How to Start a Tech Company

Starting a tech startup today is both easier and harder than ever.

Easier, because cloud platforms, open-source tools, and generative AI let a tiny team ship what once took a hundred engineers. Harder, because global capital chases a small number of breakout winners, AI giants are raising tens of billions, and customers have sky-high expectations.

This guide walks through the full journey: from “I have an idea” to building an innovative product and scaling a real technology company. Along the way we’ll anchor advice in real data and show you what you’re up against—and how to tilt the odds in your favor.

1. Understand the Odds (So You Can Beat Them)

Before you pick a stack or design a logo, it’s worth getting brutally honest about risk.

Recent analysis based on U.S. Bureau of Labor Statistics data shows:

• 21.5% of new businesses fail in the first year

• 48.4% have failed by year five

• 65.1% have failed by year ten

Put differently, only about one-third of companies are still alive after a decade.

For tech specifically, one dataset suggests 63% of tech businesses fail within the first five years, with many shutting down in year one. European data paints a similar picture: one large study found an overall failure rate around 89% for startups founded in 2013, with only 11% reaching scale or exit.

That’s sobering—but it also tells you where to focus. Most failures stem from a handful of causes: weak market need, running out of cash, team issues, and bad timing. Later we’ll translate those into concrete “how to avoid this” moves.

2. The Current Tech & Funding Landscape

You can’t design a winning strategy without understanding the environment you’re operating in.

2.1 Global startup funding is cyclical (and concentrated)

Using data from Crunchbase, global startup funding over the last few years looks like this:

Table 1 – Global Startup Funding, 2020–2025 (Crunchbase data, USD billions)

In 2025 alone, investors poured $425 billion into ~24,000 companies, up from $328 billion in 2024. But a huge amount of that money is clustering around a tiny slice of companies:

• Around 50% of 2025 global VC funding went to AI-related companies.

• Just five firms—including OpenAI and Anthropic—raised about $84 billion, ~20% of all global VC capital that year.

If you’re not building in AI or another “hot” category, you’re competing for a smaller pool of capital—so you need much clearer traction and economics.

2.2 Progression between rounds is slower and harder

A few trends matter directly to new founders:

• The average time to reach Series A has stretched to around 2–2.5 years from seed, up from roughly 1.5 years a decade ago.

• Only about 11% of startups that raised seed between 2020 and mid-2025 have made it to Series A so far, with even lower rates for recent seed cohorts.

• Nearly 46% of seed deals in early 2025 were “bridge” or extension rounds, as companies struggle to meet the higher bar for Series A.

Translation: you must plan for a longer runway, and your early metrics need to be sharper. “We’ll raise an A in 12 months” is no longer a safe assumption.

2.3 What this means for you

• You’re launching into a crowded, selective market, but not a dead one. Capital is there; it’s just picky and concentrated.

• The bar for product-market fit and business quality is higher than during the 2021 bubble.

• Bootstrapping and revenue-driven growth are more realistic—and often smarter—for many first-time founders.

3. Decide if a Tech Startup Is the Right Path for You

Not everyone who likes technology should start a startup. Ask yourself:

1. Am I drawn to a specific problem, not just “being a founder”?

2. Can I live with uncertainty for 3–10 years? (income volatility, long hours, unclear outcomes)

3. Do I have or can I build founder–market fit?

   • Industry knowledge

   • Deep customer empathy

   • Access to users, data, or distribution others don’t have

Data suggests that experience matters: one large analysis found that a 50-year-old founder is roughly twice as likely to build a successful company as a 30-year-old, and serial founders have higher success rates than first-timers. That doesn’t mean you should wait until 50—but it does mean you should aggressively borrow experience via mentors, advisors, and co-founders.

4. Choose a Problem and Market, Not “An Idea”

4.1 Start from a sharp problem

Most failed startups don’t die because the code was bad. They die because not enough people cared.

Post-failure studies of startups consistently find that weak customer demand, depleted financial runway, and team-related challenges are among the most common causes of collapse.

Across the analyzed cases, weak or nonexistent customer demand emerges as the single most common reason startups fail, affecting over 40% of companies.

A useful problem statement template:

“[Target user] trying to [achieve goal] currently uses [existing workaround], which causes [specific pain: time, money, risk, frustration]. If we could [measurable improvement], they’d switch.”

Good early markets often have:

• High pain, high frequency problems (e.g., recurring ops bottlenecks, compliance headaches)

• A clear economic buyer (you know who signs the invoice)

• A reachable niche—you can get to 50–100 customers via channels you already understand

4.2 B2B vs B2C; horizontal vs vertical

• B2B SaaS or tools: often easier to monetize early and align value with willingness to pay.

• B2C: can get huge, but distribution is brutally hard and usually requires either network effects, paid acquisition skill, or unusual virality.

• Vertical SaaS (software tailored to a specific industry) lets you go deep into one domain where incumbents are slow and UX is bad.

Ask: “If we nail this, what does a $100M+/year revenue version of this company look like?” You don’t have to know every detail, but there should be a plausible path.

5. Validate Before You Build

The easiest way to waste two years is to start building immediately.

5.1 Talk to 30–50 target users before writing serious code

For each interview:

• Ask them to walk you through their current workflow.

• Quantify the pain: “How often does this happen? How much time or money is involved?”

• Ask how they currently solve it and what they’ve tried.

• Test demand with “What would this be worth to you per month?”

Red flags:

• People say “nice idea” but never volunteer concrete numbers or intros.

• They suggest “You should talk to my friend” but won’t commit to trying a prototype.

Green flags:

• They ask “When can I use this?” more than once.

• They offer to pay, introduce you to colleagues, or try a hacky manual version.

5.2 Use experiments, not opinions

Simple validation tools:

• Landing page with a clear value prop and a “Join waitlist” CTA. Run small, targeted ads or post in relevant communities and measure sign-ups.

• Concierge MVP: manually do the service behind the scenes (e.g., fulfillment, analysis) to learn what the real product should automate.

• Design prototypes (Figma, clickable mocks) to test flows before you code.

Aim to get to: “We’ve spoken with 30–50 potential customers; 10–15 strongly want this; 3–5 have committed to being design partners or pilots once we have a v1.”

6. Design a Business Model That Can Scale

A tech startup is not just software; it’s a repeatable economic engine.

6.1 Common tech startup models

• SaaS / subscription: Monthly or annual recurring revenue; often the most straightforward for B2B.

• Usage-based / API pricing: Great for infrastructure or data products.

• Marketplace: Connects two sides (e.g., buyers and sellers). Powerful, but hard to get started due to chicken-and-egg dynamics.

• Freemium / product-led growth (PLG): Free tier to drive adoption, with paid upgrades for advanced features or team use.

For each model, sketch:

• Customer acquisition: Where do customers come from? (Outbound, inbound, partner channels, app stores)

• Unit economics: Roughly, what is your customer acquisition cost (CAC) vs. customer lifetime value (LTV)?

• Sales cycle: Is this self-serve (days), SMB sales (weeks), or enterprise (months)?

You don’t need precise numbers on day one, but you must have a hypothesis you can test.

7. Assemble the Right Founding Team and Structure the Company

7.1 Why multiple co-founders often win

Research summarized in GrowthList’s 2026 report notes that around 80% of billion-dollar companies founded since 2005 have multiple founders. Diverse skill sets, shared workload, and emotional support during the rough patches matter.

You typically want coverage across:

• Product & engineering (can build)

• Go-to-market (can sell, market, or recruit early customers)

• Domain expertise (understands the industry deeply)

Solo founders can succeed, but investors will implicitly ask: “How will you recruit and retain a world-class team around you?”

7.2 Equity splits, vesting, and legal basics

At a minimum:

• Incorporate in a reputable jurisdiction (often a C-corp in the United States for VC-backed startups, or your local equivalent if you’re focusing regionally).

• Founder equity vesting: Standard is 4 years vesting with a 1-year cliff, to protect against a co-founder leaving after a few months.

• IP assignment: Ensure all IP is owned by the company, not individuals.

• Set up a stock option pool for future employees early.

A common pattern:

• CEO / business: ~30–45%

• CTO / technical: ~30–45%

• Additional co-founders: remainder, with some equity reserved for future key hires

Avoid trying to “optimize” tiny percentage differences at the beginning—alignment and commitment matter more.

8. Build Version 0 and Version 1

8.1 Version 0: solve the problem in the ugliest way possible

Your first objective is learning, not elegance.

Examples:

• A tool that is half automated, half manual behind the scenes, but delivers value.

• A browser extension + Google Sheet instead of a full analytics platform.

• A “human-in-the-loop” AI service where you review outputs before sending to customers.

If users won’t use the ugly, manual version, they probably won’t care enough about the polished one.

8.2 Version 1: invest where it matters

When you see genuine pull—users logging in without prodding, paying, or referring others—start tightening:

• Reliability and performance (latency, uptime)

• Onboarding and UX (time to value, guided flows)

• Security and compliance if you handle sensitive data (SOC 2, HIPAA, GDPR, etc.)

Modern stacks let you move quickly:

• Cloud providers (AWS, GCP, Azure)

• Front-end frameworks (React, Next.js)

• Managed databases and auth platforms

• Generative AI APIs for search, summarization, workflow automation

But don’t let “cool tech” distract you from the core: building something people actually depend on.

9. Go-to-Market: From Zero to Your First 100 Customers

9.1 Define your ICP and wedge

Your ideal customer profile (ICP) should be painfully specific at first:

“US-based B2B SaaS companies, 20–100 employees, with a sales team of 5–20 reps, using Salesforce, spending at least $100k/year on outbound.”

Your wedge is the narrow problem you solve extremely well. Instead of “We’re the AI platform for sales,” maybe you’re “the fastest way to generate hyper-personalized outbound emails for mid-market SDR teams.”

9.2 Choose an initial GTM motion

• Product-led growth (self-serve sign-ups, free tiers) works if you can deliver value in minutes and your buyer can adopt bottom-up.

• Founder-led sales is almost always required in B2B at first: you personally talk to prospects, run demos, close deals.

• Community/education-led (content, open-source, newsletters, events) can be powerful but slow to build.

In the early days, focus beats breadth. Pick 1–2 channels and work them obsessively:

• Cold outreach (email, LinkedIn) with targeted messaging

• Content that answers specific queries (“How to calculate [X] for [your niche]”)

• Partnerships with agencies, consultants, or platforms serving your ICP

10. Funding Strategy: Bootstrap, Angels, or VC?

You don’t need venture capital to build a valuable tech company. You do need enough capital to survive long enough to reach product-market fit.

10.1 How founders actually fund their startups

Studies of small business formation data show:

• About 58% of US small businesses start with less than $25,000 in initial capital.

• “Love money”—friends and family—is still one of the most common sources of early funding.

Many tech companies start with:

• Personal savings + part-time consulting

• Small checks from friends/family

• Grants or startup competitions in some regions

• Revenue from early paying customers

Only after demonstrating traction do they approach angels or VCs.

10.2 Angel investors vs venture capital

Guides from Stripe and others outline the differences:

• Angels

  • Individuals investing their own money, usually at pre-seed or seed.

  • Check sizes: tens to hundreds of thousands of dollars.

  • Often more flexible and founder-friendly; may bring niche expertise.

• Venture capital firms (e.g. Andreessen Horowitz)

  • Invest larger sums from pooled funds.

  • Expect rapid growth and large outcomes.

  • Often join around seed and Series A and will want governance rights (board seats, approvals on major decisions).

Both angels and VCs typically buy equity in your company; you’re trading ownership and some control for capital and support.

10.3 What “good” rounds look like today (roughly)

Data from Carta and Crunchbase gives a rough picture for 2024–2025:

• Median Series A round size in the U.S. has been in the $12M+ range since 2021, with many rounds $15–20M.

• A recent analysis put average Series A around $16.6M in early 2025.

• Median Series A valuations for SaaS companies on Carta reached about $60M in Q3 2025.

For those rounds, investors expect:

• Strong evidence of product-market fit

• Repeatable customer acquisition channels

• Meaningful revenue (often $1–3M+ ARR for SaaS, depending on growth rate and sector)

Pre-seed and seed are more flexible, but even there, traction is increasingly important.

10.4 SAFEs and priced rounds (quick overview)

• SAFEs (Simple Agreements for Future Equity) are popular at very early stages. Investors give you money now; they convert into equity during a future priced round, typically at a discount or valuation cap.

• Priced equity rounds (Series Seed, Series A, etc.) set a formal valuation and issue shares directly.

Early on, the specific instrument matters less than the total dilution and the quality of your cap table (who you’re giving ownership to).

11. Scaling After Product-Market Fit

Getting from zero to something that works is one game. Scaling is another.

11.1 What product-market fit feels like

You’re likely at or near PMF if:

• Users come back on their own and complain loudly if you break things.

• You see organic growth (referrals, word of mouth).

• Churn is decreasing and usage per customer is rising.

• You struggle more with “We can’t keep up” than “We can’t get anyone to care.”

At this stage, your questions shift from “Does anyone want this?” to “How fast can we grow this without breaking it?”

11.2 Focus on the right metrics

For software / tech companies, investors and public market data suggest a few key benchmarks:

• Revenue growth: public SaaS companies’ median growth rate around 2024 was ~17% annually; top performers are much higher. If you’re early-stage and growing <30–40% yearly, you’ll look slow.

• Net revenue retention (NRR): aim for >100% (your existing customers expand over time).

• Gross margin: often 70–80%+ for pure software; infra-heavy or AI-heavy products may have lower margins initially.

• Payback period: how many months of gross profit to recoup CAC; <12–18 months is often considered healthy in B2B.

Track a small dashboard:

• MRR / ARR

• New vs churned vs expansion revenue

• CAC and payback

• Activation and retention cohort curves

11.3 Building the organization

As you grow, your biggest challenges become people and process, not code:

• Hire generalists first, then specialists as functions mature.

• Keep teams small (2–8 people) with clear goals.

• Implement lightweight planning (quarterly OKRs or equivalent) rather than big-company bureaucracy.

• Invest in internal communication: weekly all-hands, written updates, shared dashboards.

Culture isn’t about slogans—it’s about the behaviors you encourage and tolerate. For an early tech startup, you typically want:

• Customer-obsessed decision-making

• High standards for quality and speed

• Psychological safety to surface bad news early

• A bias toward experiments over endless debate

12. Why Startups Fail (and How to Avoid It)

Bringing back the data from the failure-rates report:

Common reasons for failure include:

• Lack of sufficient market demand (~40% of failures)

  • Antidote: relentless early customer discovery; kill or pivot ideas without strong pull.

• Cashflow constraints (~40–45%)

  • Antidote: conservative hiring, focus on revenue early, maintain 12–18 months of runway.

• Team and investor problems (~20%)

  • Antidote: clear roles, vesting, communication norms; choose investors as carefully as co-founders.

• Poor timing or external shocks (e.g., macro, regulation)

  • Antidote: flexible roadmaps, diverse customer base, and enough runway to ride out downturns.

• Weak go-to-market and marketing (~10–15%)

  • Antidote: treat sales and marketing as first-class product areas; test channels quickly and double down where you see unit-economic traction.

You can’t eliminate risk, but you can design your company to fail fast and cheaply on bad ideas, and double-down when the data is good.

13. Table: Failure Risk Over Time and What It Implies

Let’s bring the survival data together in a way that informs your planning. Using U.S. BLS-based statistics summarized in recent analyses:

Table 2 – Startup Failure and Survival by Time Horizon (All Sectors, U.S.)

For “true” tech startups—especially venture-backed ones—the effective failure rates are often higher, because expectations are more aggressive. But these numbers give a realistic baseline.

14. A 90-Day Launch Roadmap

To make this concrete, here’s a pragmatic 90-day plan from “I have an idea” to “I have something real in users’ hands”.

Days 1–30: Discover and validate

• Talk to 30–50 potential customers in your target segment.

• Write a 1-page problem + solution + business model narrative.

• Create a simple landing page and drive a trickle of traffic (cold outreach, communities, small ad spend).

• Aim for: 20–100 waitlist sign-ups from your exact ICP and 3–5 strong design-partner candidates.

Days 31–60: Build v0 and charge something

• Build a concierge or low-code MVP that solves a slice of the problem.

• Onboard 3–10 design partners.

• Charge any non-zero price to at least a couple of them, even if nominal. This tests willingness to pay and starts your revenue muscle.

• Iterate weekly based on usage and feedback.

Days 61–90: Tighten product and prepare funding options

• Refine positioning and pricing based on what resonated.

• Document early results: number of users, revenue, retention, quantified impact (e.g., hours saved, errors reduced).

• Decide whether to:

  • Bootstrap further, maybe with small angel checks; or

  • Raise a focused pre-seed/seed round from aligned angels or micro-VCs, using your early traction and learning as proof.

By day 90, success doesn’t mean “unicorn”; it means you’re no longer just a slide deck. You have real users, real behavior, and early revenue—raw material you can improve, scale, and fund.

15. Bringing It All Together

To start and scale a tech startup today, you need to:

1. Be clear-eyed about risk—most companies fail, but they fail for fairly predictable reasons.

2. Understand the environment—VC cycles, AI concentration, and longer paths between rounds shape your funding and growth strategy.

3. Anchor everything in a real problem and real customers—ideas are cheap; validated problems with paying users are not.

4. Design a scalable business model early, even if numbers are rough.

5. Assemble a complementary team and structure the company with proper vesting and governance.

6. Build ugly, learn fast, then refine—shipping and iterating beats over-planning.

7. Treat go-to-market as a product, not an afterthought.

8. Choose funding sources that match your ambitions and risk appetite, not just what’s fashionable.

9. Once you hit product-market fit, professionalize operations and metrics so you can scale responsibly.