Watch a founder negotiate with an investor and you'll see something close to ruthless. Every percentage point gets argued. The valuation gets stress-tested. The term sheet gets a lawyer. The pro-rata rights get a fight. By the time the wire hits, every share that just left the founder's pocket has been priced, justified, and earned a receipt in actual cash.

Now watch the same founder grant equity to a co-founder, an early employee, or an advisor.

They give it away like Halloween candy.

50% to a stranger they met at a hackathon. 2% to an early employee with a six-month vesting cliff and no performance gates. 0.25% to an advisor who once sent a useful email and never showed up again. The math, when you actually do it, is brutal — and it's the...

There’s no such thing as a “retired Founder.”

Just one who hasn’t started their next company yet.

I love hearing about Founders that exit, but what I always find kind of entertaining is their story about how they will now finally retire. It’s always something like “I can finally put the stress of running this startup behind me and spend the rest of my days basking in the sun and enjoying life!”

My response is always the same: “That sounds awesome… call me when you want to talk about your next startup!”

They assume I’m being sarcastic. The idea of starting another startup after just finally selling one and prepping for retirement sounds ludicrous!

And yet, inevitably, I get the call. “You know, retirement actually sucks, so I’m thinking abou...

Just when we thought we had finally gotten past all the bullshit of crawling out of startup mode, someone just hit the reset button on us.

“Hop in the Family Truckster, kids, we’re going back to StartupLand!”

Of course, I’m talking about the wholesale disruption that AI just put on nearly every business, and in this case, established businesses that had long since outgrown startup mode, where we thought we were safe and happy.

Startups.com has been around for 15 years (despite our best efforts), and we too have enjoyed being a well-established company that knew exactly what we sold, who our competitors were, and how we got paid.

But probably, just like your startup, all of that changed. Everything we thought was certain a year ago is brand ...

The era of the “Technical Co-Founder” is coming to a close.

It was a good run, friends. There was a time, back in the days of yore, that every aspiring Founder began a perilous quest of finding that one willing technical mind to join them and make their product dreams come true.

They would give anything (usually half the company) to convince them to join their quest, and be grateful to do so.

It was a good time to be a technical person. You were in high demand, everyone was courting you, and you had incredible negotiating power at the most critical time in a startup’s lifecycle — the founding equity division.

But then, well, AI had to come in and ruin it all. What the hell, man?

Why was a Technical Co-Founder a Thing?

For a good 30+ years, ...

There ought to be some kind of test Advisors need to pass before they are allowed to give startup advice.

But there isn’t — literally, anyone can call themselves an Advisor and get away with it. Hell, I’m doing it right now!

Having been in the business of advising startups for decades, I can say this with conviction — most startup advisors are horrible, and they have no idea they are horrible. I’m not talking about bad actors or those trying to do something nefarious. I’m talking about the advisors who actually think they are helping, and instead are doing a lot of damage.

That’s also not to say that Advisors don’t have helpful or useful advice. The problem stems as much from their delivery as from their actual advice. Sometimes, yes, the a...

“I’ve got dinner tonight with my friends… I wonder which version of me should attend?”

• Do they want to hear about the version that’s stressed out and can’t sleep?
• Or do they want the version that still makes it sound like my startup is doing better than it is?
• Maybe I’ll bring the version that pretends this startup isn’t that important to me and that, instead, I’m just focused on living my best life.

Ah, to hell with it, I’ll just pour myself a vodka gimlet and see which one shows up! Sound familiar?

It’s because every Founder constantly goes through this battle as to which version of themselves they need to bring into the world. And that world has lots of audiences, from spouses and family to friends and colleagues to investors and custo...

Lockup Period

A lockup period is the 90 to 180 day window after an IPO during which insiders are contractually barred from selling or transferring their shares. Also called an IPO lockup, the restriction binds founders, employees, pre-IPO investors, and certain other affiliated parties, including from hedging their shares. It is designed to prevent a post-IPO supply shock that would tank the newly-public stock and to give the market time to absorb the float available from the offering itself. It is one of the most important structural features of a traditional IPO and one of the things direct listings deliberately abandon.

The standard structure: the underwriters require all insiders to sign lockup agreements as a condition of the IPO, with...

Seed Round

A seed round is a startup's first substantial round of outside investment. It is raised to turn a working product into early traction and to reach signs of product-market fit, typically following pre-seed capital and preceding a Series A. It's the round where the company transitions from "we're building something" to "we're building something people want," and where the bar for the next round (Series A) gets established.

The 2025 benchmarks (Carta and PitchBook):

Prompt Engineering

Prompt engineering is the practice of crafting effective input prompts to large language models to elicit desired outputs. It encompasses techniques like clear instructions, few-shot examples, structured output specifications, chain-of-thought reasoning, role assignments, context provision, and iterative refinement. The discipline is part craft (intuition for what works) and part science (testable techniques), and is the dominant way to control LLM behavior without fine-tuning. It's the AI-era equivalent of writing good SQL queries: a transferable skill that materially impacts the quality of what you can build.

The core techniques that work:

Clear, specific instructions: vague prompts produce vague outputs.

Bad: "Summariz...

Large Language Model (LLM)

A Large Language Model (LLM) is an AI system trained on massive amounts of text to predict the next token in a sequence. The prediction capability scales into broader abilities (reasoning, code generation, analysis, conversation, translation, summarization) as models grow in size and training data. Modern frontier LLMs range from 70 billion to 1+ trillion parameters and are the technology underlying ChatGPT, Claude, Gemini, Llama, and other generative AI products that have transformed software since 2022. It's the specific type of foundation model that handles text.

What LLMs actually do (the mechanics):

Tokens, not words: LLMs break text into tokens (sub-word units). "Tokenization" of a sentence might produce 10-...