Category Archives: anti-patterns

Startup anti-pattern #4: if you build it, they will come

As part of the continued series on startup anti-patterns, we look at the battle between conviction and validation.

First, a story. In 2000, Intech technology, a fledgling startup out of Israel, was building a new type of billing software for property managers. Intech had one potential customer- the Israeli government – that shared the founders’ vision of software which could split bills across multiple tenants in a customizable fashion. For example, using this “killer” feature, the property manager could decide that one tenant pays 70% of the gardening bill while another pays the rest.

The excitement at Intech technologies was at its peak. The founders automatically assumed that if they had the vision and one customer wanted it, many others would. Eighteen months and several layoffs later, the truth was unveiled: end-users didn’t really care about the “killer” feature. Other prospective customers showed no interest in the product’s advanced bill-splitting capabilities. They opted for simpler and cheaper systems that generated invoices and connected to building meters.

After building a product that ended up being an overkill, the company shut down. The founders (Itamar was one of them) learned a hard lesson.

What it is

“If you build it, they will come” is the anti-pattern where startups make decisions based on their vision of how a solution should look, ignoring or underemphasizing customer needs and neglecting to collect sufficient product validation from prospective customers.

The origin of this anti-pattern is the allure of “a great idea”. Entrepreneurs, driven by their passion and conviction, tend to assume that their product’s brilliance alone will captivate customers and guarantee success.

Unfortunately, the mere existence of a product doesn’t automatically translate into customers flocking to buy it. The “if you build it, they will come” mentality often leads to a lack of product-market fit, a leading cause of early stage startup failure.

When combined with confirmation bias, another anti-pattern, this problem becomes even more acute. As with ignorance, it’s usually deadly when combined with a big dose of arrogance.

Why it matters

“If you build it, they will come” mentality can kill your company. It results in redundant product development and misalignment, a significant waste of resources, increased technical debt, and challenges in go-to-market. Hoping that a product will resonate with customers is often a recipe for disaster.

Building a product based on conviction as opposed to market validation can harm your startup in multiple ways:

  • Increased adoption friction. Instead of iterating and improving the product based on customer feedback, startups who fall into this anti-pattern often lack the features customers want. They find themselves trapped in a vicious cycle of slow growth, small capital raises, financial strain and, ultimately, the demise of the startup.
  • Slower product development. Development teams should aim to build what’s most valuable for the business as quickly as possible. Building on conviction without validation is risky because unnecessary features slow down development without creating sufficient business value. Solution complexity and the likelihood of incurring more technical debt, slowing down future development, and shortening a startup’s runway.
  • Low morale. Discovering post-launch that a product isn’t well-received can demoralize a team that worked hard on its development. Before then, team members who know that development is happening with insufficient validation may be demoralized by the company’s approach.

Building “in a vacuum” increases the risk of achieving product-market fit. This misalignment can manifest in various ways. The product might solve a problem that customers don’t care enough about or may fail to meet customers’ expectations or needs. Without product-market fit, it’s harder for a startup to build the right brand, launch effective marketing campaigns, and build the right sales playbook.


Diagnosis requires honest self-reflection. Look at how the company makes product decisions that commit it to significant expenditures of time and money:

  • Are you aware of all important decision points? Lack of awareness leads to implicit decision making. System 1 thinking, skewed by cognitive biases, dominates implicit decisions. Make decisions that commit the company to significant resource use explicitly.
  • When making important decisions, how much weight do you give to conviction (vision, gut feeling) vs. anecdotal evidence (hearsay, one or few data points collected by an ad hoc process) vs. sufficient evidence collected by a thoughtfully designed validation process? Making big decisions without a responsible amount of evidence is risky.
  • Does the evidence supporting decisions come from a sufficiently diverse range of stakeholders, both internal and external ones? Making decisions based on limited/skewed information is risky, especially when decision-makers aren’t aware of the bias and/or variability of the data.

When attempting to diagnose this anti-pattern, make an honest assessment of the extent to which conviction stems from fear. Sim knew a brilliant technical founder who’d rather spend 100 hours writing code than have a validation conversation with a stranger. He thought his product was going to be awesome. It was the only rational way to avoid talking to people who may give him negative feedback.

Fear often deters teams from engaging in validation processes due to a variety of psychological, organizational, and market factors:

  • Fear of being wrong. People often intertwine their ideas with their personal identity. They may perceive being wrong as a personal failure. Cognitive dissonance pushes individuals to avoid situations that might challenge their pre-existing beliefs. Confirmation bias pushes them to unconsciously ignore unfavorable feedback.
  • Fear of the unknown. If validation feedback suggests that significant changes are necessary, this can lead to an overwhelming feeling of uncertainty. The path forward might not be clear, which can be daunting. Even founders, who typically are comfortable with massive amounts of uncertainty, can fall prey to this.
  • Fear of authority. In some hierarchical organizations, when a person of authority has conviction, people lower down in the organization may avoid validation. They fear repercussions if it contradicts the authority figure’s conviction.
  • Fear of disclosure. Some entrepreneurs feel their intellectual property (IP) is so valuable that they fear validation processes might leak some of that IP. In his VC days, Sim met with several founders unwilling to talk about the details of their technology before a term sheet. You can imagine how these pitches went.
  • Fear of being late. Some teams may skip validation to hasten delivery. They may fear that competitors may beat them to market or feel pressure from stakeholders to deliver by a specific deadline. Discussing time pressure trade-offs honestly and explicitly is good. Replacing validation with conviction implicitly, for fear of being late, is a problem.
  • Fear of wasting an investment. Once a team has invested time and money in a particular direction, they might feel that continuing forward is the only option. This is known as the sunk cost fallacy. For fear of creating waste, they will ignore negative evidence. Humans often exhibit loss aversion, where the pain of losing is psychologically about twice as powerful as the pleasure of gaining.

Arrogance and confirmation bias are the most common anti-patterns that make the diagnosis of “if you build it, they will come” difficult.


Misdiagnosis occurs when companies set an unreasonably high bar for the validation required to make product decisions. It may lead to analysis paralysis in organizations, another anti-pattern, reducing the company’s competitiveness in the market and its ability to launch new products in a timely manner.

What is a reasonable, let alone optimal, split between conviction and validation when making decisions? There is no right answer. Context matters. Marissa Mayer famously asked a team at Google to test 41 different shades of blue for the toolbar on Google pages. Was that too much? It’s hardly excessive when considering Google’s scale and Google’s resources. A 41-way test may not have been that much more difficult to execute than a 2-way test. However, the request to test 41 options applied to a product with limited usage would be ridiculous. It’d take too long for the test to produce a valid result.

Refactored solutions

Once diagnosed, the refactoring of this anti-pattern requires changing the organization’s mindset and approach to product development:

  • Empower people to make data-driven decisions. Instrument products for data collection with good security and privacy controls. It should be easy to implement A/B and multivariate tests. Clean, machine-readable metadata should be available for data enhancement. Manage data consistently in a unified platform. Give key stakeholders self-service access to the analytics that matter. Operational dashboards that answer known questions aren’t enough: optimize for ad hoc analytics aimed at answering new questions quickly and precisely. Distribute organizational authority, responsibility, and accountability for making decisions based on data.
  • Embrace market research and customer feedback. Starting at the top, foster a culture of listening to markets by implementing methodologies such as customer development. Engage with potential customers through surveys, interviews, or beta testing to gather valuable feedback that shapes the product roadmap and the entire company. Pay special attention to statistical validity.
  • Share the voice of customers. Broadly distribute customer and market feedback within the organization. Spend time in all-hands and other company-wide communication channels to highlight customers. Empower your customer support/success team to work more closely with product teams and rotating engineers and product managers to support duty.

Your ability to make well-validated product decisions is like a muscle: the more you exercise it, the stronger it gets. Getting good at validation isn’t easy. It requires significant investments in culture, systems, and processes. It also requires overcoming fears.

To overcome fear and foster an environment that encourages validation, organizations and teams can foster a culture of learning and experimentation; encourage collaboration and open communication; and incorporate iterative processes with smart feedback cycles. By addressing fear, organizations can improve the likelihood of developing products that meet market and customer needs, ultimately enhancing their chances of success.

When it could help

This anti-pattern can help in two cases: when an excess of conviction can be useful and when the expected value of validation is low.

As with ignorance, an excess of conviction can be useful in very special circumstances:

  • Entrepreneurs vary wildly in their ability to predict the future. On average, they’re very wrong, but there are outliers. If you have solid evidence, without ego-boosting revisionist history, that you are such an outlier, it may be smart to put relatively more weight on your convictions.
  • If resources and timeframes are very tight, there truly may be no room for doubt or validation, and it may be worth taking on significant validation risk. It’s time for a Hail Mary pass. Startups often live or die by these decisions.
  • There’s a saying in venture capital that a little bit of data is a dangerous thing. Sometimes the presence of data that isn’t great is worse than having no data at all. This is especially true in tough fundraising climates, when investors who are slowing down their investment pace are looking for even more reasons to reject deals. Since hiding bad data is unethical, entrepreneurs sometimes make the decision to avoid or reduce validation instead of risking having to disclose unfavorable data. However, the absence of validation data may lead to fundraising failure.

All these strategies follow the strategy paradox: while they can be extremely successful, they can also lead to extreme failure. Even Steve Jobs, the quintessential product visionary, came up with Macintosh Portable and the Newton.

There are some cases where market validation has lower expected value because it produces fuzzy and/or biased results:

  • Highly disruptive products. One example is Uber/Lyft in the early days. When surveyed, early prospective customers were concerned about getting a ride with an unknown, unlicensed driver. However, after consumers got used to the convenience and cost efficiencies with ride-hailing, they became comfortable with it. Strong network effects compound this early on and it is difficult to imagine the value at scale.
  • Groundbreaking technology. It’s sometimes hard to articulate technology that works like magic to customers. When Steve Jobs introduced the iPhone, many didn’t understand why touch screens would matter so much. Previous smartphones had keyboards and regular touchscreens, and it wasn’t immediately apparent that capacitive touchscreens would change the world.
  • Category creation. In blue ocean scenarios, there are no (or almost no) prospective customers to talk with. The market or category doesn’t exist yet and will only unfold in the (hopefully near-term) future. For example, when Life360 first launched, investors, advisors, and even parents consistently said they don’t believe kids will have smartphones. Smartphones back then were business tools, not replacements for cell phones, and the general audience didn’t think kids would need them. They were clearly wrong (easily said in hindsight).

Some ideas are much harder to validate than others. Smart startups focus a lot of effort on validation to reduce the risk of achieving product-market fit.

Co-authored with Simeon Simeonov. More startup anti-patterns here.

Startup anti-pattern #3: elephant hunting

First, two stories that highlight two different sides of elephant hunting.

In 2005, Meridio was guaranteed to win a deal worth $15m+. Meridio was a small electronic documents and records management (EDRM) startup whose software ran inside some of the world’s most secure organizations: from banks to oil & gas companies to branches of government and the military. One of its happy customers, the UK Ministry of Defense (MoD), was looking to modernize its infrastructure in a massive IT procurement worth billions. Each of the two integrator consortia shortlisted for the deal had designed Meridio into the solution. It was the largest secure SharePoint deployment in the world at the time: a great proof point of the quality and scalability of Meridio’s software. The future looked bright.

Meridio did win the deal and get the money in the end, but the process nearly killed the company:

  • The product roadmap and development prioritization became more complicated.
  • Supporting the two fiercely competitive integrator consortia required staffing up teams with semi-duplicated responsibilities: a significant distraction and increase in burn far ahead of revenue.
  • Once the MoD deal was awarded to one of the consortia, Meridio had many employees it couldn’t put to productive use quickly. The resulting layoffs impacted culture.

The UK MoD deal was important for Meridio — it influenced the 2007 sale of the company to Autonomy, now part of OpenText — but it was less impactful from a valuation standpoint than the company imagined it’d be. Winning the deal came at the expense of distraction and operational inefficiency, both of which affected growth in other areas of the business. Also, there never was another deal like it.

And now for story #2. In 2014 Life360 hit gold. After 18 months of lengthy negotiations, Life360 landed a $50m investment deal from ADT, the global leader in Home Security, coupled with a strategic joint product development opportunity that could net the company tens of millions of dollars in revenue. The team was dancing on rooftops!

In 2019, long after the commercial deal was dead in the water, Life360 decided to go public early (compared to its peers), and one of the considerations was ADT’s significant position as an investor in the company. Further, after years of development that sucked, at times, half of our engineering team’s bandwidth, the product we launched was discontinued and made no contribution to our business. When the company struck the deal employees were initially very excited. They believed that the organization they were working with would be as devoted to the strategic deal’s success as their small startup was. Three management team changes later, it became clear that the deal, which was one of the highest priority items on Life360 plate, was a pretty low priority for ADT. New execs at the company didn’t feel a real commitment to it, and a Private Equity acquisition coupled with organizational changes didn’t help much either.

Everything is easier in hindsight, but Life360 could have avoided this. Luckily, the deal didn’t end up being a company killer and the other parts of the business helped Life360 cement a great spot as a public company. It’s probably fair to say Life360’s success happened despite the ADT deal, not because of it.

What it is?

“Elephant Hunting” is a buzz term describing the practice of targeting deals with very large customers. For example, hunting an elephant in the context of a startup could be a seed-stage company targeting the likes of Google or AT&T as a customer in a million-dollar deal. These customers can provide large contracts, but they can be hard to catch and require large teams to tackle. With business-to-business (B2B) startups, there’s almost nothing more exciting (or seductive) than hunting and bagging an elephant-sized deal. It can produce huge revenue growth, provide you with highly leverageable customer references, and it’ll excite investors. Once you hunt down an elephant, it can feed many mouths (and egos) at the company for a long time. What could be better?

Be warned: the pursuit of elephants can be a dangerous game. If you fail to “kill the elephant” it might well be the one killing you. Unlike young and dynamic startups, elephants are organizational dinosaurs and striking a deal with an elephant will require your entire team — from sales to engineering — to engage with the elephant at different levels of the organization. This engagement happens over months, sometimes years. Even if you succeed in getting an elephant, you may get less benefit than you expected, as the cases of both Meridio and Life360 demonstrate.

Why it matters?

Elephant hunting can bring your company down on its knees. Here are some perils to be aware of:

  • No repeatability. Elephants are hard to catch and often there aren’t enough of them. Meridio never found another UK MoD. Life360 never found another ADT.
  • Heavy operational burden. When you pursue and, later, land an elephant, it’s tempting to put all your resources into serving them. But this can lead to neglecting other clients and missing out on potential opportunities. Both Meridio and Life360 suffered operationally while selling and, later, servicing their respective elephants. Elephants may demand extended payment terms or lower prices, which can put a strain on a startup’s finances. It’s important to carefully consider the financial implications of taking on an elephant client.
  • Missed learning opportunities. When you and your team are laser-focused on one client you might be missing the forest from the trees. As a startup, you seek scalable solutions that matter to most potential customers you want to serve. More feedback is better, and getting feedback from just one elephant makes it harder to identify the scalable, repeatable, products that your target audience needs.
  • Overpromising and underdelivering. In the rush to impress an elephant, startups may make unrealistic promises they can’t keep. This can damage their reputation and lead to the loss of the elephant and future clients. Elephants have tall expectations for products and services delivered, as well as a web of requirements across legal, compliance, cybersecurity, etc. that smaller companies may be incapable of servicing well.
  • Compromising your identity. When a startup lands an elephant, it’s easy to become absorbed in their world and lose sight of your own identity and values. This can lead to compromises that go against your startup’s mission and culture. Note, for example, how many big tech companies have had to compromise to do business in China.
  • Losing control. Elephants may have their own demands and expectations that clash with a startup’s way of doing things. This can lead to a loss of control and autonomy, as the startup becomes beholden to the elephant’s whims. On the partner/channel side, this relates to the platform risk anti-pattern. In conclusion, while landing an elephant can be a huge boost for a startup, it’s important to be aware of the perils that come with it. By maintaining a balance, staying true to your values, and carefully considering the operating implications, startups can avoid the dangers of elephant hunting and build sustainable growth.


Diagnosis is relatively straightforward. Here are a few signals that you might be spending too much time elephant hunting or are getting sucked into the Savannah:

  • Are you and your sales team spending most of your time focused on one deal with a big enterprise client? Has this been going on for an extended period?
  • Are you increasing spend ahead of revenue more than what you’d normally do for just one or two deals?
  • Is a significant chunk of your engineering team’s bandwidth focused on building custom features for one big customer? Does it feel like this customer is essentially dictating your roadmap for the foreseeable future? Do you find yourself having to promise steep SLAs and help desk hours that you know your existing team can’t support now or in the near future? Startups often do need to stretch to deliver, but if your team feels that servicing the elephants will consume the entire company, they’re probably right.


A common misdiagnosis stems from not fully understand or realizing the scope and bandwidth consumption of Elephants. Often, it’s easy for the team to get excited about big deals and they tend to look the other way. Developing and delivering products to Elephants comes with significant overhead, longer sales cycles, lower win rates, and, often, requirements and standards that don’t make a positive impact on the joint outcome, but suck a lot of time and energy from everybody in the room.

Put together KPIs and tools to help you measure the impact elephant hunting has on your Sales and Engineering teams and make data-based decisions.

If your startup is investor-backed, remember that your job is to grow equity value. Revenue, profits and growth are pieces of how equity value is determined. Ask yourself whether the pursuit or even the winning of an elephant will have a meaningful positive impact on equity value given all the positive and negative externalities.

Refactored solutions

Once diagnosed, the refactoring of this anti-pattern very much depends on the set of challenges and opportunities your company has at hand. A few ideas on how to make the most out of Enterprise customers without consuming your entire (small) organization in the process:

  • Try to strike a smaller, multi-phase, deal with the Elephant. That would help both sides build confidence and capabilities to better serve each other.
  • (Artificially) Limit the resources devoted to elephant hunting. Be ruthless about this with your sales and bizdev folks. They’re likely to gravitate towards elephant hunting — these deals tend to be very exciting.
  • Continuously measure and analyze how much your team spends on custom work (especially non-repeatable deals and non-productizable work). It might put a strain on your relationship with the Elephant customer, but good Sales and Customer success teams can help strike a balance and set expectations.
  • Do you have enough slack to sign a deal with an Elephant? One good rule of thumb is assuming that deal will require twice as much resource and time compared to your original expectations. If that’s the case, would you still execute on the deal?

When it could help?

Does this mean you should never try to hunt elephants? No, but it does mean you should think very carefully about it, and be prepared to answer a few questions: 

  1. Where does elephant hunting fit in your sales and growth strategy; near vs. longer term; lower-hanging fruit vs. higher up your sales tree?
  2. How many elephants are there for you to hunt? Is that a real market niche for your business?
  3. Do you have the human resources to hunt and satisfy elephant-sized customers?
  4. Do your sales, engineering and customer success people have the skillsets and experience to satisfy this species of customer? 
  5. Does your CEO have the bandwidth and skill to take down the elephant? This strategy often demands an inordinate amount of the CEO’s time. Which of the CEO’s other responsibilities might suffer?
  6. Does your company have the financial resources to survive and thrive in the face of typically slow decision and purchase cycles? Will investors give you (relatively) cheap cash so that you can wait for the revenue?

For many startups, the transition to spending more time on Elephant hunting is part of the startup journey from childhood to adolescence. If you have good answers to the above questions, a more mature product that is ready to scale, you and your team might be ready to make the move, but tread carefully so you don’t end up being yet another victim on the plains of the Serengeti.

Co-authored with Simeon Simeonov. More startup anti-patterns here – 

Intro to Startup anti-pattern Series

An anti-pattern is a commonly used process, structure, or pattern of action that, despite initially appearing to be an appropriate and effective response to a problem, has more bad consequences than good ones.

Simeon Simeonov first wrote an introduction to the value of startup anti-patterns back in 2013. To sum it up, it’s hard to pinpoint the exact set of reasons startups succeed, but experienced entrepreneurs and investors have a good sense of what drives startups’ failures.

Startup anti-patterns are all about that — patterns that increase the risks associated with startups (hey, it’s a risky business to begin with). Pursuing an anti-pattern doesn’t mean that your company will die tomorrow or in the next year, but each anti-pattern adds-up and could lead to clouding your focus and hampering your ability to execute.

Together with Itamar Novick from Recursive Ventures, Simeon Simeonov is bringing the Startup anti-pattern series to life. Stay tuned for more in this series as we work through each anti-pattern with tangible examples from our experiences as founders and investors in 100+ startups, and the experiences of guest founders from our portfolio.

Startup Anti-Patterns full list (work in progress…)

Studying repeatable patterns of startup failure (startup anti-patterns) is more useful than studying non-repeatable strategies for startup success.

Top Startup Anti-Patterns:

  1. Elephant hunting
  2. Ignorance
  3. Platform risk
  4. If you build it, they will come
  5. Analysis paralysis
  6. Arrogance
  7. Attribution risk
  8. Bad revenue
  9. Bleeding on the edge
  10. Boiling the ocean
  11. Bridge to nowhere
  12. Changing strategy instead of execution
  13. Chasing the competition
  14. Confirmation bias
  15. Confusing activity with results
  16. Consulting to product
  17. Death by pivot
  18. Deathmarch
  19. Delayed scaling
  20. Demand generation
  21. Design by committee
  22. Designing for investors
  23. Drag
  24. Escalation of commitment
  25. Escape to the familiar
  26. Escapism
  27. Featuritis
  28. Forward thinking
  29. Founderitis
  30. Groupthink
  31. Hail Mary
  32. Ivory tower
  33. Lack of focus
  34. Lagging indicators
  35. Learned helplessness
  36. Long feedback cycles
  37. Lying to investors
  38. Magic salesperson
  39. Mentor whiplash
  40. Missing your exit
  41. Myopic bootstrapping
  42. Next round only
  43. Not knowing your investors
  44. One-off customization
  45. Oooh, shiny!
  46. Overengineering
  47. Overselling
  48. Oversteering
  49. Platform trap
  50. Premature optimization
  51. Premature scaling
  52. Promiscuity
  53. Proof by anecdote
  54. Pushing a rope
  55. Raising too little
  56. Random founders
  57. Scapegoat
  58. Second class citizens
  59. Seed extensions
  60. Secrecy
  61. Silver bullet
  62. Spreadsheet Bingo
  63. Stovepipes
  64. The one idea entrepreneur
  65. Top-down planning
  66. Uber pivot
  67. Underqualifying
  68. Unicorn hunting
  69. Unrealistic expectations
  70. Warm bodies
  71. Weak board
  72. Yes man
  73. Zombie
  74. Outsourcing your architecture (via Alan Neveu)

Note: the list is not “drawn to scale.” Some anti-patterns occur more frequently than others and some are more likely to cause a startup to fail than others.