a16z: The best technology doesn't necessarily guarantee the final victory in the enterprise market

Written by: Pyrs Carvolth, Christian Crowley

Translated by: Chopper, Foresight News

In the current blockchain application cycle, founders are learning a disturbing but profound lesson: companies don’t buy the “best” technology; they buy the least disruptive upgrade path.

For decades, new enterprise-level technologies have promised to deliver exponential improvements over traditional infrastructure: faster settlements, lower costs, cleaner architectures. But in practice, the implementation rarely matches the full extent of these technical advantages.

This means: if your product is “better” but can’t win, the gap isn’t in performance but in product fit.

This article is for a group of crypto founders: those who started in public chains and are now painfully shifting toward enterprise solutions. For many, this is a huge blind spot. Here, we share key insights based on our experience, successful cases of founders selling products to enterprises, and real feedback from corporate buyers, to help everyone better pitch and close deals with enterprises.

What Does “Best” Really Mean?

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

SWIFT is slow and expensive but remains dominant. Why? Because it offers shared governance and regulatory reassurance. COBOL is still in use because rewriting stable, critical systems poses survival risks. Batch file transfers persist because they establish clear checkpoints and audit trails.

A potentially uncomfortable conclusion is: enterprise adoption of blockchain is hindered not by lack of education or vision, but by misaligned product design. Founders insisting on pushing the most perfect form of technology will keep hitting walls. Those who treat enterprise constraints as design inputs rather than compromises are more likely to succeed.

So, don’t diminish blockchain’s value; instead, focus on packaging the technology into an enterprise-acceptable version, which requires the following approaches.

Enterprises Care More About Losses Than Gains

A common mistake founders make when pitching to enterprises is assuming decision-makers are primarily motivated by benefits: better technology, faster systems, lower costs, cleaner architecture.

In reality, the core motivation for enterprise buyers is minimizing downside risk.

Why? Because in large organizations, the cost of failure is asymmetric. Unlike small startups, founders who haven’t worked in big companies often overlook this. Missing an opportunity rarely results in punishment, but obvious mistakes—especially involving unfamiliar new tech—can severely impact careers, trigger audits, or even attract regulatory scrutiny.

Decision-makers rarely benefit directly from the technology they recommend. Even if there’s strategic alignment or company-level investments, the benefits are dispersed and indirect. But losses are immediate and often personal.

As a result, enterprise decisions are rarely driven by “what could be achieved.” Instead, they’re driven by “what’s highly unlikely to fail.” That’s why many “better” technologies struggle to gain traction. The hurdle isn’t technical superiority but whether using the technology makes decision-makers’ jobs safer or riskier.

Therefore, you must rethink: who is your customer? One of the biggest mistakes founders make in enterprise sales is assuming “the most knowledgeable technical person” is the buyer. In reality, enterprise adoption is rarely driven by technical conviction; it’s more about organizational dynamics.

In large organizations, decisions are less about benefits and more about risk management, coordination costs, and accountability. At scale, most organizations outsource some decision processes to consultants—not because they lack intelligence or expertise, but because key decisions must be continuously validated and justified. Engaging reputable third parties provides external endorsement, disperses responsibility, and offers credible backing when decisions are questioned later. Most Fortune 500 companies operate this way, allocating substantial budgets annually to consulting.

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

How Do Companies Make Decisions?

Corporate decision-making is similar to how many now use ChatGPT: we don’t ask it to make decisions for us, but to test ideas, weigh pros and cons, and reduce uncertainty—while remaining responsible ourselves.

The behavior is similar; the support layer, however, is human, not a large model.

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

• What problems could arise?

• Who is responsible if something goes wrong?

• How does this fit with existing systems?

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

Therefore, for truly innovative projects, “the customer” is almost never a single buyer. Instead, it’s a coalition of stakeholders, many of whom care more about avoiding mistakes than about innovation.

Many technically superior products fail here: not because they can’t be used, but because the organization lacks the people who can safely operate them.

For example, consider an online gambling platform. With the rise of prediction markets, crypto “salespeople” (like payment gateway providers) might see online sports betting as a natural enterprise client. But to do so, you must understand that the regulatory framework for online sports betting differs from prediction markets, including licensing in different states. Knowing that state regulators have varying attitudes toward crypto, payment providers realize their clients aren’t the engineering or business teams eager to access crypto liquidity, but the legal, compliance, and finance teams concerned about existing gambling licenses and fiat business risks.

The simplest solution is to identify decision-makers early. Don’t be afraid to ask your product supporters (those who like your product) how they can help promote it internally. Behind the scenes, legal, compliance, risk, finance, and security teams hold veto power and have very different concerns. A winning team packages the product as a risk-controlled decision, with stakeholders having ready-made answers and a clear risk/reward framework. By asking questions, you’ll learn who to tailor your messaging for and how to find a seemingly safe, reassuring “consent” path.

Consulting Firms

Often, before reaching enterprise buyers, new technologies pass through intermediaries—consultants, system integrators, auditors—who play key roles in translating and legitimizing new solutions. Whether you like it or not, they are gatekeepers. They use familiar frameworks and collaboration models to turn new proposals into familiar concepts, reducing uncertainty into actionable advice.

Founders often feel frustrated or suspicious, thinking consulting firms slow down progress, add unnecessary layers, or influence final decisions for their own benefit. They are right—yet founders must be pragmatic: in the US alone, the management consulting market is projected to exceed $130 billion by 2026, mostly serving large enterprises in strategy, risk, and transformation. While blockchain-related projects are a small part of this, don’t assume that simply branding your project as “blockchain” will bypass this decision-making system.

This pattern has influenced enterprise decisions for decades. Even if you’re selling a blockchain solution, this logic remains. Our experience with Fortune 500 companies, large banks, and asset managers repeatedly shows that ignoring this layer can lead to strategic errors.

A typical example is Deloitte’s partnership with Digital Asset: by collaborating with a major consulting firm, Digital Asset’s blockchain infrastructure is repackaged into familiar enterprise language—governance, risk, compliance. For institutional buyers, the involvement of a trusted third party like Deloitte not only validates the technology but also clarifies the path to implementation.

Don’t Use the Same Pitch

Because decision-makers are highly sensitive to their own needs—especially downside risks—you must customize your presentation: don’t use the same pitch, slides, or framework for every potential client.

Details matter. Two large banks may seem similar on the surface, but their systems, constraints, and priorities can differ vastly. What resonates with one may be ineffective with the other.

A one-size-fits-all approach signals you haven’t taken the time to understand their specific project definition. Without tailored messaging, it’s hard for organizations to believe your solution will fit perfectly.

Another common mistake is the “start from scratch” narrative. In crypto, founders often envision a completely new future: replacing legacy systems entirely with newer, decentralized tech to usher in a new era. But in reality, most enterprises have deeply embedded infrastructure—workflow, compliance, vendor contracts, reporting systems, and countless touchpoints. Starting over would not only disrupt daily operations but also introduce significant risks.

The broader the scope of change, the more internal resistance there is: bigger decisions require larger coalitions.

Successful cases we’ve seen involve founders first adapting to the existing enterprise environment, rather than demanding clients conform to their ideal vision. When designing entry points, aim to integrate with current systems and workflows, minimizing disruption and establishing reliable footholds.

A recent example is Uniswap’s partnership with BlackRock on tokenized funds. Uniswap didn’t 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 didn’t require BlackRock to change its operations—just extended them on-chain.

Once your solution passes procurement and is officially deployed, it’s still possible—and advisable—to pursue larger goals later.

Enterprises Hedge Their Bets; You Want to Be That “Right Hedge”

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

Big companies don’t put all their eggs in one basket with emerging infrastructure; instead, they run multiple experiments simultaneously. They allocate small budgets to several vendors, test various solutions within innovation departments, or pilot without touching core systems. This preserves options while limiting exposure.

But founders should beware: being selected doesn’t mean being adopted. Many crypto companies are just options for enterprises to test the waters. Pilot projects are fine, but there’s no need to scale prematurely.

The real goal is to become the “most promising hedge”—the one most likely to be adopted. Achieving this requires not only technical superiority but also professionalism.

Why Professionalism Outweighs Purity

In these markets, clarity, predictability, and credibility often beat pure innovation: technical excellence alone rarely wins. That’s why professionalism is crucial—it reduces uncertainty.

We mean: when designing and presenting your product, fully consider institutional realities—legal constraints, governance processes, existing systems—and aim to operate within those frameworks. Following established practices signals that your product is governable, auditable, and controllable. Whether or not this aligns with the ideals of decentralization or crypto ethos, enterprises view technology implementation through this lens.

This isn’t resistance to change; it’s a rational response to corporate incentives.

Obsessing over ideological purity—be it “decentralization,” “trustlessness,” or other crypto principles—rarely convinces risk-averse, regulated institutions. Expecting companies to fully embrace a “complete vision” overnight is unrealistic and overly hasty.

Of course, there are breakthrough cases where cutting-edge tech and ideological purity align. LayerZero’s recent launch of the new public chain Zero aims to address enterprise scalability and interoperability while maintaining core decentralization and permissionless innovation principles.

But Zero’s real differentiation isn’t just architecture; it’s the organizational approach. Instead of building a one-size-fits-all network and expecting enterprises to adapt, it collaborates with key partners to design dedicated “Zones” for specific use cases like payments, settlements, and capital markets.

The architecture, team, and brand of LayerZero, along with their willingness to co-develop these applications, significantly reduce concerns from large traditional financial institutions. This combination has led firms like Citadel, DTCC, and ICE to become partners.

Founders often mistake enterprise resistance as mere conservatism or bureaucracy. Sometimes that’s true, but often there’s another reason: most institutions are rational, aiming to sustain operations. Their design goal is to preserve capital, protect reputation, and withstand scrutiny.

In such environments, winning technology isn’t necessarily the most elegant or ideologically pure—it’s the one that best fits the enterprise’s current state.

These realities help us understand the long-term potential of blockchain infrastructure in the enterprise sector.

Transformation rarely happens overnight. Look at the “digital transformation” of the 2010s: despite existing for years, most large companies still modernized core systems gradually, often spending huge sums on consulting. Large-scale digital transformation is a step-by-step process—integrating carefully, expanding based on proven use cases, rather than complete overnight replacement. That’s the reality of enterprise change.

Successful founders are those who understand how to implement in phases, not those demanding a full vision from the start.