51–60 of 183 posts
I've been at a few VC / startup events recently and I was stunned to see the number execs frothing at the mouth about finding a 1-person-ai-driven-billion-dollar-startup. This "playbook" is probably not going to help.
Loss of objectivity
The challenge: Ask an AI tool for evidence supporting what you already believe, and it will find it. Confirmation bias now comes with a research engine.
Earlier quoted context omitted.
> AI has not changed that. But it has. AI can help you do market research, develop buyer personas, evaluate potential customers, create, analyze and enrich prospect lists, evaluate marketing channels, create ad copy, write sales scripts, think through objections and how to respond, etc. Will it turn you into Jordan Belfort? No. Will it be 100% successful or effective? No. But can it help enough to make a difference?…
If anything, AI has made it more difficult and challenging because every customer and investor is drowning in AI-generated collaterals, websites, etc. The situation is dire in the academic world, where both the applicants and the reviewers now rely so heavily on AI that both publishing and financing has turned into a lottery. I am positive this will settle down at some point, but the difference will always remain abo…
In many markets, yes. If you're a software buyer, for example, your inbox, LinkedIn, etc. is filled with AI-generated sales outreach. And you know it's AI.
But keep in mind that there are tons of markets (think local services) where buyers aren't familiar with AI. They don't know that what they're reading was produced by AI, and they wouldn't care.
In these markets, if you use AI, you have a realistic shot at being "better" than your competition, and if you use it even a little bit more effectively, it can make a real difference.
Detail-oriented work with lots of output that can cover up the noisy bits of thoughtless garbage? Sure, great.
Analysis-oriented work where decisions have consequences over large amounts of resources? Only an idiot would use these tools for that.
Maybe as a conversational note-taker, but anything more and you don't know what you're doing.
>As an AI-native startup founder, your responsibility is to know what's in your codebase, understand any potential exposure vectors, and not ship obvious vulnerabilities to real users who are trusting you with their data. This is fairly funny coming from the company whose employees report merging in hundreds of PRs per engineer per day, and accidentally leaked their own source code through a security misconfiguration…
Good guide but I think the product market fit portion of a startup is so key that you need no other skills except that to make a good startup. AI won't help you with that portion, only in depth knowledge of a industry or natural product intuition will. Who knows, maybe an AI ideated and AI created product will be the best app of 2026.
>As an AI-native startup founder, your responsibility is to know what's in your codebase, understand any potential exposure vectors, and not ship obvious vulnerabilities to real users who are trusting you with their data. This is fairly funny coming from the company whose employees report merging in hundreds of PRs per engineer per day, and accidentally leaked their own source code through a security misconfiguration…
It seems like CYA; with all the marketing about how LLMs will solve all problems it was really surprising to see that, but legal probably told them to go easy on it.
I think it's easy for those already in the tech industry to pooh-pooh this, as the previous comments on this post have. Right now, people with ideas prompt their LLM by saying "I know how to make x, how do I turn that into a business?" Anthropic knows that, and releasing a playbook like this is a way to make people who haven't asked that question think to ask it. For a non-technical person with a small business they…
This does not sound like an issue small craft businesses have, but something programmer think is a thing.