Achieving $3 Million ARR in 5 Months with a Valuation of $85 Million: A Comprehensive Breakdown of Chris Donnelly's AI Startup Strategy

This episode is worth dissecting, and I'll start with a core judgment: What truly deserves research about Searchable is not the speed of "$85 Million valuation in 5 months," but that it has hit upon a structural change in the internet traffic distribution mechanism: users used to choose brands from Google's "link list," but increasingly, purchasing decisions will first go through the AI's "answer layer." Therefore, in the SEO era, businesses competed for: Rank. In the AEO/GEO era, the competition has shifted to: Mention, Citation, Recommendation, Share of Voice, ultimately determining whether AI includes you in the user's candidate set. This is not a minor change in marketing tools. If the Agent eventually gains purchasing power, it could evolve into: Who can influence how machines understand, filter, and recommend the business world. 1. First, calibrate the core numbers: Searchable's $85 Million valuation is real, but do not write it as "$85 Million value created in 5 months." In May 2026, Searchable announced a $14 Million financing round, valuing the company at $85 Million; at that time, the company disclosed it had been live for about four months, with ARR exceeding about $2 Million. By June, Chris Donnelly publicly announced that ARR had surpassed $3 Million. So, "5 months, $3M ARR, $85M valuation" is generally valid, but the two numbers did not occur on the same day. 2. "Achieving $1M ARR in 60 days" and "achieving $1M ARR in 3 weeks after launch" are actually two different timing metrics. Chris recently stated that Searchable went live in January and reached $1M ARR in 3 weeks; another piece mentioned "it took about 60 days from idea to $1M ARR." Therefore, it is best not to rigidly state a number in formal courses; it can be phrased as: "It took about two months from product construction to $1M ARR, with approximately three weeks after public launch to reach $1M ARR." 3. The claim of achieving $3M ARR with 18 people is also the latest disclosure from the founder. Chris clearly stated that when the company surpassed $3M ARR, the team was about 18 people. This means a rough ARR/Employee of nearly $167,000, and the company is still in the very early expansion phase. 4. However, the claim of "successfully creating four eight-figure businesses" should be understood cautiously. Searchable's official introduction states that Chris has taken Verb Brands to an eight-figure exit, Lottie to a nine-figure valuation, and Creator Accelerator to about $10M/year in revenue, in addition to today's Searchable. However, this mixes exit value, private valuation, and revenue run rate, which are three completely different business metrics; it cannot be written as "four times selling a ten-million-dollar company." 5. The real "Why Now" for this company should not be written as "humans are shifting from Google to ChatGPT." This statement is too simplistic and not accurate. By 2026, Google's AI Mode had already surpassed 1 billion monthly active users, and AI Overviews exceeded 2.5 billion monthly active users; Google also stated that search query volumes reached an all-time high. What is truly happening is not the disappearance of Google, but that Google itself is also transitioning from link search to answer-based search. 6. Therefore, the real trend is not "Google → ChatGPT," but "Link Retrieval → Answer Generation." Users previously input: "best CRM for small business," then clicked on ten blue links; now they might directly ask ChatGPT, Gemini, AI Mode, or Perplexity: "I have a 20-person sales team, should I use HubSpot or Pipedrive?" The machine first reads, compares, and compresses for the user, then provides only a few answers. Brand competition thus occurs at an earlier stage. 7. This will change the top of the marketing funnel. In the SEO era, businesses competed for "user clicks on me"; in the AEO era, the first step becomes: "Does AI think I am worth mentioning?" If your brand is not even in the AI candidate set, users may not even visit your website. Thus, businesses need new metrics: Presence Rate, Citation Rate, Share of Voice, Sentiment, Prompt Coverage. Searchable is currently building its product around these metrics. 8. However, AEO/GEO is not a concept invented by Searchable. In 2023, research teams from Princeton and others published "GEO: Generative Engine Optimization," formally studying how to enhance content visibility in generative search answers, finding that certain strategies could significantly improve visibility. Today, the industry uses terms like AEO, GEO, AI SEO, etc., but standards are not yet fully unified. 9. Therefore, I prefer to define AEO as "a new distribution layer above SEO," rather than a replacement for SEO. Searchable's product still connects to Google Analytics and Search Console, and Chris has publicly emphasized that doing traditional SEO well usually helps with AI citation. The real structure should be: Technical SEO + Entity Authority + Authoritative Content + Structured Data + Third-party Mentions + AI-specific Monitoring. 10. This is very important because the narrative that "AEO will kill SEO" is itself a marketing narrative. AI referral traffic is indeed growing rapidly, but different studies show that its absolute share of total website traffic is still far below traditional search. Some research estimates that by 2026, AI search referrals will only account for about 0.32% of all website traffic, although it has grown about 16 times in two years. In other words: this is a new channel with high growth, but it is not yet the absolute main channel. 11. Meanwhile, the "quality" of AI referrals may be more valuable than quantity. Adobe's 2026 data shows that users entering retail websites via AI recommendations have significantly higher browsing depth and revenue per visit than ordinary channels; Reuters reported Adobe data indicating that AI-referred shoppers generate about 53% more revenue per visit. This aligns with intuition: AI has already filtered for consumers before clicks occur. 12. Therefore, what truly matters in the future is not Traffic Volume, but Intent Quality. Google users may search for "CRM" just to do research; ChatGPT users asking: "Our company has 40 people, budget $20K, recommend the three most suitable CRMs," are already close to making a purchasing decision. This means the economic value of an AI citation may far exceed that of an ordinary informational click. 13. This is also why Searchable may become a good business: it is not merely measuring traffic, but attempting to measure "brand share in the AI decision layer." The current product can track ChatGPT, Google AI Overviews, Perplexity, and in higher plans, cover Claude, Gemini, Grok, DeepSeek, Copilot, etc., while analyzing citation, sentiment, and competitor share of voice. 14. However, the biggest technical issue with AEO is that it is not as stable as Google Rank. Searching "best CRM" on Google may rank third today and fourth tomorrow; asking the same prompt to an LLM twice may yield different answers. Model versions, retrieval sources, system prompts, location, and memory can all change the answers. Therefore, measuring AEO is essentially a probability distribution problem, not a static ranking problem. 15. Searchable itself acknowledges this. Its official documentation advises clients not to overinterpret single-day results but to observe weekly trends and continuously compare the same set of prompts and competitors. In other words, the correct approach to AEO is more like brand polling/market share sampling rather than traditional keyword ranking. 16. The recent drastic changes in Reddit citation are a good risk case. In the summer of 2026, some monitoring data indicated a significant short-term drop in ChatGPT's citation share for Reddit, and the specific reasons were not transparent. This shows that if a business finds an "AEO Hack," thinking they can maintain a long-term position is very dangerous. Generative search platforms are still in a period of rapid change. 17. Therefore, Searchable must truly upgrade from a "Dashboard company" to an "Execution company." If it merely tells the CMO: "Your visibility is 23%, and your competitor is 31%," this data will soon be incorporated by traditional marketing platforms like Semrush, Ahrefs, HubSpot, Adobe, etc. Searchable itself has also clearly stated in its financing announcement that the future core is shifting from measurement to agentic execution. 18. This is why the real battle in the AEO market is not "who can track," but "who can truly change outcomes." Profound has already completed a $96M Series C in 2026, with a valuation of $1B, raising about $155M in total, and has begun launching Agents; there are also players like Peec AI, Scrunch, Bluefish entering the market. Searchable is not entering a blue ocean without competition, but rather a new track where capital is rapidly accumulating. 19. This also means that Searchable's $85 Million valuation is not absurdly incomprehensible, but already includes a lot of future options. When financing, if viewed at about $2M ARR, the valuation is close to 40×+ ARR; after reaching $3M ARR, it is still about 28× ARR. Investors are clearly not buying today's revenue but are buying: Will AEO become a new category similar to the SEO software market? 20. Therefore, the real question is not: "Is $3M ARR worth $85M?" but: "Is AEO ultimately a feature, or a whole new marketing stack?" If it is just visibility tracking, it can easily enter Semrush, HubSpot; if it ultimately includes Monitoring + Content + Entity Graph + Agent Execution + Attribution + AI Commerce, the TAM will be completely different. 21. Looking at Chris's CODE framework, this framework itself is valuable, but it is not a rigorous investment model. Chris's latest public definition is: C = Consumer Trend; O = Opportunity; D = Demand; E = Economic Sizing. His principle is that if an idea cannot pass through all four layers, do not build. 22. C—Consumer Trend, the real question is not "what's hot now," but "has behavior undergone an irreversible shift?" AI search is a good example. The truly strong entrepreneurial opportunities are not what is being discussed on TikTok this month, but that users have begun to form new default behaviors that the old product structures have not fully adapted to. 23. The most valuable lesson here is the Rising Tide mindset. If a market naturally grows by 50% each year, an ordinary team may achieve decent growth; if the market shrinks by 20% each year, you must be extremely excellent to swim upstream. VCs love to say "the market is more important than the team," and the logic behind this is: a massive structural wave can pay part of the customer acquisition costs for startups. 24. However, "big trends" cannot stand alone. In 2021, the Metaverse was a big trend; in 2022, Web3 was also a big trend narrative; many companies still died. Therefore, the second O in CODE is crucial: Is there a specific economic problem that remains unsolved within this trend? 25. The O that Searchable found is very clear: brands used to know their ranking on Google, but suddenly do not know how ChatGPT, Gemini, and Perplexity describe themselves. This creates a new "observability black hole." Businesses are very uncomfortable with channels they cannot measure, so the first batch of products is naturally Monitoring. 26. D—Demand, is the most important link in the entire CODE. Chris's public definition is not "many people complain in forums," but stronger: validating that real people will pay. I strongly agree with this. Complaints are just a signal; payment is the economic validation. 27. Therefore, the real value of "spending 6 hours a day on Reddit for a month" is not Reddit's magic, but the founder conducting Qualitative Market Research. You are looking for recurring language: how people describe pain, how they solved it in the past, how much they are willing to spend, and what alternatives they currently use. This content will directly enter product copy, sales scripts, and roadmaps in the future. 28. But do not mistake "many people complaining" for market existence. There may be 100,000 people complaining about email usability on Twitter, but no one is willing to pay $100 a month. The real stronger Demand Hierarchy is: complaints → fill waitlist → accept demo → provide data → trial → pay → renew. The further along, the stronger the signal. 29. E—Economic Sizing, cannot stop at just "number of customers × annual fee." This is the most basic Bottom-up TAM, but it truly needs to be broken down further: TAM, SAM, SOM, ACV, Gross Margin, CAC, Churn, Competitive Intensity. A $5B TAM, if divided among 20 giants, may not be easier to work with than a $500M high-growth niche. 30. Especially the TAM of AEO cannot be directly equated to the SEO market size. Because part of the budget will shift from SEO, not all will be newly added. If a business originally spent $500K on SEO annually, it may become $350K SEO + $150K AEO in the future, rather than suddenly adding another $500K AEO. What should be studied is Budget Reallocation. 31. The founding team's "UX + Deep Engineering + GTM" triangle is very enlightening, but it should not be treated as an entrepreneurial iron law. The roles of the three co-founders in Searchable are indeed very clear: Chris is responsible for GTM, Arya leans towards engineering, and Sam leans towards product/AEO methodology. The official company introduction also clearly divides this. 32. Why is this combination particularly strong in 2026? Because AI has made "writing code" itself cheaper, so what remains truly difficult are the three extremes: doing the right things, making them reliable, and selling them. Product Taste, Deep Engineering, and Distribution correspond to these three bottlenecks. 33. However, beginners are most likely to learn incorrectly: thinking they must find three co-founders. Not necessary. What is truly needed is coverage of three types of capabilities. One founder can take on two roles at once; some businesses selling products may not even need a strong UX founder; Deep Tech may reasonably have two engineering founders. The framework is a capability map, not an organizational charter. 34. "Before the product is made, build a waitlist" is a very replicable lesson from this episode, but it should also be understood that Chris has a huge first-mover advantage. Before Searchable, he had already operated multiple businesses and personal content brands, so his daily output of AI Search content already had existing distribution capability. A founder starting from scratch with 0 followers cannot mechanically expect the same waitlist conversion speed. 35. Therefore, Founder-led Content is truly an asset for lowering CAC, not just simply posting on LinkedIn. Chris has been continuously producing content around AI Search since October 2025, establishing category awareness before the official public launch. When the product appears, the audience is not hearing about this issue for the first time. 36. This is called Category Education Before Product Launch. Many companies find it challenging to do two difficult things simultaneously at launch: explain "why this problem exists" + "why use my product." Searchable first used content to address the first issue, so when the product launches, it only needs to complete the second. This will significantly shorten the Sales Cycle. 37. The true value of the waitlist is not the email list but the Demand Reservoir. On the product launch day, it does not face zero traffic but rather a group of people who already know the problem, are interested in you, and are willing to try. This can simultaneously increase initial revenue, product feedback speed, and social proof. 38. However, the "free waitlist 50%-70% conversion rate" mentioned in your materials is not recommended to be written as a universal rule. I have not found independent, standardized sources proving this is a universal waitlist benchmark for Searchable. Chris has indeed publicly stated that one of their core Lead Magnets—the free AI Visibility Report—has converted nearly 50% of users to paid, but this is a specific funnel performance reported by the founder, not an industry-wide benchmark. 39. Moreover, if "free → paid 50%" were to hold universally in the long term, it would be an extremely unusual SaaS conversion rate. Therefore, professional writing must add: "According to the founder's disclosure, their early lead magnet cohort had nearly 50% paid conversion." Do not write it as "all free users of Searchable have a 50% paid conversion." 40. Why is the AI Visibility Report an excellent Lead Magnet? Because it does not just offer a PDF but creates "problem awareness." Users input their domain and immediately see: my brand only appears 12%, while competitors appear 46%. Customers instantly experience Loss Aversion. This is not traditional content marketing but Diagnostic Selling. Searchable currently still publicly offers such free reports without requiring a credit card. 41. The highest-level Lead Magnet is not educating customers but making them see their own losses. "AI Search is important" is abstract; "Your competitor appears 41 times in 73 high-intent prompts, while you only appear 9 times" is immediately specific. This structure can be replicated in selling insurance, cybersecurity, advertising optimization, financial software: Reveal the Gap → Quantify the Pain → Sell the Fix. 42. This is also why Searchable's Free Report is much stronger than "download the AEO 2026 white paper for free." The value of a white paper is information; the value of a diagnostic tool is personalized information. Personalized information is closer to the purchasing decision. 43. Chris's two-week MVP principle is also very good, but it also belongs to heuristics. He publicly summarizes it as: "one ideal customer, one specific problem, one core product, completed within two weeks." This is very applicable to ordinary AI SaaS because Claude/Codex/Cursor have significantly compressed Build Time; however, medical devices, financial infrastructure, and chips cannot mechanically launch in two weeks. 44. What should truly be learned is Scope Discipline, not the number "two weeks." The founder's biggest mistake is not developing slowly but trying to solve 17 problems from the start. Searchable's first layer of value is very clear: telling businesses where they appear in AI answers. First, let one person generate a clear "Wow." 45. "100 paying customers before going all-in" is also Chris's own experiential rule, not an entrepreneurial law. He publicly wrote that 100 real paying customers are a strong signal worth fully investing in. However, for a $500K ACV Enterprise SaaS, having 5 customers is already very strong; a Consumer App may need 100,000 users. So the real metrics remain: repeatability, retention, and willingness to pay. 46. Founder Content → Consultative Outreach → AEO is Searchable's beautiful three-layer Distribution Stack. The first layer creates trust; the second layer actively acquires customers; the third layer attempts to have machines recommend themselves in the future. The combination of the three is equivalent to managing Human Distribution + Sales Distribution + Machine Distribution simultaneously. 47. The "free diagnosis instead of directly scheduling a demo" is very advanced. "Would you like to see our demo?" is a request for the customer's time; "I have already analyzed three AI visibility gaps for you, would you like to see?" creates value first. This reduces the psychological resistance of cold outreach. It aligns perfectly with the previous logic of Clay's Permissionless Value. 48. However, if AEO ultimately evolves into "to trick LLM into recommending itself," it will replay the worst history of SEO. Keyword stuffing, content farms, and spam backlinks ultimately forced Google to continuously combat cheating. In the future, there will certainly be LLM Spam, Citation Manipulation, Synthetic Reviews, and Agent Gaming. The truly long-term safe strategy remains: more authoritative, clearer, more trustworthy, and verifiable information. 49. This is why the long-term moat of AEO should not be "finding a few Prompt Hacks." Prompts and models will change. The truly long-term assets are: Entity Authority, brand trust, third-party authoritative citations, real user reviews, original data, and clearly structured knowledge assets. These are valuable to both humans and machines. 50. Searchable's current biggest competitive risk is also very clear: Monitoring can easily become commoditized. Its current public pricing of $125, $400, and $999/month has already proven this is a standard SaaS product; meanwhile, Profound, Peec, Scrunch, HubSpot, Semrush, Adobe, etc., are all entering. Therefore, Searchable must continue to move towards Execution, Attribution, Workflow, and Agent. 51. The truly valuable step will be from "telling you AI did not recommend you" to "automatically making you more likely to be recommended." For example, automatically analyzing missing entities, citation gaps, technical structures, content coverage, then generating modification plans, creating content, updating schema, monitoring results, and learning automatically. This way, the product transitions from Analytics to Closed-loop Optimization. 52. This is similar to the development of the advertising industry. Initially, Google Analytics only told you what happened; later, Google Ads directly optimized bids and conversions. The truly largest platforms are often not Measurement Layers but Execution Layers. Because the execution layer controls more budgets and is closer to revenue. 53. Therefore, Searchable's so-called "Autonomous AI Growth Agent" is more valuable than a Dashboard. If the Agent can ultimately autonomously complete: discovering visibility gaps → generating content → fixing technical issues → building citations → measuring results → optimizing, it is not just a $125/month tool but is executing part of the Marketing Labor for businesses. 54. This connects Searchable to what we previously discussed: "Services: The New Software." In the past, businesses paid $1 for SEO software and then paid $5-$10 to Agencies; if the AI Agent ultimately delivers ranking/citation outcomes directly, software companies will begin to compete for budgets that originally belonged to Agencies. The TAM will suddenly expand. 55. But caution is also needed: AEO's "Outcome" is harder to attribute than ad placements. Facebook Ads can see spend → click → purchase; AI recommendations often occur in a black box dialogue, and users may directly input brand names, with GA4 not knowing the starting point came from ChatGPT. Therefore, the next technological war will be AI Attribution. 56. Whoever can connect "AI Mention → Website Visit → Pipeline → Revenue" will be more valuable than a simple visibility dashboard. Searchable is already attempting to establish this link by connecting Google Analytics/Search Console, which will be an important direction. 57. This episode also raises a very thought-provoking question for investors: How many real technical barriers does Searchable possess? Prompt monitoring itself is not difficult; content generation is even easier; model APIs are also public infrastructure. The real barriers must come from: Cross-engine historical data, customer workflow, attribution graph, execution results, enterprise integrations, brand and distribution. 58. Therefore, one of its strongest assets now may not be technology, but Chris's Distribution. He has proven capable of continuously creating content, conducting Founder-led marketing, building an audience, and converting that audience into revenue. This GTM capability is very valuable in an era of rapid product homogenization in AI. 59. This is an increasingly evident trend in AI startups in 2026: Build is being commoditized, Distribution is being repriced. Two teams may both use Claude/Cursor to create an AEO Tracker in two weeks, but one founder has a target audience of 500,000, customer network, and industry credibility, while the other does not, leading to completely different business results. 60. Therefore, Chris's true Playbook is not CODE, nor is it "two-week MVP." Rather, it is: trend judgment + pre-distribution + rapid validation + low-scope product + high-frequency user feedback + strong Lead Magnet + multi-channel replication. The combination of these elements constitutes a growth machine. 61. The biggest hidden variable in this method is that the Founder has accumulated over a decade of business experience. Speed does not mean that someone starting a business on day one can be equally fast. A serial entrepreneur may identify customer objections in 10 minutes, while a first-time entrepreneur may take three months. This is called Experience Compression. 62. Therefore, the title "Achieving a $85 Million Company in 5 Months" is actually a very misleading title. Searchable has only existed for a few months, but Chris's marketing experience, Verb's ten years, Lottie, Creator Accelerator, personal brand, and relationship network have existed for many years. The company's age is 5 months, but the capital of capability is not 5 months. 63. This is also a common illusion in the entrepreneurial world: Overnight Success. Rapid growth of a new company does not mean success took only a few months. The real question should be: How much Skill, Network, Capital, Audience, and Mistakes has this Founder accumulated? This is the complete starting point. 64. From an investment perspective, I am most interested in observing Searchable not for the next round valuation, but for five metrics: First, can growth be maintained after $3M ARR; second, 12-month retention; third, the proportion of enterprise customers and ARPA; fourth, can AI visibility prove revenue attribution; fifth, can Agent execution truly improve customer outcomes. The first four determine whether it is a good SaaS, and the fifth determines whether it can become a larger platform. 65. Also, pay special attention to Competition-adjusted growth. Profound has already reached a $1B valuation, serving hundreds of large enterprises; traditional SEO giants are also joining AI visibility. Rapid growth in a track does not mean every company can win. The larger the market, the easier it is to attract the strongest competition. 66. I even believe the real risk is not that the AEO market does not exist, but that it ultimately gets "Feature-ized." If Google Search Console, HubSpot, Semrush, Adobe provide AI citation analytics for free to all businesses, the monitoring value of independent AEO SaaS will quickly be compressed. At that point, only execution, workflow, and proprietary outcome data can retain real value. 67. Conversely, if Agent Commerce is established, the ceiling for AEO will be much higher than SEO. Today, AI merely answers: "Recommend three insurance brokers." In the future, an Agent might directly say: "I compared 12 companies, already selected Harper, and completed the application." At that time, being recommended by AI will not just mean Traffic, but will directly determine Transactions. 68. Thus, the final version of AEO may not be called AEO. It will evolve into Machine Distribution Optimization: how to ensure that a business's product information, pricing, credibility, inventory, reviews, API, policies can all be correctly understood, compared, and invoked by Agents. This market is much larger than "writing articles for ChatGPT to cite." 69. This is also why Searchable, if truly smart, will eventually move from Content to Commerce, Product Data, Agent Protocols. When machines become buyers, brands need not only articles but also structured catalogs, pricing, availability, credible signals, and machine-readable actions. 70. The ten key takeaways ordinary entrepreneurs can extract from this episode can be compressed into one systematic statement: Do not chase "AI hotspots," chase behavioral shifts; do not build first, find pain points that have already paid; do not treat waitlists as PMF; money and renewals are more important; MVP should be small, but problems can be big; founder content is a Distribution Asset; the strongest Lead Magnet is diagnosing users' own losses; in the AI era, building is cheap, but distribution is more expensive; in the early stages of new channels, the speed of learning is paramount; any "new SEO" will ultimately experience cheating, platform countermeasures, and standardization. 71. If I were to compress Searchable's growth flywheel into a formula, I would write: Behavior Shift → Category Education → Waitlist → Narrow MVP → Paying Users → Personalized Diagnostic → Founder-led Content → Inbound/Outbound → AEO Visibility → More Brand Authority → More Customers → More Execution Data → Better Agent. What is truly powerful is not any single technique, but that each link provides lower-cost inputs for the next link. 1. Looking at a higher level, this episode is truly about "distribution power is shifting." In the past, brands optimized for Google; later, they optimized for Facebook/TikTok algorithms; now they are beginning to optimize for LLMs and Agents. Businesses are always chasing the same thing: Whoever controls the next step of the consumer must understand who. 1. In the SEO era, Google was the Gatekeeper. In the Social era, the Feed Algorithm was the Gatekeeper. In the Agent era, the AI Model + Retrieval Layer may become the new Gatekeeper. This is why AEO is not just a marketing trend, but involves significant platform power issues: several AI companies will increasingly have the ability to decide which brands enter human cognition and purchase candidate sets. 2. Therefore, the most dangerous state for businesses in the future is not being 10th on Google, but that the machine does not recognize you at all. Once users get used to asking an Agent instead of searching through a bunch of links, the window for brands to enter the consideration set will shrink. Previously, there were ten positions on the first page; in the future, AI may only recommend three. 3. This will sharply decrease the economic value of anything beyond third place. Traditional search users can still scroll to the second page; generative answers often compress the world directly. This means AI Distribution may become more Winner-Take-Most, which explains why capital is so eager to bet on AEO/GEO today. 4. However, Google's own data currently reminds us: do not prematurely declare traditional search dead. AI Mode and AI Overviews have instead driven Google Search query volumes to an all-time high. The smartest companies are not choosing between "SEO vs AEO" but are establishing a unified Search Everywhere Strategy. 5. Ultimately, I would upgrade Chris Donnelly's CODE framework into a more complete entrepreneurial judgment: Trend × Pain × Willingness to Pay × Distribution × Market Size × Speed of Learning. The first four items find opportunities; The last two determine: Can you really win. Because good markets are visible to everyone. What truly generates enterprise value is: Who learns faster how to occupy it.