In 2023, Itamar Novick at Recursive Ventures started the Startup Anti-Pattern Series on his website, cataloguing 75 recurring ways startups hurt themselves. At the time of writing this post he hasn’t drafted content for more than the first 14, so I wanted to re-create his list here, with an example of each anti-pattern.
| # | Anti-pattern | One-line example |
|---|---|---|
| 1 | Elephant hunting | A five-person SaaS startup spends 14 months chasing a $2M Fortune 100 contract instead of selling $20K deals to smaller customers. |
| 2 | Ignorance | The founders enter healthcare without understanding HIPAA, reimbursement, procurement cycles, or how hospitals actually buy software. |
| 3 | Platform risk | A startup builds its entire business on one social network’s API and collapses when that API access is restricted. |
| 4 | If you build it, they will come | Engineers spend two years perfecting a product without talking to customers, then launch to almost zero demand. |
| 5 | Bad revenue | A SaaS company celebrates $1M ARR even though most revenue comes from low-margin custom services distracting the team from its product. |
| 6 | Chasing the competition | Every time a competitor launches a feature, the startup immediately copies it regardless of whether its own customers need it. |
| 7 | Chasing Blue Oceans | A founder rejects every proven market as “too competitive” and keeps searching for a market where nobody else is selling anything. |
| 8 | Analysis paralysis | The team spends six months comparing pricing strategies rather than testing three prices with actual customers. |
| 9 | Founder arrogance | The CEO dismisses repeated customer complaints because “customers don’t understand the vision yet.” |
| 10 | Boiling the ocean | A startup tries to build CRM, payments, analytics, payroll, messaging, and accounting simultaneously before finding product-market fit. |
| 11 | Bridge to nowhere | The company builds sophisticated infrastructure for millions of users while its product has only 300 active customers. |
| 12 | Design by committee | Product decisions require consensus from founders, sales, engineering, investors, advisers, and five launch customers until the product becomes incoherent. |
| 13 | Confirmation bias | The founder highlights three enthusiastic customer interviews while ignoring twenty prospects who said they would never pay. |
| 14 | Bleeding on the edge | A startup adopts an experimental database nobody on the team knows and loses weeks fixing problems mature technology already solved. |
| 15 | Attribution risk | Sales jump after a marketing campaign and the company assumes the campaign caused it without noticing a major competitor simultaneously shut down. |
| 16 | Changing strategy instead of execution | After two weak sales months, the founders abandon the target market rather than fixing their ineffective outbound process. |
| 17 | Confusing activity with results | The sales team proudly reports 2,000 emails sent and 150 demos booked while revenue remains flat. |
| 18 | Consulting to product | A consulting firm assumes software built for three clients can simply be packaged and sold as a scalable SaaS product. |
| 19 | Death by pivot | The startup changes from fintech to HR tech to creator tools to AI agents within eighteen months and masters none of them. |
| 20 | Deathmarch | Leadership requires months of nonstop nights and weekends to hit an unrealistic launch date until key employees quit. |
| 21 | Delayed scaling | A company clearly discovers repeatable profitable acquisition but remains overly cautious and lets better-funded competitors capture the market. |
| 22 | Demand generation | The startup spends heavily trying to convince customers they have a problem instead of targeting buyers already seeking a solution. |
| 23 | Designing for investors | The founders shape product, metrics, and strategy around what sounds fundable rather than what customers actually value. |
| 24 | Drag | One dysfunctional executive repeatedly slows decisions, hiring, releases, and deals but remains because nobody wants the confrontation. |
| 25 | Escalation of commitment | After investing $3M into a failed product, management invests another $2M because abandoning it would mean admitting the original decision was wrong. |
| 26 | Escape to the familiar | When sales become difficult, a technical founder retreats into coding new features because engineering feels more comfortable than talking to customers. |
| 27 | Escapism | Instead of addressing churn, the CEO spends weeks redesigning the office, attending conferences, and brainstorming the company’s ten-year vision. |
| 28 | Featuritis | The roadmap contains 80 new features while users keep asking for the three existing core workflows to work reliably. |
| 29 | Forward thinking | The team prioritizes hypothetical future needs over fixing problems current customers are experiencing today. |
| 30 | Founderitis | A founder refuses to hire experienced leaders or delegate decisions because nobody else can possibly understand the company as well as they do. |
| 31 | Groupthink | Everyone agrees with an aggressive international expansion because nobody wants to be the only executive challenging the CEO. |
| 32 | Hail Mary | With three months of runway left, the company bets nearly all remaining cash on one giant product launch. |
| 33 | Ivory tower | Product managers design workflows from headquarters without observing how actual warehouse workers use the software. |
| 34 | Lack of focus | A 12-person startup simultaneously targets consumers, SMBs, enterprises, developers, schools, and government agencies. |
| 35 | Lagging indicators | Management waits for quarterly revenue numbers to reveal problems instead of monitoring pipeline, activation, retention, and usage earlier. |
| 36 | Learned helplessness | After repeatedly losing enterprise deals, the sales team concludes “large companies never buy from startups” and stops trying new approaches. |
| 37 | Long feedback cycles | Engineers work for nine months before putting the product in users’ hands, making every incorrect assumption extremely expensive. |
| 38 | Lying to investors | The CEO describes signed pilots as recurring customers and presents pipeline opportunities as nearly guaranteed revenue. |
| 39 | Magic salesperson | Founders believe hiring one superstar VP Sales will magically fix an offer that founders themselves have never successfully sold. |
| 40 | Mentor whiplash | The company changes pricing Monday, positioning Wednesday, and go-to-market Friday after three different advisers give conflicting advice. |
| 41 | Missing your exit | Founders reject a strong acquisition offer expecting enormous growth, only to watch the market collapse twelve months later. |
| 42 | Myopic bootstrapping | A profitable founder refuses outside capital even when additional funding could clearly accelerate a winner in a land-grab market. |
| 43 | Next round only | Management optimizes every metric and announcement to secure Series B rather than building an economically sustainable company. |
| 44 | Not knowing your investors | A founder takes money from an investor without realizing that investor routinely replaces founders when companies encounter trouble. |
| 45 | One-off customization | Sales closes ten customers by promising ten unique versions of the product until engineering effectively maintains ten separate products. |
| 46 | Oooh, shiny! | The roadmap suddenly pivots to generative AI because it is fashionable even though customers are asking for basic reporting improvements. |
| 47 | Overengineering | A startup expecting 5,000 users builds a microservices architecture designed to handle 500 million. |
| 48 | Overselling | Sales promises automated integrations and real-time analytics that don’t exist, leaving implementation teams to apologize after contracts are signed. |
| 49 | Oversteering | The CEO changes strategy after every week of weak metrics, preventing any initiative from running long enough to produce meaningful evidence. |
| 50 | Platform trap | The startup tries to become an ecosystem before its core product is valuable enough to support one. |
| 51 | Premature optimization | Engineers spend weeks reducing page-load time from 220ms to 150ms while only a few hundred people use the product. |
| 52 | Premature scaling | A startup hires 40 salespeople immediately after closing its first three founder-led deals before knowing whether the process is repeatable. |
| 53 | Promiscuity | The company pursues too many customers, channels, partnerships, and experiments at once to learn deeply from any of them. |
| 54 | Proof by anecdote | The founder concludes the product has product-market fit because one famous CEO said it was “amazing.” |
| 55 | Pushing a rope | Sales repeatedly pressures prospects to adopt a product they don’t consider urgent instead of identifying customers already desperate for the solution. |
| 56 | Raising too little | A hardware startup raises enough money to design its device but not enough to manufacture, certify, distribute, and support it. |
| 57 | Random founders | Three people meet at a networking event, decide startups sound exciting, and incorporate together before learning how they work under pressure. |
| 58 | Scapegoat | The board blames the VP Sales for missed targets even though poor positioning, pricing, and product reliability are the real causes. |
| 59 | Second class citizens | Engineering gets prestige, equity, and executive access while support and implementation teams handling customers are treated as replaceable labor. |
| 60 | Seed extensions | Instead of confronting weak traction, a startup repeatedly raises small seed extensions that keep it alive without resolving the underlying problem. |
| 61 | Secrecy | Founders refuse to discuss their idea with potential users for fear of theft and consequently build something nobody wants. |
| 62 | Silver bullet | Leadership believes a rebrand, new VP, AI feature, major partnership, or funding round will single-handedly solve deep structural problems. |
| 63 | Spreadsheet Bingo | Management adjusts assumptions in the financial model until the spreadsheet conveniently produces the revenue number investors want to see. |
| 64 | Stovepipes | Sales, engineering, marketing, and customer success optimize their own metrics while barely communicating with one another. |
| 65 | The one idea entrepreneur | A founder remains emotionally committed to the original idea even after strong evidence shows the underlying customer problem is different. |
| 66 | Top-down planning | Executives set an annual roadmap containing hundreds of commitments without input from the people building the product or talking to customers. |
| 67 | Uber pivot | After struggling with an ordinary marketplace, founders reposition it as “Uber for X” even though its supply, frequency, and unit economics cannot support an on-demand model. |
| 68 | Underqualifying | Sales accepts demos with anyone who fills out a form and wastes most of its time talking to prospects with no budget, authority, or need. |
| 69 | Unicorn hunting | The team dismisses strong, achievable opportunities because they are obsessed with finding a business capable of becoming a massive outlier. |
| 70 | Unrealistic expectations | Founders budget for revenue to grow 20% every month indefinitely despite having no evidence their acquisition channels can support it. |
| 71 | Warm bodies | Management responds to missed deadlines by hiring more people rather than fixing unclear ownership, weak processes, and poor technical architecture. |
| 72 | Weak board | Directors politely approve management decisions without challenging strategy, metrics, executive performance, or major capital allocation choices. |
| 73 | Yes man | The CEO surrounds herself with executives who enthusiastically support every idea and gradually drives away anyone willing to disagree. |
| 74 | Zombie | The startup generates enough revenue to survive indefinitely but not enough growth or profitability to create a meaningful outcome for founders or investors. |
| 75 | Outsourcing your architecture | A startup lets an external development agency make all core architecture decisions and later discovers nobody internally understands its own system. |