Understand how the tech industry is funded, grows, and behaves.
Goal: Understand how the tech industry is funded, grows, and behaves.
Teo is on a call with Bao, the senior PM who agreed to a half-hour "how does this all actually work" chat. She asks something that's been nagging her: Brightwell gives away a chunk of its app for free and only 40 people work there, so who is paying the salaries? Bao laughs. "Right now? Mostly investors. We don't make a profit yet. We're spending someone else's bet that we will."
That sentence is the doorway to this whole topic. Tech companies grow on money, and there are two very different ways to get it.
The first is venture capital (VC). Investors hand a young company cash, and in return they get equity — a slice of ownership. They're not lending it; there's no monthly repayment. They're buying a piece of a company that loses money today, betting it grows huge later and their slice becomes worth a fortune. Most of those bets fail. The few that win are supposed to pay for all the rest.
The second path is bootstrapping — growing on your own revenue, no outside investors. You keep full ownership and control, you answer to no one, but you usually grow slower because you can only spend what you actually earn.
Brightwell is VC-backed. The accountant Teo met at a meetup, Davor, works somewhere bootstrapped — smaller, calmer, profitable from year one. Neither is "the right answer." They're two machines that run on different fuel, and they feel completely different to work inside.
VC buys ownership and bets on a huge future. Bootstrapping keeps ownership and grows on what it earns today.
When a VC-backed company raises money, it does it in rounds — discrete chunks, each one usually later and bigger than the last. You'll see these in job ads and news headlines, so it's worth knowing the order:
pre-seed → seed → Series A → Series B → Series C (and on through the alphabet).
Each round trades more equity for more cash, ideally at a higher valuation (what the whole company is judged to be worth) because the company has grown since last time. Rough U.S. ballparks, so the words mean something concrete to you:
| Round | Cash raised (ballpark) | Valuation (ballpark) |
|---|---|---|
| Seed | ~$3–4M | ~$15–20M |
| Series A | ~$10–18M | ~$50–78M |
Treat those as orientation, not gospel. They swing hard with the economy — they fell roughly 30–50% from the 2021 frenzy, then crept back up through 2025. The shape is what matters: each round is a bigger bet that buys the company more time to prove it can grow.
Time to prove what, exactly? That's the metric every startup watches like a hawk: runway — how many months of cash are left before the money runs out. Brightwell raised a Series A; Bao says they have "about 20 months of runway." That number is the company's heartbeat. It explains the urgency Teo keeps noticing: a VC-backed startup must show enough growth before the runway ends to justify raising the next round — or it dies. The investment doesn't just enable the hustle. It demands it.
Marisol, Brightwell's founder, was a teacher before she was a CEO. In an all-hands she says the quiet part plainly: "We took the money. That means we promised these investors we'd grow fast. So we move fast." That promise shapes the daily texture of the place, and it's worth knowing what you're signing up for.
Here is the trade, both sides of it:
"Growth at all costs" is a real culture with real costs. The pace that lets you learn in months what takes years elsewhere is the same pace that can burn you out.
None of this is a reason to flee. It's a reason to choose with your eyes open. A bootstrapped company or a big stable employer (back in Topic 2) trades that intensity for steadiness. Knowing the trade is how Teo picks a first job that fits her, instead of being blindsided by it.
Teo almost talked herself out of this whole career change because of one fear, and it's worth naming. She kept reading headlines about tech layoffs. Were they true? Yes — and the pattern underneath them is something you should understand rather than dread.
During 2020–2021, money was cheap and everyone over-hired. Then the cycle turned. Companies cut hard: roughly 165,000 tech jobs lost in 2022, a peak of about 263,000 in 2023, and around 152,000 in 2024 (figures from the widely-cited layoffs.fyi tracker). Funding and headcount move together, and both move with the broader economy.
So stability is not a fixed property of "tech." It depends on stage and timing. A pre-profit Series A startup running on runway is more exposed than a profitable giant; a downturn hits harder than a boom. Renske, Brightwell's recruiter, puts it to Teo straight in their first call: "I won't promise you any job here is forever. What I look for is someone who's calm when the plan changes." Comfort with change isn't a feel-good platitude in this industry. It's the thing that's actually hiring.
A few currents are visibly moving the ground under everyone entering the field, Teo included.
AI is everywhere. Large language models — ChatGPT, Claude, and their cousins — are the biggest wave in tech right now, reshaping products and the texture of daily work. The practical takeaway for a job-seeker: basic AI literacy (knowing what these tools can and can't do, and using them well) is becoming valuable in every role, engineering and non-engineering alike.
Remote and hybrid work is normal now. That cuts both ways for Teo. It widens her opportunities — she can work for a company three time zones away — and it widens her competition, because that company is also considering candidates from everywhere.
Tools and "what's hot" turn over fast. The specific framework or app that's essential this year may fade in two. Chasing each one is a losing game.
Which points at the one durable truth of a tech career. Because the specifics keep changing, the meta-skills that last are continuous learning and adaptability — exactly what Teo is practicing by working through this track. And under all the technology, tech is still people-driven: communication, collaboration, and curiosity move careers as much as any tool. That's quietly good news for a career-changer, because human strengths — the ones a former teacher already has — are the part that doesn't go obsolete.
Teo finds a junior-analyst opening at a startup called Lumio and, instead of just clicking apply, she runs it through this whole topic.
She searches the company name and sees a headline: "Lumio raises $14M Series A." Now that string carries information she can read. Series A tells her the company is past the earliest stage but still young and pre-profit; $14M raised sits right in the ballpark she learned, so the round is normal-sized, not a red flag. VC-backed, not bootstrapped — so she expects a fast, growth-driven, change-heavy culture, and she should expect to be judged on numbers.
She digs one layer down. The raise was 14 months ago. She does the math she now knows to do: that money is runway, and a Series A typically buys a couple of years, so Lumio is likely mid-runway and under pressure to show growth before raising again. That's not a reason to avoid it — it's context. It tells her the interview will reward someone who's energized by pace and calm about change, the exact posture Renske told her companies hire for.
In the interview, the founder asks why she wants a startup over a big, stable firm. Teo doesn't fake bravado. She says she's chosen the trade knowingly: more change and less certainty, in exchange for learning fast and having real impact early — and that as a former teacher, walking into rooms full of unknowns and staying steady is already her job. One feature of one company, decoded through funding, stage, runway, culture, and trend. That decoding is the skill this topic exists to give her, and you.
Pick one tech company you'd consider working for and search "[company name] funding" or "[company name] raises." Write down three things: (1) Is it VC-backed or bootstrapped? (2) What's the latest round (seed, Series A, B…), and roughly how much? (3) Based on that, would you expect a fast-paced, change-heavy culture or a steadier one? You've just done the exact read Teo did — the read that turns a company name into a real expectation about what working there would feel like.
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