As a founder, hiring someone with an impressive brand on their CV is tempting.
However, hiring an exec from Big Tech is a known anti-pattern in startup hiring.
Despite their impeccable interview style and flawless references, Big Tech execs often fail when thrown into the chaos of an early-stage role.
Here are three non-obvious reasons why this happens so often.
1. Price’s Law
Derek J. de Solla Price was a science historian obsessed with measuring productivity.
In his 1963 book, Little Science, Big Science, he observed that over half of the published research in a scientific field came from a tiny proportion of the scientists.
This became known as Price’s Law, and the pattern generalises beyond science:
Half the output comes from the square root of the participants.
You see this in sports. The top 10 tennis players take over half of the titles. And even among the top 10, three of them win most often—Alcaraz, Sinner, Zverev.
You see this in music. Most of the listens on Spotify come from a small number of musicians—Taylor Swift, Bad Bunny, and Drake.
And you see this within businesses too:
- In a 10-person company, 3 people generate over half the results.
- In a 100-person company, it’s around 10 people.
- In a 10,000-person company, just 100 people drive over 50% of the output.
I shared this formula at one of my recent CEO intensives, and watched my founders get out their calculators to work out the square root of their headcount. One by one, they all nodded in agreement.
So when you hire talent from a big company with over 10,000 people, the chance you’re hiring one of their top performers is dishearteningly low. The distribution of performance is wildly uneven.
How to mitigate: Reference the candidate with someone you already know is a top performer. Without a strong network of your own, you’ll have to rely on their references which is less reliable.
2. Unearned Scale Advantages
If a big company isn’t full of competent people, how did they scale?
Often, the difficulty of scaling talent is offset by the advantages of scale.
Not every business gets better with scale. Indeed, companies that rely heavily on human competence to deliver value (agencies, consulting, services) often get worse with scale (at least before AI came along).
But Big Tech is different. Successful tech products get better with scale, and there are a few drivers of this:
- Network Effects: New users of the product make it more valuable for existing users (e.g. social networks, marketplaces, and communication tools).
- Economies of Scale: Scale leads to lower costs that can be passed to the customer (e.g. Netflix can spread the cost of exclusive TV shows across millions of viewers).
- Brand Power: Buyers place a premium on safety, trust, and status when making a purchase (e.g. “No one ever got fired for buying IBM”).
This makes it extremely hard to separate the contributions of the individual from the advantages of working for an at-scale company.
How to mitigate: Check when they joined and at what scale. If they joined after the size you’re at now, discount their contributions accordingly.
3. Already Established Systems
Even when you find a high performer, you can’t assume they’ll perform as well at your company.
We tend to think of performance as an individual quality. But it’s also a function of the systems someone operates within. A top-performing Sales Development Rep (SDR) at one company can fail at another with weaker systems.
It’s helpful to group execs into two buckets: builders and operators.
Builders thrive when they get to build systems from scratch. Operators thrive when they get to run systems that already exist.
Big Tech companies have well-developed systems across the board:
- Org Systems: clear roles and responsibilities.
- IP Systems: playbooks, checklists, and training.
- IT Systems: automations and workflows.
- Cultural Systems: rituals and shared language.
This means most Big Tech execs are operators who got results by running systems someone else built.
But in an early-stage company, the systems don’t exist yet and you need someone to build them. And that’s a different kind of person.
How to mitigate: First figure out whether you need a builder-type to create a system, or an operator-type who can operate the system you already have. Then assess their profile using this guide.
Brand Names Can Hide Weak Performers
There are real advantages to hiring from Big Tech. They’ve seen what good looks like at scale, they bring pattern recognition from inside mature systems, and they come with networks and credibility you can borrow.
But there are also drawbacks worth knowing, so you can ask better questions at interview and debunk some of your false assumptions.
Ultimately, working at a brand doesn’t make you a top performer.
And there’s a bigger lesson in this for you.
As you scale, you can’t rely on competence alone. Make sure you’re building products that get better with scale and systems that turn average performers into great ones.
Because the only way to build a company of A-players is to find ways to make everyone’s job easier.
Related Reading:
Originally published on May 13th, 2026
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