Hiring? Here are 10 pitfalls to avoid

10 hiring mistakes early stage founders make — and how to avoid them

Aurora Petracca

There are a lot of pitfalls early-stage founders face when it’s time to scale their teams. Read on for how to avoid the 10 most common mistakes that can damage a startup’s chance for success — and how even bare-minimum planning can save time (and pain) later on.

1. Underestimating how much time and work recruiting will take

Founders often find themselves surprised and frustrated with how challenging it is to attract quality candidates.

2. Starting every candidate interview with a generic speech

Unless you understand a specific candidate’s motivations — what they’re interested in and why they’re speaking to you in the first place — how can you expect to effectively pitch them?

3. Overemphasizing FAANG experience

Past-company pedigree isn’t everything. Many companies — not just big tech companies like those in FAANG (Facebook, Amazon, Apple, Netflix or NVIDIA, and Google) — have strong brands and engineering programs to attract talent. And not everyone who thrives in the structure of a FAANG company will necessarily do well at a scrappy crypto startup.

See more hiring pitfalls

The end of the foundation era in crypto

Miles Jennings

With new U.S. regulatory frameworks emerging in Congress, the crypto industry has a rare opportunity to leave foundations, and all of the friction they cause, behind.

Foundations are nonprofit organizations that support the development of a blockchain network. At one time, they were a clever legal pathway to progress; but today, few things slow founders down more through misaligned incentives, operational inefficiencies, and other shortcomings.

An industry seeking to scale and challenge Big Tech, Big Banks, and Big Government cannot hinge on altruism, charitable funding, or vague mandates. If the crypto industry is to fulfill its promise, it must mature beyond structural crutches that no longer serve it.

So what can crypto projects do instead? And how can they make the shift from foundations to a model that creates more and better efficiencies — from deploying capital to attracting talent — instead of one that gets in the way?

Read more on why we needed foundations, and a better path forward

AI vs. ID: Proof of human in a world of agents, bots, and deepfakes

In a world where AI — agents, bots, deepfakes, and so on — act as and on behalf of people, we need to