t = t₀ + Δt · (signal strength)
"The future is not some place we are going, but one we are creating. The paths are not to be found, but made. And the activity of making them changes both the maker and the destination."
Overview
I've been playing with this simple formula for a while: future time equals present time plus the time delta multiplied by how strong the signal is.
It basically means the future isn’t purely random, you can forecast it by looking at how today’s signals relate to yesterday’s and how strong they are. For me, that looks like tracking where money flows, where people move, and what gets funded.
Lists like Forbes 30 Under 30 are one of those signals. Yes, some people buy placements, work with publicists, or get scouted. But the bigger point is this: most honorees have a real story to tell and are genuinely relevant to the time we’re living in.
The 2026 list just dropped, I reviewed it, and here are my takeaways.
The list as a diagnostic tool
In January 2012, Forbes launched the inaugural 30 Under 30 list to highlight founders and leaders building the next big thing. Every year since, they have celebrated top young talent across industries shaping the future of business and culture.
Over 15 years, 46 alumni have become billionaires like the founders of Stripe, Snapchat, and Spotify. But nothing has created wealth at the rate of the current AI wave. 19 of those 46 billionaires crossed the threshold since the start of this year alone (source). As noted in the article, “the requirements to be a pioneering entrepreneur remain constant: imagination, intelligence, and plenty of grit.”
Honestly, the timeline from having an idea to actually building something real is so much shorter now. The tools are better, capital is way more accessible, and you don’t have to wait until your 30s to do meaningful work anymore & I’m feeling energized + pressured!
What the 2026 numbers reveal
This year's class: 600 honorees.
“To create the Under 30 list, Forbes reporters harness their authoritative reporting, robust sources, and independent experts. Judges this year include pop sensation Olivia Rodrigo, actress Yara Shahidi, billionaire entrepreneur Palmer Luckey, AI50 startup founder May Habib and basketball player Kyle Kuzma. More than 10,000 candidates were evaluated on their impact, financials and potential to scale. The result? 600 young leaders across 20 industries who are impacting both culture and economies.” (source).
$3.8 billion in cumulative funding, up from $3.6 billion last year.
Average age: 27. The youngest is 17.
70% are Gen Z. This is the final list that will include any millennials (source).
68% are founders or co-founders. The rest are creators building personal brands. Either way, they are building.
22% are immigrants, from China, India, Mexico, Korea, Australia, and elsewhere.
The geography of young success
The top cities where honorees live, in order:
New York
San Francisco
Los Angeles
Boston
Chicago
Austin dropped off after making the list last year. This did not surprise me because I have been noticing the declining AI/tech activity in there.
These cities are what Brookings refers to as Superstars or Star Hubs, which I wrote about in my previous post on The Digital Divide 2.0. The places with the most AI jobs, the deepest talent pools, and the most active builder communities. It’s also where the AI investment and infrastructure are clustering. That’s where young founders go because that’s where things are actually happening.
They have the right mix of infrastructure, talent density, capital, meetups, investors.
Austin slipping off doesn’t mean anything dramatic yet, but it is a signal to pay attention to. Cities rise and fall based on whether they can keep the people who build the next thing.
Capital, talent, and infrastructure create their own feedback loops. If you’re working on something that needs compute, investors, and people who “get it,” you naturally gravitate toward places with density. That’s just how systems behave.
The velocity problem
What really shocked me is how new most of the AI companies on the list actually are. Almost all of them were founded in 2023 or 2024, not ten years ago. Literally two years ago… some even less.
Decagon? The $1.5B customer-service AI that powers ClassPass and Duolingo? Founded in 2023. Axiom Math, the one started by 24-year-old Carina Hong raised $64M at a $300M valuation in under a year. It’s wild to me.
The gap between having an idea and hitting unicorn status has gotten so short that it barely feels real. When I was working with a VC team last year, the average timeline was about four years. Now we’re seeing companies go from zero to “how did we ever live without this?” in basically one product cycle. Wild!
And Jesse Zhang, Decagon’s founder, said it perfectly: when there’s a big tech shift, tons of companies pop up, but only a few ideas are actually good. For me, its really about sourcing and analyzing the ones are actually good.
Patterns across categories
I went through the full list and noticed a few things. Not just what people are building, but how they are building it.
AI
What blows my mind is how young these AI companies are. Decagon (2023), TensorWave (2023), Paraform (2022), Legora (2023). But here’s the part people overlook: we’re not just automating tasks. We’re automating how we sense, interpret, and respond to the world.
Think about customer service, recruiting, research. They’re where you complain, get reassurance, ask for help, explain what you need. And Decagon’s whole pitch is basically: “We want to build the smartest, most human-like, most empathetic agents.” Focus on the “empathetic”. They want you to forget you’re talking to an algorithm.
Same with what Isa Fulford is doing at OpenAI with Deep Research and ChatGPT Agents. These tools can browse the internet, book hotels, return shoes, pull info from public and private sources. That’s perception. It’s gathering information, making sense of it, then acting on it.
For me its like, wow, these companies aren’t building cute consumer apps. They’re building the pipes ! Serious infrastructure others will rely on & I always say that when you build infrastructure, you’re betting on what the whole ecosystem will need next. And right now it’s obvious: automation, compute, and talent pipelines.
What this means for next year:
– More agent-based systems
– More infrastructure plays around who controls the chips, cloud, training pipelines
– AI in places you didn't expect
– More intelligence embedded in how we sense, interpret, and respond
Manufacturing & Industry
The innovations aren’t flashy at all. It’s stuff like 3D-printed housing, new metals for supply chains, industrial lasers, plant-based materials stronger than steel, battery diagnostics for the grid. But if AI is the brain, this is the skeleton.
Zane Hengsperger learned metals in his family’s machine shop and now runs Nox Metals with $4.6M raised. Anand Lalwani built Cardinal Robotics after watching hospital janitors risk COVID; they now service Hilton, Caesars, Bank of America, and MGM with projected 2026 revenue of $6M+. Joshua Yang couldn’t access lasers in his Stanford lab, so he helped create Brightlight Photonic’s chip-scale titanium:sapphire laser ($1.7M raised). Nick Callegari’s Verustruct is 3D-printing cost-efficient housing ($2.4M pre-seed). Soarce turns plant waste into a material 8x stronger than steel ($2.8M raised). FlowCellutions builds diagnostics for grid-scale batteries ($600K raised).
The bigger point: we can simulate anything digitally, but we still need housing, materials, batteries, and supply chains that actually work. The gap between what we can model and what we can manufacture is widening and these founders are closing it.
And while their funding is tiny compared to AI, their customers are massive: hotels, casinos, banks, hospitals, data centers, the electrical grid. It’s slower and less glamorous, but essential and worth watching.
What this means for next year:
– More pressure on traditional manufacturers to adopt new tech
– More startups will focus on domestic manufacturing
– More robotics for cleaning, maintenance, inspection
– Energy infrastructure will become a competitive advantage
Retail & Ecommerce
We’re moving into a hyper-sensory era of commerce. You can see it in fragrance, in Moldovan-inspired barware, in Hoppn’s color-wheel search tool. These are sensory interfaces. You’re shopping through smell, color, texture… not keywords.
This is what I've been thinking about with the eight perceptual systems: Taste, Scent, Touch, Sight, Sound, Space, Time, System. Retail is shifting from utility to perception, and AI is becoming the invisible sales associate. Corvane turns CRM data into real shopper insight, Phia scans 40,000 fashion sites for the best price, and Hoppn lets you search by feeling, not description.
The bigger shift: keyword search is fading. We’re heading toward visual search for texture, scent profiles for discovery, audio cues that influence purchase. Commerce is starting to speak to all eight senses.
Retail is also breaking into micro-communities: Pilates studios, fragrance lovers, exotic car circles. LuxConcierge thrives on repeat and referral; Ace Grip Socks spread through studios, not ads. Brands that succeed aren't trying to reach everyone. They're trying to become essential to someone. And once they do, the network effects are powerful.
And the shopping journey isn’t linear anymore. It’s multi-sensory and multi-modal: color scans, price alerts, secondhand options, unboxings, reviews, authenticity checks, all before checkout. Retail used to be want → search → buy. Now it no longer happens in one moment, like typing something into Google and buying it.
Instead, products follow you around your entire digital life; you see them on TikTok, then in a newsletter, then in a price alert, then in a “similar items” carousel, then in a resale recommendation. So by the time you’re actually ready to buy, you’ve already been nudged, informed, reminded, and reassured across multiple touchpoints.
The algorithm brings you in. The community and sensory experience make you stay.
What this means for next year:
– Every brand needs an AI layer
– Color, scent, and texture become search parameters
– Luxury becomes service, not price point
– Community becomes the storefront
Food & Drink
We have personalized music (Spotify), video (Netflix), shopping (Amazon). Now we are personalizing flavor.
And this connects directly to how I think about Taste: Systems Intelligence applied to gastronomy. Flavor isn’t just “what tastes good”; it’s chemistry, culture, memory, and technique layered together. When something tastes right, a whole system aligned.
You can see that in the founders leading this shift.
Maggie Tang’s Magic helps restaurants like Carbone and Momofuku remember your preferences and anticipate what you’ll want. It makes dining feel personal again, the same way a perfect playlist feels like someone knows you.
On the retail side, Sauz’s miso-garlic marinara, Protein Pints in 8,000 stores, and Transcendence Coffee’s baklava and gulab jamun syrups show how flavor becomes cultural translation.
And the business models are splitting in two directions. Nicolai Mlodinow runs a profitable 16-seat restaurant & speakeasy called Class Act built on intimacy. Tini Younger scales through virality with 14M followers and major brand collaborations. One grows through community online; the other grows through presence offline. Both work.
What this means for next year:
– AI goes deeper into hospitality
– Heritage flavors will become more popular in mass retail (I’m in favor of the “ethnic aisle” is disappearing!)
– Creators become restaurateurs (and vice versa)
– Wellness converges with indulgence
Media
One thing that really stood out to me is how media has flipped. The audience is the business model now, not the product. Creators aren’t just building followings anymore; they’re building actual institutions.
Look at Kimberly Bizu. She started Rich Little Brokegirls in 2022, and now it’s basically a whole media company: 350k followers, a podcast with half a million downloads, big events, and partnerships with Google, Disney, L’Oreal. Or Eli Rallo, 1.3M followers, two books, and her own literary community.
And the bigger insight here is that platforms are just infrastructure. The best creators aren’t trying to “win” on TikTok or Instagram. They’re using those platforms to distribute, then owning the actual IP, the format, the relationships. Tariro Makoni is a perfect example, she launched Trademarked on Substack in mid-2024. Six months later she had 6,500 subscribers, 80k monthly readers, was Top 100 on Substack, and now she writes for Marie Claire and Vogue Business.
It’s basically: build your credibility independently, then get invited into the legacy institutions, not the other way around. Your newsletter becomes your portfolio. Your subscribers are your proof. And traditional media is starting to act more like a distribution partner for creators than the main stage.
What this means for next year:
– More creators will build vertically integrated businesses
– Customization will become the expectation
– Analog formats will resurge as digital antidotes
– Independent writers will outpace legacy institutions
What this tells us about time
Everything we’ve talked about (AI hubs, migration patterns, retail shifts, hospitality, infrastructure, flavor, founders) all points to the same idea about time:
The future shows up early if you know how to read the signals.
That’s really what the formula t = t₀ + Δt·(signal strength) is saying.
Strong signals shrink the distance between now and next. The future doesn’t just “arrive,” it becomes more visible.
And the more literate you are in the signals (AI and technology, talent density, capital flow, cultural taste, infrastructure gaps, sensory patterns, personalization, community, scarcity, scale), the more you realize what’s already happening, before it becomes obvious.
That’s what I see the Forbes list as, a mirror of the moment and snapshot of what this time values.
Thank you for thinking with me. This piece is part of Ode by Muno, where I explore the invisible systems shaping how we sense, think, and create.
I'm curious what patterns you're noticing. Which sector surprised you? What signal feels strongest to you? Leave a comment with what resonated, or share this with someone building something that matters.
The opening quote is from political theorist John Schaar. The framework of "future time = present time + (Δt × signal strength)" is inspired by systems thinking and predictive modeling.
In my next post, I'll explore experience as a function of density and duration, how choosing a city, building a career, or planning travel all follow the same underlying logic. Spoiler: Tokyo demands speed. Kyoto demands slowness. And knowing the difference changes everything.
