跟讀練習: The ‘Old Rules’ of SaaS Still Win - 通過影片學習英語口語
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104 句
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I see a lot of keyboard warriors out there shouting that AI is changing everything about SaaS, that the old rules are dead, that if you're not building AI native, you're already obsolete.
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They're f*ing wrong.
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After building multiple SaaS companies and investing in over 230 more, I can tell you there are fundamentals that haven't changed.
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If you ignore these, no amount of AI is going to save you.
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And one of them, AI is actually making it worse, not better.
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Now I want to be clear, I'm not saying AI doesn't matter.
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It's actually the biggest change to SaaS I've seen in my 20 years of doing this.
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You can build faster, test cheaper, ship more often.
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But those are tools.
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The fundamentals, the stuff that actually determines whether your business survives, those haven't changed.
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The first is you still have to solve a problem people care about.
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AI makes it easy to build solutions, but solutions without painful problems are just toys.
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Problem-solution-fit hasn't gone anywhere, and I'd argue it matters more now than ever.
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If you solve a problem that isn't painful enough for your customers, faster coding doesn't save you.
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In our last batch of companies that we funded through my SaaS accelerator, TinySeed, we reviewed hundreds and hundreds of AI-powered applications.
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And we funded, wait for it, three.
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The difference wasn't the AI, it was whether they'd found a real problem.
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The question hasn't changed.
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Would someone pay for this if it didn't have AI in the H1 or in in the description or anywhere in the code.
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Number two, you still have to talk to customers.
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AI makes it easy to feel like you've done customer research.
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You can scrape Reddit.
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You can summarize the complaints, generate a list of pain points, but that's not research.
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That's homework avoidance.
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Real product sense comes from talking to real people, and there's no shortcut for that.
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AI can analyze feedback at scale.
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It's true, but someone still has to understand the humans.
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You still have to talk to customers, gather feedback, and figure out what to build.
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This is the role of product.
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And AI will not do this for you.
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AI can summarize it, but someone still has to understand the humans, what they're saying, and what they're not saying.
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One of our Tiny Seed founders, Jason Buckingham, was a development manager at Microsoft.
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He wanted to build a SaaS, but he had no idea what to build.
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So he made 70 cold calls, not to validate an idea, but to find one.
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And out of those conversations, he discovered this whole world of senior living placement agents, basically realtors for elderly care, who are running their businesses on spreadsheets and sticky notes.
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With his co-founder, he built Senior Place.
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And because he actually talked to those people, he learned things no AI summary would ever surface.
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Like the fact that his average customer is a woman in her 50s or 60s who is, in her own words, not even acquainted with computers.
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That shaped everything about the product.
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You don't get that from a Reddit scrape.
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You get that from a phone call.
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Number three, you still have to market.
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AI can write your email your ads, your blog posts, it still can't make people care.
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Distribution is still the hard part.
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Marketing and sales are still the hard part and no tool is gonna do this for you.
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AI can help you produce that content.
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It can send outreach.
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I'm receiving dozens of these junky AI generated emails every day.
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It's not going to do distribution for you.
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You still need to think through and find a channel that works.
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You still have to earn attention.
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The founders who win aren't the ones with the best AI tools.
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They're the ones who figured out where their customers hang out and how to reach them.
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If you're thinking about this very topic about how to find a marketing channel that works, check out our recent video about the big five marketing strategies.
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We'll link it up in the description.
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Number four, you still have to understand churn and AI makes it worse.
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AI native companies have the worst retention I've ever seen in SaaS apps.
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I'm seeing 60, 70, 80% annual churn.
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That's not a revolution.
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That's a leaky bucket.
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So this is one where AI isn't just neutral.
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It's actively making things harder.
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It's making them worse for SaaS founders.
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The data is brutal.
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AI-native products have median gross retention around 40% compared to 90 plus percent for traditional B2B SaaS.
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A lot of what's being counted as ARR is really experimental budget, companies trying things out and not committing.
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People aren't leaving because of payment failures, they're leaving because the product didn't stick, it didn't work, it didn't live up to the promise that was made.
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Founders still have to diagnose why customers leave and fix root causes and not mask churn.
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AI doesn't solve churn, and in most cases, it accelerates it.
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These fundamentals aren't complicated, but they can be hard.
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And they're a lot harder if you're trying to figure them out on your own.
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One of the best things I ever did for my entrepreneurial journey was to join a mastermind.
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It's a small group of founders who meet regularly to share wins, talk through challenges, and hold each other accountable.
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And finding the right people is the hard part.
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That's why we started Mastermind Matching at MicroConf.
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We've successfully matched almost 1,800 founders across 64 countries.
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And applications for our next group of masterminds are open now.
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You can go to microconfmasterminds.com to apply.
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All right, so I have one more fundamental, and this one is less to do with technology and more to do with your mindset.
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It's execution over ideas.
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AI has made ideas cheap.
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Execution is still rare.
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This might be the most fundamental lesson in this video.
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These days, everyone can spin up a landing page.
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Anyone can generate code or ship a prototype in a weekend.
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That's not a moat.
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It's a starting line.
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The founders who win aren't the ones who ship fastest.
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They're the ones who stick around long enough to figure it out.
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Persistence and resilience still win.
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Startups will take years.
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I say all the time, think in terms of years, not months.
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And one of the most popular tweets I've sent out in the past few months said, overnight success takes a decade.
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AI might compress some timelines.
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It makes building faster, but it doesn't change the game.
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It just raises the stakes.
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If you're thinking about how to actually build a SaaS in this environment, not just the theory, but the practical reality, I just sat down with Jason Cohen.
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He's built two unicorns, WP Engine and SmartBear.
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We talked about how he would approach building a new SaaS today in the age of AI.
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That conversation is right here.
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Check it out.
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If you found this video helpful, please give it a like and subscribe.
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Thanks for watching.
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I'll see you next time.
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本課概述
在這個影片學習環節中，您將會探索SaaS（軟體即服務）行業中的一些“舊規則”，並理解這些規則在現今依然重要。通過觀看影片，您將接觸到與客戶溝通、解決實際問題及市場行銷等主題，這些都是成功企業所必備的基本要素。通過英語口語練習，您將能夠提高自己在這些領域的表達能力，特別是在突出自己觀點、呈現思路以及應對客戶反饋時，提升您的英語表達流利度和自信心。
關鍵詞彙與短語
- SaaS - 軟體即服務
- AI - 人工智慧
- 客戶研究 - 瞭解客戶需求和反饋的過程
- 解決問題 - 提供使用者真正需要的解決方案
- 市場行銷 - 將產品傳播給潛在客戶的過程
- 產品適合度 - 產品是否滿足市場需求的程度
- 反饋收集 - 向用戶獲取意見和建議
- 分銷渠道 - 產品傳播的方式和路徑
練習提示
為了更好地提升您的英語口語能力，特別是在快速理解和表達的方面，我們建議您在觀看此影片時，進行影子跟讀（shadow speak）練習。首先，調整影片的播放速度，根據自己的英語水平開始練習。當您聽到演講者的講述時，試圖模仿他們的語音語調和語速。這種方法能夠幫助您在英語口語練習中提升自信，同時改善您的英語發音。
此外，請關注演講者在與客戶溝通、分析問題以及市場行銷方面的表達方式。在每次跟讀之前，先嚐試理解他們的關鍵觀點，並將其用您自己的語言重新表達。這不僅增強了您的理解能力，同時也在不斷的實踐中幫助您掌握更復雜的句式和詞彙。
最後，務必建立一個記錄您練習內容的日誌，以便您能夠追蹤自己的進步，並在未來的英語練習中找尋更為針對性的改進方向。通過這種方法，您可以穩步提升自己的英語口語能力，有效利用每一次練習的機會。
影片中的語法
說話人最常用的結構，並附上影片中的原話：
| 結構 | 影片中的用法 |
|---|---|
| 現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事 | haven't changed · I've seen · hasn't gone |
| 定語從句 who / which + 從句 — 補充說明人或事物 | ones who figured · ones who ship · ones who stick |
| 被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的 | being counted · was made |
什麼是跟讀法？
跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。