Larry Cheng’s Post

The barometer for whether technology spend is accretive is whether it leads to: (1) Happier customers  (2) Better margins There’s a lot of tech spend that does neither which is a waste. You don’t lose anything by cutting it. But if it does both, it can be transformative.

A good fundraising story is both top-down and bottom-up at the same time. Top-down paints the strategic story of market opportunities, pain points, value delivered, competitive moats, capacity to scale, aspirations for greatness. It conveys opportunity. Bottom-up layers in real actualized company data around each key assumption required for the opportunity to be realized. Everything is grounded in data, and it conveys believability. The top-down elements inspire the optimist. The bottom-up elements quell the pessimist. What must be avoided is being in the muddled middle where the optimist is not inspired and the pessimist is not satisfied. It's far more productive for fundraising to live on both ends of the spectrum and do both extremes well than to sit in the middle which usually leaves everyone wanting more.

Social media is extending into out-of-home ad units and out-of-home ads are extending into social media.

1 simple exercise that will help you build a better company. Grade your company’s: → Income Statement → Balance Sheet → Cash Flow Statement It doesn’t matter if one is an A, if another is a D. The worst one at best impairs the company, at worst it takes down the company. Don’t celebrate the strongest one, strengthen the weakest one.

Another great reminder that there's a significant difference between doing something every day vs. once in a while.

New impact data feature from Grove Collaborative is fantastic - had no idea until I opened the app yesterday. So great to just be buying our everyday household essentials and helping the planet at the same time.

It is evident that for core enterprise and consumer applications of scale, there will be "AI-native" start-ups that VCs will fund to re-invent those applications and their categories. The "AI-native" companies will position current "legacy" apps as old and flat. The legacy applications will counter with AI integrations to adapt their applications for a new world while the AI-native start-ups will re-think and re-design these applications from the ground up. This is what happens in every foundational technology transition (e.g. web to mobile, offline to online, on prem to cloud, etc.). The big mistake made from legacy applications is to underestimate the risk of the new native entrants. The big mistake of the new native entrants is believing that just because they exist, the market is ready to adopt it. Therefore, for "AI-native" start-ups, I'd recommend patience and capital efficiency while reinventing your category. For "legacy" companies, I'd recommend having some portioned-off team whose job is to reinvent rather than just adapt.

If you have a strategic question for your business with an unclear answer and an unclear path to finding an answer, a good path to take is to talk to your customers. It never hurts to talk to customers, and they're the most likely source to replace ambiguity with clarity.

Strong cash position + no debt + profitable business = controlling your destiny. Add growth and you have real value creation in normalized market conditions. This is true regardless of company size, industry, public or private. Simple financial goals can help focus the mind.