a16z's harsh lesson for crypto founders: Why don't companies buy the best technology?

Original Title: The best technology doesn't always win (in the enterprise)

Original Authors: Pyrs Carvolth, Christian Crowley, a16z crypto

Original Compiler: Chopper, Foresight News

In the current blockchain application cycle, founders are learning a disturbing yet profound lesson: enterprises do not buy the "best" technology; they buy the upgrade path with the least disruption.

For decades, new enterprise-level technologies have promised orders of magnitude improvements over traditional infrastructure: faster settlements, lower costs, cleaner architectures. However, the reality rarely matches the technological advantages.

This means that if your product is "clearly better" but still fails to win, the gap is not in performance but in product fit.

This article is written for a group of founders in the crypto space: those who started in the public chain scene and are now painfully pivoting to enterprise-level business. For many, this is a significant blind spot. Below, we share several key insights based on our experiences, successful cases of founders selling products to enterprises, and real feedback from enterprise buyers to help everyone better market to enterprises and secure orders.

What Does "Best" Really Mean

Within large enterprises, "the best technology" is the one that perfectly integrates with existing systems, approval processes, risk models, and incentive structures.

SWIFT is slow and expensive, yet it remains unshaken. Why? Because it provides shared governance and regulatory security. COBOL is still in use because rewriting stable systems poses survival risks. Batch file transfers still exist because they create clear checkpoints and audit trails.

A potentially uncomfortable conclusion is that the adoption of blockchain by enterprises is hindered not by a lack of education or vision, but by misaligned product design. Founders who insist on promoting the most perfect technological form will continually hit walls. Those who treat enterprise constraints as design inputs rather than compromise solutions are the ones most likely to succeed.

Therefore, there is no need to downplay the value of blockchain; the key is to help the technical team package a version that enterprises can accept, which requires the following ideas.

Enterprises Fear Loss More Than They Love Gain

One common mistake founders make when selling to enterprises is assuming that decision-makers are primarily driven by gains—better technology, faster systems, lower costs, cleaner architectures, and so on.

The reality is that the core motivation of enterprise buyers is to minimize downside risk.

Why? In large institutions, the cost of failure is asymmetric. This is in stark contrast to small startups, and founders who have not spent time in large companies often overlook this point. Missing an opportunity rarely incurs penalties, but obvious mistakes (especially those related to unfamiliar new technologies) can severely impact career prospects, trigger audits, and even attract regulatory scrutiny.

Decision-makers rarely benefit directly from the technologies they recommend. Even if there is strategic alignment and company-level investment, the benefits are often dispersed and indirect. But losses are immediate and often personal.

As a result, enterprise decisions are rarely driven by "what could be achieved" but more by "the high probability of not failing." This is why many "better" technologies struggle to gain traction. The threshold for implementation is often not technological superiority but rather: does using this technology make the decision-maker's job safer or more dangerous?

Thus, you must rethink: who is your customer? One of the most common mistakes founders make in enterprise sales is assuming that "the most tech-savvy person" is the buyer. In reality, enterprise implementation is rarely driven by technological faith but more by organizational dynamics.

In large institutions, decisions are less about gains and more about risk management, coordination costs, and accountability. At the enterprise level, most organizations will outsource part of the decision-making process to consulting firms, not because they lack intelligence or expertise, but because key decisions must be continuously validated and substantiated. Introducing a well-known third party can provide external endorsement, disperse responsibility, and offer credible justification when decisions are later questioned. Most Fortune 500 companies operate this way, which is why there are substantial consulting fees in their annual budgets.

In other words: the larger the institution, the more decisions must withstand internal scrutiny afterward. As the saying goes, "No one gets fired for hiring McKinsey."

How Enterprises Make Decisions

Enterprise decision-making is quite similar to how many people currently use ChatGPT: we do not let it make decisions for us; instead, we use it to validate ideas, weigh pros and cons, and reduce uncertainty, while always holding ourselves accountable.

The behavior of enterprises is largely the same; their decision support layers are human, not large models.

New decisions must pass through layers of legal, compliance, risk, procurement, security, and executive oversight. Each layer has different concerns, such as:

• What could go wrong?

• Who is responsible if something goes wrong?

• How does this integrate with existing systems?

• How do I explain this decision to executives, regulators, or the board?

Therefore, for truly meaningful innovation projects, the "customer" is almost never a single buyer. The so-called "buyer" is actually a coalition of stakeholders, many of whom are more concerned about not making mistakes than about innovation.

Many technically superior products often fail here: it is not that they cannot be used, but that there are no suitable people within the organization who can use them safely.

Take the example of an online betting platform. As prediction markets become popular, crypto "water sellers" (such as deposit channel service providers) may see online sports betting platforms as natural enterprise customers. But to do this, you must first understand: the regulatory framework for online sports betting is different from that of prediction markets, including individual licenses for each state. Knowing that regulatory attitudes toward crypto vary by state, deposit service providers will realize that their customers are not looking to integrate products, engineering, or business teams for crypto liquidity, but rather the legal, compliance, and finance teams, who are concerned about the risks associated with existing betting licenses and core fiat operations.

The simplest solution is to clearly identify decision-makers early on. Do not hesitate to ask your product supporters (those who like your product) how they can help promote it internally. Behind the scenes often stand legal, compliance, risk, finance, and security... they all have hidden veto power and vastly different concerns. Winning teams will package the product as a risk-controlled decision, providing stakeholders with ready answers and a clear benefit/risk framework. As long as you ask, you can find out for whom to package, and then find a seemingly safe yet reassuring path to "agreement."

Consulting Firms

Often, new technologies first pass through an intermediary before reaching enterprise buyers. Consulting firms, system integrators, auditors, and other third parties often play a key role in the transformation and legitimization of new technologies. Whether you like it or not, they have become the gatekeepers of new technologies. They use established, familiar frameworks and collaboration models to translate new solutions into concepts people understand, turning uncertainty into actionable recommendations.

Founders often feel frustrated or skeptical about this, believing that consulting firms slow down progress, add unnecessary processes, and become additional stakeholders influencing final decisions. They do! But founders must be realistic: in the U.S. alone, the management consulting services market is expected to exceed $130 billion by 2026, with most of it coming from large enterprises seeking help with strategy, risk, and transformation. Although blockchain-related business constitutes only a small portion, do not think that simply adding "blockchain" to a project will allow you to bypass this decision-making system.

Whether you like it or not, this model has influenced enterprise decision-making for decades. Even if you are selling a blockchain solution, this logic will not disappear. Our experiences communicating with Fortune 500 companies, large banks, and asset management institutions repeatedly prove that ignoring this layer could lead to strategic errors.

The collaboration between Deloitte and Digital Asset is a typical example: by partnering with large consulting firms like Deloitte, Digital Asset's blockchain infrastructure was repackaged into language more familiar to enterprises, such as governance, risk, and compliance. For institutional buyers, the involvement of trusted parties like Deloitte not only validates the technology but also clarifies and substantiates the implementation path.

Do Not Use the Same Pitch

Because enterprise decision-makers are extremely sensitive to their own needs (especially downside risks), you must customize your presentations: do not use the same corporate sales pitch, the same PPT, or the same framework for every potential customer.

Details matter. Two large banks may appear similar on the surface, but their systems, constraints, and internal priorities can be vastly different. What resonates with one may be completely ineffective with another.

A one-size-fits-all pitch essentially tells the other party that you have not taken the time to understand this institution's specific definition of the project. If your pitch is not tailored, it will be hard for the institution to believe that your solution can perfectly fit.

An even more serious mistake is the "start from scratch" rhetoric. In the crypto space, founders often tend to paint a picture of a brand new future: completely replacing old systems with newer, better decentralized technologies to usher in a new era. But enterprises rarely do this; traditional infrastructure is deeply embedded in workflows, compliance processes, existing vendor contracts, reporting systems, and countless touchpoints and stakeholders. Starting from scratch not only disrupts daily operations but also introduces various risks.

The broader the impact of the change, the less anyone within the organization dares to make a decision: the larger the decision, the larger the decision-making coalition.

The successful cases we have seen are those where founders first adapt to the current situation of enterprise customers rather than demanding that customers adapt to their ideals. When designing entry points, it is essential to integrate into existing systems and workflows, minimize disruption, and establish reliable entry points.

A recent example is the collaboration between Uniswap and BlackRock on tokenized funds. Uniswap did not position DeFi as a replacement for traditional asset management but instead provided permissionless secondary market liquidity for products issued under BlackRock's existing regulatory and fund structures. This integration does not require BlackRock to abandon its operational model; it merely extends it onto the blockchain.

Once you navigate the procurement process and the solution is officially launched, you can pursue more ambitious goals later.

Enterprises Hedge Their Bets; You Need to Be the "Right Hedge"

This risk aversion manifests as a predictable behavior: institutions hedge their bets, often on a large scale.

Large enterprises do not place all their bets on emerging infrastructure; instead, they conduct multiple experiments simultaneously. They allocate small budgets to multiple suppliers, test various solutions in innovation departments, or pilot projects without touching core systems. From the institution's perspective, this preserves options while limiting risk exposure.

But for founders, there is a subtle trap here: being chosen ≠ being adopted. Many crypto companies are merely one of the options enterprises use to test the waters; piloting may be fine, but there is no need to scale up.

The real goal is not to win a pilot but to become the hedge with the highest probability of success. This requires not just a technological advantage but also professionalism.

Why Professionalism Trumps Purity

In such markets, clarity, predictability, and trustworthiness often outweigh pure innovation: it is difficult to win solely on technology. This is why professionalism is crucial; it reduces uncertainty.

What we mean by professionalism is: when designing and presenting a product, one must fully consider institutional realities (such as legal constraints, governance processes, and existing systems) and strive to operate within these frameworks. Following conventions signals to the other party that the product is governable, auditable, and manageable. Regardless of whether this aligns with the spirit of blockchain or crypto, this is how enterprises view the implementation of technology.

This may seem like enterprises resisting change, but it is not. It is a rational response to the incentive mechanisms of enterprises.

Getting caught up in the ideological purity behind the technology, whether "decentralized," "minimum trust," or other crypto principles, is unlikely to persuade institutions constrained by legal, regulatory, and reputational factors. Demanding that enterprises accept a product with a "complete vision" all at once is asking too much and is overly ambitious.

Of course, there are examples of breakthrough technologies that achieve a win-win with ideological purity. LayerZero recently launched a new public chain, Zero, attempting to solve scalability and interoperability issues in enterprise implementation while retaining the core principles of decentralization and permissionless innovation.

However, Zero's true differentiation lies not just in its architecture but in its institutional design thinking. It did not create a one-size-fits-all network and expect enterprises to adapt; instead, it collaborated with core partners to design dedicated "Zones" for specific scenarios like payments, settlements, and capital markets.

The architecture of Zero, the willingness of the team to collaborate around these application scenarios, and LayerZero's brand have all significantly reduced some concerns of large traditional financial institutions. These factors combined have led institutions like Citadel, DTCC, and ICE to announce partnerships.

Founders often easily interpret enterprise resistance as conservatism, bureaucracy, or a lack of vision. Sometimes this is true, but often there is another layer of reason: most institutions are not irrational; they aim to maintain operations. Their design goals are to preserve capital, protect reputation, and withstand scrutiny.

In this environment, the technologies that win are not necessarily the most elegant or ideologically pure but are those that strive to adapt to the current state of enterprises.

These realities can help us see the long-term potential of blockchain infrastructure in the enterprise space.

Enterprise transformation rarely happens overnight. Look at the "digital transformation" of the 2010s: despite the relevant technologies having existed for years, most large enterprises are still modernizing core systems, often requiring substantial funds to hire consulting firms. Large-scale digital transformation is a gradual process that requires controlled integration and expansion based on mature use cases rather than a complete overnight replacement. This is the reality of enterprise transformation.

Successful founders are not those who demand a complete vision from the start but those who understand how to implement step by step.