and with equal or lesser political risk than here. Raise international ex-U.S. to a strategic weight of about 33% of your equity portfolio. Valuations are lower (MSCI ACWI ex-USA fwd P/E ≈14.6). Pair developed economies with a measured exposure to emerging markets. There is plenty of room to grow in the world. AI can be expected to be an agent of economic growth worldwide. Expanding the middle class around the world can create trillions in the next decades. Invest in the world of tomorrow, today.

Hold enough cash and Treasuries. The Fed has begun cutting rates and will face political pressure to keep cutting and devalue the US dollar. Target range 4.00–4.25% as of Sept 17, 2025 while CPI/PCE hover ~3%/~2.7%. With the 10-yr ≈ 4.18%, consider shifting part of “cash” to intermediate Treasuries (3–10y) and a barbell with T-bills for liquidity; add TIPS as inflation insurance. Codify risk rules, rebalancing cash / equity ratios frequently, keep 6–12 months of cash needs out of risk assets, and avoid leverage on speculative sleeves.
Own real assets, deliberately. Keep gold (5–10%)—official-sector demand remains supportive—and consider a small managed futures sleeve for diversification. Crypto (BTC/ETH) fits only as a high-volatility satellite (e.g., 0–5%). If buying Bitcoin, do it via low cost ETFs. There are many Bitcoin ETFs available since there approval in 2024.

Energize your portfolio. Lean into energy and utilities because they enable the global economy. While it is impossible to know who the AI winners will be, it’s predictable that the AI era will require plenty of energy and utilities. These sectors may be in bargain territory right now and pay dividends in the future as power needs help industrials, utilities, and grid/power equipment. A modest sleeve there can diversify tech beta while riding the same secular driver (data-center electricity demand is projected to roughly double by 2030).

Example, allocation template (illustrative only)

Equities 55%: 30–35% U.S. core (total market), 20–25% International (split developed / emerging), +5–10% specific sectors (technology, communications, industrials, utilities, energy).

High-quality bonds 30%: 15–20% U.S. Treasuries (laddered 3–10y), 5–10% TIPS, 0–5% international bonds.

Diversifiers 10%: 5–10% gold; 0–5% other commodities.

Optionals 5%: find plays that interest you (e.g. Bitcoin); go crazy, but just with 0–5% of your money depending on your risk tolerance.

Remember to rebalance periodically to keep the chosen allocation.

Conclusion — Two Landfalls, One Choice

530 years separate October 1492 and November 2022, yet both dates describe the same human gesture: stepping onto an unknown shore and deciding what kind of world to build from it. Columbus’s landfall redrew maps, minted empires and fortunes, and left scars that still ache. November 2022 was the AI landfall, the moment language models became everyday collaborators begun to redraw workflows, institutions, and power, with winners clustering around compute, data, and the skills to orchestrate machines. The analogy is clarifying but also cautionary. In 1492, ships, ports, and chartered companies structured the future. Today, models, platforms, and energy-hungry infrastructure projects are restructuring the future. In 1492, compasses and caravels rewarded navigators. Today, prompts, agents, and judgment are rewarding entrepreneurs, investors, and owners. The lesson is not inevitability but responsibility: we can choose exploration without exploitation, productivity with dignity, invention with accountability. If 1492 launched the Age of Colonization, let 2022 inaugurate an Age of Collaboration worthy of its promise—where the dividends of intelligence at scale may flow broadly, where transparency and safety may govern the frontier, and where human flourishing, not mere efficiency, remains our North Star.
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