I’ve worked at two seed-stage startups.

At that stage, you have a dream, venture cash, and a status of “default dead.”

Juggling chaos, overwhelmed teams, and silos can too often result in that exact outcome.

Here’s what I observed (if you’ve been at a startup, apologies for the PTSD this list might trigger):

• Engineering spends 60%+ of its time on maintenance instead of building features that drive growth
• Sales promises what doesn’t exist while Product builds what nobody wants
• Customer insights are scattered across 15+ tools, so decisions get made by whoever shouts the loudest

If I were betting on the companies most likely holding their head in their hands as they look at this list, I’d say they are:

Mid-market to growth-stage startups and scale-ups (50–500 employees), particularly in SaaS or technology sectors.

I’m a big fan of outbound sales because 1) it expands your total addressable market, and 2) it puts you in the shoes of someone who can educate customers about the potential opportunity. That said, there are signals you can use to identify companies that are the most suitable:

• Fresh funding (Series A–B) + aggressive hiring in Eng/Product
• Glassdoor reviews mentioning “moving fast but breaking things”
• Tech stack sprawl visible in job postings (10+ disconnected tools)
• Founders posting about “scaling challenges” on LinkedIn
• Customer success teams growing faster than product teams (reactive scaling signal)

The value to startups is competitive velocity.

There’s always more work than time or existing capacity at a startup.

Let AI do what it does best—augment.