跟读练习: The ‘Old Rules’ of SaaS Still Win - 通过视频学习英语口语
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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.
本课概述
在这个视频学习环节中，您将会探索SaaS（软件即服务）行业中的一些“旧规则”，并理解这些规则在现今依然重要。通过观看视频，您将接触到与客户沟通、解决实际问题及市场营销等主题，这些都是成功企业所必备的基本要素。通过英语口语练习，您将能够提高自己在这些领域的表达能力，特别是在突出自己观点、呈现思路以及应对客户反馈时，提升您的英语表达流利度和自信心。
关键词汇与短语
- SaaS - 软件即服务
- AI - 人工智能
- 客户研究 - 了解客户需求和反馈的过程
- 解决问题 - 提供用户真正需要的解决方案
- 市场营销 - 将产品传播给潜在客户的过程
- 产品适合度 - 产品是否满足市场需求的程度
- 反馈收集 - 向用户获取意见和建议
- 分销渠道 - 产品传播的方式和路径
练习提示
为了更好地提升您的英语口语能力，特别是在快速理解和表达的方面，我们建议您在观看此视频时，进行影子跟读（shadow speak）练习。首先，调整视频的播放速度，根据自己的英语水平开始练习。当您听到演讲者的讲述时，试图模仿他们的语音语调和语速。这种方法能够帮助您在英语口语练习中提升自信，同时改善您的英语发音。
此外，请关注演讲者在与客户沟通、分析问题以及市场营销方面的表达方式。在每次跟读之前，先尝试理解他们的关键观点，并将其用您自己的语言重新表达。这不仅增强了您的理解能力，同时也在不断的实践中帮助您掌握更复杂的句式和词汇。
最后，务必创建一个记录您练习内容的日志，以便您能够追踪自己的进步，并在未来的英语练习中找寻更为针对性的改进方向。通过这种方法，您可以稳步提升自己的英语口语能力，有效利用每一次练习的机会。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。