耶鲁大学公共卫生学院 Becca Levy 教授及其团队的长期追踪研究，对衰老持有更积极自我认知（positive self-perceptions of aging）的老年人，平均寿命长出约7.5年。对创始人而言，长期主义心智的本质，是把韧性当成组织的核心基础设施 —— 你永远不能靠透支的身体、涣散的团队去完成关键跃迁。
Inside OpenEvidence’s $12B Rise: The Playbook Winning AI Companies Share
In eleven months, OpenEvidence went from a $1 billion valuation to $12 billion. By April 2026, the company reported that its platform was being used by approximately 65% of US physicians and supported nearly 27 million clinical consultations that month, with much of its adoption attributed to physician word-of-mouth.
Think explosive growth is just about having the best AI tech? It’s not. If you look at the AI companies truly scaling today, their real competitive edge is deep market insight. Too many founders skip this step because they’re rushing to build something impressive instead.
Many view AI as a dragon coming to burn down their industry. But it also represents transformative and generative power. If you cannot outmuscle a force like that, you learn to ride it to become stronger.
As AI shifts from a simple tool to an autonomous agent, completing complex work with less and less human intervention, founders face a clear choice: draw a sword, or learn to fly.
Qian and the Anatomy of a Founder
The I Ching (Book of Changes), an ancient Chinese philosophical text, uses the dragon as a central metaphor in its first hexagram, Qian (The Creative). It tracks a dragon through six stages of maturation — from total obscurity to full command of the sky. It perfectly mirrors the modern founder’s journey.
Peter Diamandis, founder of the XPRIZE Foundation, describes five mindsets that keep people stable and effective through accelerating change: curiosity, abundance, exponential thinking, longevity, and moonshot thinking. Map them onto the dragon’s ascent and you get an operating system for building through the AI era — one altitude at a time, plus a warning at the top that most founders skip.
1. Hidden Dragon — The Curiosity Mindset
“The dragon is hidden. Do not act.”
1. Hidden Dragon — The Curiosity Mindset
At the earliest stage, the market doesn’t know you exist, and that’s fine. This is a research phase. The Curiosity Mindset is the fuel: what specific problem does this technology actually solve, for whom, better than the current alternative? Curiosity prevents premature action and allows you to deeply understand the landscape before making your move.
2. Dragon in the Field — The Abundance Mindset
“The dragon appears in the field. It furthers one to see the great man.”
2. Dragon in the Field — The Abundance Mindset
You launch, and suddenly you’re standing next to other companies with more computing power, more data, and more capital than you’ll ever have. This is where scarcity thinking kills founders, treating AI as a fixed pie that a handful of giants will win.
An abundance mindset realizes that AI is driving the cost of intelligence toward zero, baking an infinitely larger pie. You now have the tools to build things that would have required a much larger engineering team just a few years ago.
3. The Diligent Dragon — The Longevity Mindset
3. The Diligent Dragon — The Longevity Mindset
“All day long the superior man is creatively active. At nightfall his mind is still beset with cares. Danger. No blame.”
This is the grind. You have entered the market and are building furiously, but the psychological and physical pressure is immense. You are active all day, yet anxious at night. To survive this perilous phase of non-stop execution, founders must adopt the Longevity Mindset.
A Yale study led by Professor Becca Levy found that older adults with more positive views of aging lived about 7.5 years longer. For founders, the Longevity Mindset applies this same logic to the body and the organization: you cannot reach the next stage on a burned-out founder or a brittle team. Resilience works as load-bearing infrastructure for the leap itself.
4. Leaping Dragon — The Exponential Mindset
4. Leaping Dragon — The Exponential Mindset
“The dragon leaps over the abyss. No blame.”
This is the scaling phase, the most dangerous part of the journey. To cross the chasm, founders must adopt the Exponential Mindset.
Human brains are wired to think linearly, but AI advances exponentially. The Exponential Mindset means architecting for where the model will be in eighteen months, not where it is on launch day.
Founders who build their product roadmap against today’s capability ceiling are already building a legacy product. You must anticipate the leap, building infrastructure that scales with the compounding intelligence of the models themselves.
5. Flying Dragon — The Moonshot Mindset and Scenario Maturity
5. Flying Dragon — The Moonshot Mindset and Scenario Maturity
“The flying dragon is in the heavens. It furthers one to see the great man.”
The Moonshot Mindset treats “impossible” as an unsolved engineering problem rather than a wall. But a moonshot without a landing site is just a hallucination with better production values. What separates a flying dragon from an expensive fireworks show is Scenario Maturity — a check on whether the specific use case you’ve chosen, not the technology in general, is actually ready to fly.
That means asking harder questions, such as:
Is there a real buyer, with real budget and real urgency, ready to act now rather than someday?
Does the workflow generate a feedback loop that compounds in your favor the longer you run it?
Can today’s models actually do the job reliably at the point of use?
Get that match right, and the moonshot has somewhere to land. Chase ambition alone, and you’ve built a very well-funded crash.
Case in Point: Open Evidence
Open Evidence is an AI-powered medical search engine and clinical decision-support platform that allows verified healthcare professionals to ask complex medical questions and receive rapid answers grounded in peer-reviewed literature. It demonstrates scenario maturity through a precise, high-stakes alignment of buyer, monetization, moat, and capability match:
The Buyer & Monetization: Targeted physicians making time-sensitive decisions at the point of care. Instead of inventing a new budget, it tapped into existing pharmaceutical marketing dollars by keeping the tool free for verified doctors and monetizing via contextually relevant pharma advertising.
The Moat: Built exclusively on peer-reviewed medical journals and direct content partnerships with elite institutions like the American Medical Association and the New England Journal of Medicine. The data asset is compounded by proprietary, verified clinical consultation loops that competitors cannot easily replicate.
The Capability Match: Bounded the problem domain tightly to clinical medicine rather than attempting open-ended consumer chat, allowing current-generation models to maintain exceptional reliability.
That combination, not a superior model, is what turned a niche physician tool into the fastest-scaling case in the sector.
One Line Further: The Arrogant Dragon
One Line Further: The Arrogant Dragon
The Qian hexagram doesn’t stop at the flying dragon. Its sixth and final line describes a dragon that has flown too high — an overreaching dragon with cause for regret. It’s the founder who mistakes access to a powerful model for scenario readiness, and pours capital into the most exciting application instead of the most prepared one.
The lesson isn’t to stop climbing. It’s to keep re-checking, at every altitude, whether the business, the data, and the technology are actually ready for where ambition wants to take you.
The Human Edge: Judgment Over Data
If AI can already process the available information instantly, where does human advantage come from?
Howard Marks, co-founder of Oaktree Capital, drew this line decades before anyone was worried about AI:
first-level thinking stops at the obvious conclusion;
second-level thinking asks what everyone else is missing, and what happens next because of it.
AI has made first-level thinking free — any model can summarize the data, the consensus, the obvious take, instantly. That pushes the entire edge left for founders and investors up to the second level:
Judging the second-order effects of what the data actually implies, not just what it states.
Weighing what can’t be measured — management quality, grit, the structural maturity of a scenario.
Deciding, on conviction, which future is worth building toward before the market has agreed with you.
The Human Edge: Judgment Over Data
AI is an incredibly powerful engine, but it lacks a soul. It lacks intent. Understanding the limitations of AI allows us to shed the victim mindset and reclaim our natural birthright as creators.
No matter how powerful the machine becomes, the human founder still evaluates the scenario and sets the destination – at least for now. We remain in charge of our lives, fully capable of shaping our own destinies.
Do not fear the dragon. Find your scenario, and ride it.
本届 WAIC 最让人惊喜的创业故事，不是大厂的重磅发布，也不是实验室的技术突破，而是一个一人公司（OPC）跑出的项目 ——TideFlow AI 个性化睡眠决策系统。
创始人吴松芸没有医学背景，创业的起点只是自己长期受失眠困扰的真实体验。 她的核心洞察很精准：很多人失眠不是环境不好，而是大脑长期处于高唤醒状态，没法自然从清醒过渡到睡眠。TideFlow 用 AI 实时感知用户状态，动态匹配放松音频、呼吸引导等干预方案，帮大脑自然入睡，区别于市面上千篇一律的白噪音、冥想产品。
Your tokens are cheap. Your model is open-source. So what do you actually own?
That question shaped my review of WAIC 2026, held in Shanghai.
More than 1,100 companies presented over 3,000 exhibits. But the real divide was not between larger and smaller models. It was between technologies that attract attention and those approaching defensible, revenue-generating deployment.
WAIC 2026 Shanghai
Over three days, I examined the most relevant medical AI cases through the Mans International SMAF lens: the Scenario Maturity Assessment Framework, which looks beyond model parameters to assess proprietary data, workflow integration, buyer readiness, trust and commercial scalability.
Three trends stood out and they were not equally mature.
Trend 1: The moat moved from the model to the data
Leading companies are no longer applying general models directly to medical questions; they are building “medically enhanced large models” grounded in exclusive data.
A prime example is Baichuan Intelligence’s “Futang·Baichuan’s pediatric model. It was developed with Beijing Children’s Hospital using the clinical expertise of more than 300 paediatric specialists and decades of high-quality, de-identified medical records.
The results are striking: in a head-to-head against 12 attending and resident physicians on 60 real outpatient cases, it hit 91.7% diagnostic accuracy, nearly 15 points above the human average, with 92% medication-safety compliance. It now lives in daily multidisciplinary clinics and is rolled out to 150+ county hospitals in Hebei.
Trend 1: The moat moved from the model to the data
China also presents a compelling initial scenario. Leading paediatric expertise is concentrated in major hospitals, while primary-care and county-level institutions often lack experienced specialists. AI could help distribute medical expertise more widely, not by replacing doctors, but by allowing expert knowledge to travel across institutions and regions.
SMAF read: A static dataset can eventually be copied. A clinical system that improves through validated feedback from each deployment becomes increasingly trusted and harder to replace.
Trend 2: Embodied AI is dazzling — and still maturity-gated
United Imaging Intelligence’s equipment-data-algorithm stack is a real hardware moat that pure software players can’t easily copy. And the humanoid demos were the crowd favorite: Galaxy General’s “AstraBrain” architecture driving a robot through folding laundry and making breakfast; Fourier Intelligence’s GR-3 Care-bot executing a full intent-to-action loop from a spoken “I’m thirsty”; Optics Valley Dongzhi’s “Photon” robots handling patrol, companionship, and health monitoring in elder-care settings.
Trend 2: Embodied AI is dazzling — and still maturity-gated
Impressive. Not yet mature. Getting a robot from a booth into a home or hospital means clearing three hurdles that don’t show up in a product demo:
Safety — the care recipients are disabled or elderly; failure tolerance is close to zero.
Privacy — continuous in-home data collection needs real consent architecture, not a terms-of-service checkbox.
Humanity — the job is care, not just task completion. A robot that folds shirts perfectly but feels clinical hasn’t solved the actual problem.
SMAF read: high potential, low current maturity. This is the category where the technology outpaces the scenario — worth watching, not yet worth pricing as though it’s solved.
Trend 3: Narrow problem, Real payers — OPC models are proving maturity can be earned fast
The most interesting founder story at WAIC wasn’t a lab spinout. TideFlow AI, an “AI personalized sleep decision system” was built solo by Wu Songyun, no medical background, just her own struggle with insomnia.
Trend 3: Narrow problem, Real payers — OPC models are proving maturity can be earned fast
TideFlow’s core insight is that insomnia often stems not from a poor environment, but from a hyperaroused brain. The system uses AI to perceive the user’s state in real-time, dynamically matching intervention plans to help the brain naturally transition into sleep. After 12 iterations, this highly personalized, lightweight business architecture stepped onto the global stage, acquiring real paying users overseas.
SMAF read: this is what fast-tracked maturity looks like — a narrow, well-defined pain point, a founder close enough to it to iterate quickly, and payers who validate the solution before the funding round does.
The Mans International Takeaway
In this profound transformation, the core of industry competition is undergoing a structural reshaping from “Model IQ” to “Scenario EQ.” This is not short-term technological hype; it is a fundamental shift in the logic of value creation, capture, and defense.
Navigating this structural change requires far more than financial reports and model parameters. It demands a precise grasp of regulatory boundaries and a professional analytical framework capable of systematically assessing scenario maturity and identifying strategic gaps. This is precisely the design intent behind the Mans International SMAF.
Ultimately, every medical AI participant must confront a fundamental question: Is your AI strategy designed to win brief applause at the exhibition booth, or to truly crack the real industry dilemma of waiting three hours to see a doctor for five minutes?
If you’re trying to figure out where a specific medical AI bet actually sits on that maturity curve — or how to position a product for international scaling — that’s the exact gap SMAF was built to close. Happy to compare notes.
Mans International applies the Scenario Maturity Assessment Framework to help technology founders and investors distinguish technical readiness from commercial, workflow and ecosystem readiness—particularly across China and international markets.
The I Ching (Book of Changes) states: “Heaven’s movement is ever vigorous; thus, the noble person constantly strives for self-improvement.” This underlying force of relentless self-renewal, regardless of the circumstances, has found its most extreme validation in the practice of Mr. Cai Lei.
An ALS breakthrough: A master class in Deep-Tech Ecosystem Building, Founder Resilience, and SMAF
In 2019, Mr. Cai Lei, a former vice president of JD.com and one of the pioneers behind China’s electronic invoice system, was diagnosed with amyotrophic lateral sclerosis, or ALS. He was 41. He had just welcomed a new child. His career, family, and life were all at a peak moment.
Then came the diagnosis. ALS is often described as one of the most devastating neurodegenerative diseases. The average survival window after diagnosis is often only a few years.
Seven years later, in 2026, his body function score plummeted from 48 to 4. He is completely paralyzed from the neck down, his vocal cords have severely atrophied, and he relies on a liquid diet and a 24-hour ventilator to survive. Across his entire body, only his eyes remain under his autonomous control.
Cai Lei before and after ALS
Yet, Cai Lei’s story is far more than an inspiring narrative of resilience and empathy. Analyzed through the Scenario Maturity Assessment Framework (SMAF), it stands as a textbook masterclass in deep-tech scenario breakthroughs. It is a blueprint of how to take a globally recognized “unsolvable dead end” and reconstruct it into a high-maturity, self-sustaining ecosystem of research collaboration and commercial translation.
I. Deconstructing the Breakthrough via SMAF: A High-Maturity Super Ecosystem
At Mans International, we utilize the SMAF (Scenario Maturity Assessment Framework) to evaluate the commercial viability and translation potential of deep tech ventures. We have seen too many projects perish in the “slide deck” phase or or “lab-only self-indulgences.”
From a scenario maturity perspective, the true brilliance of Cai Lei’s “ice-breaking” initiative is not simply his unwavering belief, but his methodical execution. He took a highly fragmented, chronically inefficient rare-disease scenario — one lacking adequate resource attention — and orchestrated it into a synchronized system uniting patients, data, research, clinical trials, capital, AI, and public trust.
1. Data and Workflows: From Scattered Patients to R&D Infrastructure
One of the greatest bottlenecks in rare disease R&D is scattered patient populations, scarce biological samples, and a lack of real-world data. Often, research does not lack direction; it lacks a stable, continuous, and actionable data foundation.
The Data Engine: Cai Lei built the “Jianyu Mutual Aid Home,” the world’s largest civilian ALS research database (over 18,000 registered users), housing tens of thousands of structured real-world cases. He also launched an “ALS Research AI Brain,” training 24/7 on over 20 million interdisciplinary papers to automatically filter and evolve targets without burdening researchers.
The Workflow: This 360-degree dynamic vital-sign tracking system compresses notoriously slow clinical recruitment to astonishing speeds — achieving “hour-level” responsiveness (i.e. 700 sign-ups in 2 hours; launching clinical trials within 3 months).
Data and Workflows: From Scattered Patients to R&D Infrastructure
2. The Business Closed Loop: A Mechanism for Long-Term Sustenance
Rare disease research cannot survive solely on short-term donations or one-off grants. Drug discovery features long cycles, high failure rates, and relentless capital demands, while external funding environments and public attention fluctuate. Without a stable financial engine, even the grandest mission will bleed out mid-way.
The partnership forged between Cai Lei and his wife, Duan Rui, perfectly demonstrates the synergy of vision and operations. Many view Duan Rui’s live-streaming efforts purely as a “wife’s sacrifice.” While deeply moving and true, from a strategic perspective, it is a brilliantly designed commercial closed loop.
Cai Lei continually raises the ceiling of their mission — connecting patients, scientists, pharma, and society. Meanwhile, Duan Rui absorbs the immense operational realities: live-streaming revenue, team management, cash flow, cost control, and risk mitigation. This closed-loop of “front-end commercial revenue funding back-end R&D burn” provides a continuous lifeline for a highly uncertain, long-cycle scientific endeavour.
The Business Closed Loop: A Mechanism for Long-Term Sustenance
3. Narrative & Ecosystem: Evolving from Empathy to Industry Consensus
Before Cai Lei, ALS was trapped in a weak narrative within public and industry discourse — viewed merely as an “incurable and unprofitable” tragedy. It garnered generalized sympathy but lacked actionable pathways.
Cai Lei elevated this narrative fundamentally. He did not stop at emotional appeals for awareness; he broke down rare-disease R&D into actionable industry propositions. He allowed the scientific community, the biotech industry, and the public to clearly see their specific roles and value.
This mature narrative has penetrated industry silos, uniting over 60 global research teams and 50+ biotech companies, transforming an untouched “cold sector” into a highly coordinated battlefield with shared consensus, pooled resources, and a synchronized tempo.
Narrative & Ecosystem: Evolving from Empathy to Industry Consensus
II. The Founder’s Mirror: Resilience for Global Founders
In his recent “Countdown” speech on Global ALS Day, June 21, 2026, Cai Lei said he had already defeated an enemy more terrifying than ALS: despair.
For founders today — navigating agonizing market cycles and high-stakes survival tests — Cai Lei’s mental fortitude serves as a profound mirror:
Reject the Victim Mentality. Complaining about the macro environment or the “capital winter” yields zero value. Completely paralyzed and unable to speak, Cai Lei never wallowed in the unfairness of fate. He immediately pivoted his strategy, utilizing an eye-tracking device to launch a race against time. Radical acceptance and execution to the absolute limit are the foundational ethics of a founder.
Pry Open Incremental Gaps in Dead Ends. Cai Lei noted: “You might think there is only a solid wall in front of you. But look down, there might be a path; turn sideways, there is a gap. You can even choose to climb over or dig through.” When traditional funding tightens and cross-border barriers rise, a founder’s core competency is leveraging tools — like AI and cross-disciplinary ecosystems — to pry open growth spaces ignored by the mainstream.
Anchor Your Venture in a Grand Proposition.“The best way to overcome fear is to place yourself within a much greater cause.” When your corporate vision is tied to core societal challenges — hard tech breakthroughs, life sciences, energy transitions — the resilience you unlock will far surpass what secular fame or profit can sustain.
Pry Open Incremental Gaps in Dead Ends
III. Conclusion: The Countdown is a Prelude to Victory
In Cai Lei’s room, four clocks sit ticking. The media calls it the countdown of his life. He corrects them: “This is my countdown to ALS.”
“If my eyes fail, I will connect to a Brain-Computer Interface. If my brain stops turning, I will upload my consciousness to an embodied robot. I have marched all the way to the face of this terminal illness, and I am not here to surrender.”
As heaven’s movement is ever vigorous, so must a leader ceaselessly strive along.
The Countdown is a Prelude to Victory
Here is to all the founders who keep walking through the valleys of economic cycles. Here is to the researchers grinding relentlessly in their labs. Here is to all those who refuse to bow to fate.
Do not ask where the hope lies. Keep moving forward, and hope will reveal itself. As long as you do not retreat, every direction is the way forward.
Global Strategic Partnership
Leading global research institutions, multinational pharmaceutical companies, biotech innovators, and international funds are invited to partner with Mans International to access and navigate high-maturity life science and deep-tech ecosystems.
Through our SMAF — Scenario Maturity Assessment Framework — we help identify where technology, capital, clinical resources, market readiness, and ecosystem trust can be precisely aligned.
Our goal is to reduce cross-border and cross-sector friction, accelerate clinical and commercial translation, and support breakthrough technologies and strategic capital in moving from promise to real-world impact.
In Week 1 of the Mans International SMAF Sprint 2026, I revisited Insilico Medicine to stress-test the AI-drug premium. The conclusion was clear: the premium is no longer given for technical ambition; it must be earned through measurable scenario maturity.
This week, the SMAF Compass™ 2.0 moves from AI biotech to space infrastructure, frontier AI, and physical robotics.
The case is SpaceX. Through the SMAF lens, the IPO is a scenario-premium case: where investors are being asked to price several maturity layers at once.
Starlink is the current commercial maturity anchor.
Starship is the future capacity promise.
xAI and Grok are the AI imagination layer — but also the unresolved maturity gap.
This raises a harder question: Can mature infrastructure scenarios carry less mature AI scenarios inside the same valuation premium?
That is where the Scenario Maturity Assessment Framework, or SMAF Compass™, becomes useful.
Deconstructing the SpaceX Bundle via the SMAF Lens
A traditional IPO asks investors to value a business. The SpaceX IPO asks investors to value a system: reusable launch, Starlink, Starship, xAI, and the broader Musk narrative.
Deconstructing the SpaceX Bundle via the SMAF Lens
Starlink is the Anchor
Business Maturity: Starlink is the undisputed commercial anchor of the IPO. It has translated deep-tech capability into high-margin, recurring global revenue. From maritime communication and enterprise backup to national defense resilience, the pain point is urgent, the buyer is clear, and the value-capture path is proven. Without Starlink’s business maturity, the broader IPO valuation would be highly fragile.
Data Maturity: Starlink creates a compounding intelligence loop. More users and traffic generate richer network data, which improves routing, reliability, and performance. Better performance increases adoption, and greater adoption deepens the data advantage.
Starlink is the Anchor
Starship is the Capacity Promise
Narrative Maturity: Starship nails this pillar. It gives the market a canvas for its grandest space-based imagination — lunar missions, orbital data centres, and Mars colonization. It converts staggering technical complexity into a highly memorable story of future capacity optionality.
Starship is the Capacity Promise
However, while its Narrative Maturity is maximum, its short-term Business Maturity remains an unproven future option.
xAI is the Unresolved Layer
Workflow Maturity: This is the core maturity gap in the bundle. xAI and Grok inject a massive “AI imagination premium” into the valuation. Yet, serious enterprise and government users still face immense workflow friction: model differentiation, data trust, and deep operational integration.
xAI is the Unresolved Layer
Right now, a highly mature infrastructure scenario (Starlink) is actively carrying a far less mature workflow scenario (xAI) inside the same valuation story.
The Strategic Takeaway for Founders and VCs
Capability shock is not scenario maturity.
A technology company becomes truly investable only when the surrounding scenario matures enough to absorb the innovation and convert it into durable, compounding value.
When evaluating your own tech stack or investment pipeline this quarter, step away from technical specs and ask the tough SMAF questions:
What is your business maturity anchor? What working scenario is generating the predictable revenue needed to subsidize your future bets?
Is your narrative outpacing your workflow? If your Narrative Maturity is a 10, but your Workflow Maturity is a 2, your valuation premium is dangerously fragile.
In the frontier tech era, technology maturity is merely the baseline for entry. Scenario maturity is where the premium is actually earned.
Scenario Maturity is the Premium
Join the Mans International SMAF Sprint 2026
This assessment is Week 2, Case Study 02 of the Mans International SMAF Sprint 2026.
If you are a tech founder, deep-tech VC, industrial leader, or cross-border strategy decision-maker navigating AI, robotics, space infrastructure, or US-China technology decoupling, do not wait for the market to expose the gap.
Your technology may be strong. Your narrative may be compelling. But if the scenario is not mature enough, adoption, revenue, and valuation will eventually break under pressure.
Let’s identify the strategic gaps before the market corrects them.
Send us a direct message to request the proprietary SMAF Compass™ Briefing.
Insilico Medicine and the AI-Drug Premium: A SMAF Stress Test
I first analyzed Insilico Medicine in my 2023 book, when it became one of the most visible pioneers in AI-driven drug discovery.
By 2025, Insilico’s narrative moved beyond sheer R&D velocity. It had become a test of whether AI could translate biological insight into clinically meaningful, commercially viable assets in longevity and age-related disease — through tools like PreciousGPT and its lead asset, Rentosertib.
In 2026, the story became more complex.
Despite a milestone-based Eli Lilly collaboration worth up to $2.75 billion, including a $115 million upfront payment, Insilico’s public-market narrative remains under pressure after a $352.3 million net loss for 2025 and sharp volatility on the HKEX.
That is why I chose Insilico Medicine as an early case for the Mans International SMAF Sprint 2026.
Mans International SMAF Sprint 2026
For founders, the lesson is clear: In AI commercialization, technology maturity does not always coincide with business maturity, capital-market confidence, governance credibility, or narrative maturity.
This is exactly the kind of mismatch the Scenario Maturity Assessment Framework, or SMAF, is designed to examine.
1. Business and Narrative Maturity: “AI-Discovered Drug” Is No Longer Enough
Insilico’s real breakthrough was not simply using AI to discover drugs. It was translating a broad technology promise into a concrete business scenario.
“Aging” itself is not an FDA indication. To build a credible path to market, companies must convert broad healthspan ambition into specific diseases, measurable endpoints, and regulatory logic that investors, pharma partners, and clinicians can evaluate. Insilico did this by targeting IPF, or idiopathic pulmonary fibrosis.
Through an SMAF lens, this is the strategic move. The company did not stay at the level of “AI can discover drugs.” It selected a disease scenario where the technology could be tested against real-world evidence, regulatory, partnership, and business requirements. This is why Rentosertib matters.
The asset moves the conversation from AI discovery speed to a harder question:
Can an AI-enabled biotech company turn discovery into validated assets, strategic partnerships, and repeatable business value?
Business and Narrative Maturity: “AI-Discovered Drug” Is No Longer Enough
In the early AI wave, “AI-discovered drug” was enough to capture attention. By 2026, it will no longer be enough to sustain the premium.
Markets now want specifics: the target, the indication, the endpoint, the regulatory path, the partner logic, and the platform’s repeatability.
For founders, the lesson is clear: AI novelty may open the door. But only a mature business scenario keeps the door open.
A strong narrative does not exaggerate certainty. It shows how technological possibility becomes clinical evidence, commercial value, and investor confidence.
2. Cross-Border Maturity: Speed ≠ Trust
Insilico is especially important because it sits across different geographies, capital systems, and operating logics.
Its links to Hong Kong and China’s biotech infrastructure give it access to real advantages: engineering talent, biotech clusters, automation capacity, scientific speed, cost-efficient R&D execution, and increasingly sophisticated capital-market infrastructure.
But global commercialization requires another layer.
It requires regulatory confidence, clinical transparency, pharma trust, investor communication, data governance, and geopolitical risk management.
This is where globally operating AI biotech companies with strong Hong Kong, China, or Asia-linked R&D networks face a hidden challenge.
Cross-Border Maturity: Speed ≠ Trust
Speed is not enough.
To win globally, they must translate technology, evidence, governance, and narrative into a form that global stakeholders can trust.
Through an SMAF lens, this is not just an expansion strategy. It is a maturity test.
The ultimate question for cross-border founders is: “Can this company become globally legible, credible, and trusted?”
3. The SMAF Takeaway: A Conditional Premium
Did Insilico Medicine pass the SMAF test? Partially.
Insilico has passed some important parts of the SMAF test:
Its AI drug discovery capability appears strong.
Its story has moved from a broad AI-discovery promise to a more concrete disease pathway through Rentosertib and IPF.
The Eli Lilly collaboration strengthens external validation and commercial credibility.
But it has not yet fully passed the broader scenario maturity test.
The remaining question is not whether the technology is impressive.
It is whether the surrounding scenario is mature enough to support repeatable clinical progress, durable commercial value, capital-market confidence, and globally credible governance.
The SMAF Takeaway: A Conditional Premium
That is why the AI-drug premium is not dead. It is being repriced.
Markets will no longer reward AI capability alone. The premium must now be earned through clinical progress, pharma validation, financial discipline, and globally credible governance.
For cross-border biotechs, the real bridge is not just market access. It is the ability to translate speed into trust, science into evidence, and platform ambition into globally legible value.
This is the core question behind the Mans International SMAF Sprint 2026:
If the technology works, is the surrounding scenario mature enough to turn it into adoption, revenue, and durable strategic value?
This is the exact diagnostic we run at the Mans International SMAF Sprint 2026.
At Mans International, we use the Scenario Maturity Assessment Framework (SMAF) to help founders, investors, and strategic leaders diagnose one critical question: If the technology works, is the surrounding scenario mature enough to convert it into adoption, revenue, and durable strategic value?
Most AI health startups ask the wrong question: “What can our technology do?”
Formation Bio asked something far more valuable: “Where is value already trapped — and who has the budget to unlock it?”
That single shift explains why Formation Bio has become one of the most closely watched AI-native drug development companies. The company has reportedly raised about $615 million, reached a valuation of around $1.8 billion, and attracted investors including Sam Altman, Sequoia Capital, and Andreessen Horowitz.
But the real lesson is not that Formation Bio “uses AI.” The real lesson is that Formation Bio chose a mature commercial scenario before scaling the technology. That is what most AI health startups miss.
The Real Bottleneck Was Never Drug Discovery
For years, the dominant AI drug development story has been about discovery:
Find new targets
Generate new molecules
Predict biological behaviour faster than humans
But Formation Bio’s founder and CEO, Ben Liu, saw a different bottleneck.
“Pharma does not lack promising molecules. It lacks a faster, cheaper, more reliable way to move drugs through clinical development.”
Clinical trials are slow, expensive, operationally complex, and filled with execution risk. TIME recently reported that Formation Bio is focused on accelerating administrative and analytical tasks related to trials. Formation Bio:
Buys or in-licenses “stalled” assets — drugs already discovered but shelved by big pharma due to budget cuts, strategic shifts, or portfolio pruning
Uses proprietary AI to “stress-test” and accelerate trials — optimizing patient recruitment, site selection, and protocol design
De-risks and out-licenses — creating value through speed, not novelty
That distinction matters. Formation Bio is not trying to replace pharma’s entire R&D system. It is attacking a painful, expensive bottleneck in a system already facing budget constraints, urgency, and strategic pressure.
That is Scenario Maturity Thinking.
What Is Scenario Maturity?
Scenario Maturity is the difference between a technology that looks impressive and a business that can actually convert.
A mature scenario has three pillars:
The Scenario Maturity Compass
1. Business Maturity
Who actually buys?
Who owns the budget?
Why would they act now?
2. Workflow Maturity
Can the solution fit into real-world operations?
Or does it require customers to change behaviour, rebuild infrastructure, and take on new risk?
3. Data Maturity
Does usage create better data?
Does better data improve the system?
Does that improvement compound into a defensible advantage?
When these three pillars align, revenue has a pathway. When one breaks, even excellent technology can stall.
This is why I often tell founders: technology does not generate revenue on its own. Scenario maturity creates the conditions for revenue.
Clear Buyer Convergence: Who Actually Pays?
Many AI health startups fail because they build for users rather than buyers.
They build for clinicians, patients, researchers, or health platforms — but cannot answer the most important commercial question: Who signs the purchase order?
Formation Bio identified their buyer early: Pharma business development & clinical operations teams at companies like Sanofi and Eli Lilly.
Have multi-billion dollar R&D budgets
Face intense pressure to improve time-to-market
Already understand the value of de-risked late-stage assets
This buyer convergence creates:
Shorter sales cycles (no market education needed)
Higher contract values (ROI is quantifiable: months saved = millions earned)
Strategic partnership opportunities (not just vendor relationships)
Workflow Maturity: AI Embedded Into the Real Job
One of the biggest mistakes AI startups make is selling AI as a product.
Formation Bio avoids this trap. In partnership with OpenAI and Sanofi, Formation Bio launched Muse, an AI tool designed to analyze scientific literature and generate tailored patient recruitment materials, cutting recruitment timelines from months to minutes.
Muse is embedded into Formation Bio’s trial acceleration workflow. Customers don’t buy “AI correlation.” They buy:
Lower trial costs → higher margin on out-licensed assets
Reduced execution risk → more predictable ROI
This is the key lesson for founders: AI becomes valuable when it disappears into the workflow and improves the business outcome.
If your customer has to stop, learn, reconfigure, and take on extra operational risk to use your product, your scenario maturity is low.
Data Maturity: The Closed Loop Most Startups Never Build
Most AI health startups face a “cold start” problem:
Data is fragmented across EHRs, wearables, and trials
Feedback loops are weak or non-existent
Model improvements don’t compound into business value
Formation Bio engineered a closed data loop:
Clinical trial execution → Real-world trial data → AI model iteration → Faster, cheaper next trial → Higher asset valuation
This creates:
Compounding advantage: Each trial makes the platform smarter
Defensible moat: Proprietary trial execution data can’t be scraped or replicated
Investor confidence: Clear path to margin expansion as the platform scales
This isn’t just a biotech story. It’s a scenario selection story — and it applies to every complex market.
The Kintsugi Contrast
This is why the contrast between Kintsugi and Formation Bio is so important.
Kintsugi had impressive technology: AI-based voice biomarkers for detecting depression. It had a compelling mission, clinical signal, and strong investor interest.
But the commercial scenario was much harder.
Who pays?
Hospitals?
Employers?
Health plans?
Digital health platforms?
Clinics?
Each buyer had different incentives, budgets, workflows, and risk concerns.
That created a scenario maturity gap.
Formation Bio, by contrast, chose a clearer buyer, a known pain point, a measurable ROI, and a workflow where AI could improve execution without requiring the whole market to change first.
That is the difference between promising technology and investable momentum.
Why This Matters for Every Tech Founder
Formation Bio’s lesson is universal: Success isn’t about better tech — it’s about smarter scenario selection.
Before you scale, ask:
Budget vs. Buzz: Is there an existing procurement line for your solution — or just interest?
Fit vs. Friction: Does your product plug into existing workflows, or require behaviour change?
Leverage vs. Labour: Does every customer make your system stronger — or add custom work?
Causation vs. Correlation: Can your buyer measure ROI in cost savings, revenue gains, or risk reduction?
If your technology is strong but revenue is slow, the problem may not be the product.
It may be your scenario maturity.
At Mans International, this is exactly what we help founders diagnose: where your product is getting stuck, why the market is not converting, and what must change before investors, customers, or strategic partners are ready to move.
Our expertise lies in Scenario Maturity Thinking — helping founders assess whether their technology is entering a market where the buyer, budget, urgency, data, and value-capture logic are mature enough to support real commercialization.
Because in today’s market, the winners are not always the companies with the most impressive technology.
They are the companies that know exactly where value is trapped, who has the incentive to unlock it, and how to convert that insight into revenue, partnership, and scale.
