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

The best technology doesn’t always win (in the enterprise)

Authors: Pyrs Carvolth, Christian Crowley, a16z crypto

Compiled by: Chopper, Foresight News

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

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 technological advantages.

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

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

What does “best” really mean?

Within large enterprises, “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 security. COBOL is still in use because rewriting stable systems poses survival risks. Batch file transfers persist because they create 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.

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

Enterprises fear loss far more than they value gains

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

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

Why? In large organizations, the cost of failure is asymmetric. Unlike startups, where missed opportunities rarely lead to severe consequences, obvious mistakes (especially involving unfamiliar new technology) can seriously impact careers, trigger audits, or even attract regulatory scrutiny.

Decision-makers rarely benefit directly from the technology they recommend. Even if strategic alignment and company-level investments are involved, 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” but more by “what is unlikely to fail.” This explains why many “better” technologies struggle to gain traction. The hurdle isn’t technological superiority but whether using the technology makes the decision-maker’s job safer or riskier.

So, you need to 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 defensible. 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 to consulting firms annually.

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 enterprises actually make decisions?

Enterprise decision-making is similar to how many now use ChatGPT: not to make decisions for us, but to test ideas, weigh pros and cons, reduce uncertainty, while remaining responsible for the outcome.

The behavior is similar; only the decision support layer 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 might arise?
• 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 rarely 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 personnel capable of safely deploying them.

Take an online betting platform example. With the rise of prediction markets, crypto “salespeople” (like fiat onboarding service providers) might see online sports betting platforms as natural enterprise clients. But to do so, they must first 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, onboarding service providers realize their clients aren’t the engineering or business teams wanting access to crypto liquidity, but legal, compliance, and finance teams concerned with existing betting licenses and fiat business risks.

The simplest solution is to early identify the decision-makers clearly. Don’t be afraid to ask your product supporters (those who like your product) how they would pitch 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 ready-made answers and a clear benefit/risk framework for stakeholders. By asking questions, you’ll learn who to tailor your pitch for and how to find a seemingly safe, reassuring “yes.”

Consulting firms

Often, before reaching enterprise buyers, new technologies pass through an intermediary layer: consulting firms, system integrators, auditors, and other third parties. They often play a key role in translating and legitimizing new tech. Whether you like it or not, they are gatekeepers. They use familiar frameworks and collaboration models to turn new solutions into familiar concepts, reducing uncertainty into actionable advice.

Founders often feel frustrated or skeptical, thinking consulting firms slow down progress, add unnecessary bureaucracy, or influence decisions for their own benefit. They are right! But 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, don’t assume that just because a project has “blockchain” in its name, it can bypass this decision-making system.

This pattern has influenced enterprise decision-making for decades. Even if you sell blockchain solutions, this logic persists. Our experience with Fortune 500 companies, large banks, and asset managers repeatedly shows: ignoring this layer can lead to strategic mistakes.

Deloitte’s partnership with Digital Asset is a prime example: by working 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 makes deployment more straightforward and credible.

Don’t use the same pitch for everyone

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

Details matter. Two large banks may look similar on the surface, but their systems, constraints, and internal 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 definitions. Without tailored messaging, it’s hard for organizations to believe your solution will fit perfectly.

Another serious mistake is the “start over” mentality. In crypto, founders often envision a completely new future: replacing legacy systems entirely with newer, decentralized tech to usher in a new era. But enterprises rarely do this. Existing infrastructure is deeply embedded in workflows, compliance, vendor contracts, reporting systems, and countless touchpoints with stakeholders. Starting from scratch not only disrupts daily operations but also introduces significant risks.

The broader the scope of change, the more internal stakeholders hesitate to approve: the bigger the decision, the larger the decision-making coalition.

Successful cases we’ve seen involve founders first adapting to the current enterprise environment, rather than demanding clients conform to their ideal vision. When designing entry points, it’s crucial to integrate with existing 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 operating model; it simply extended it on-chain.

Once your solution passes procurement and is officially deployed, pursuing larger goals is still very much possible.

Enterprises hedge their bets; you want to be the “right” hedge

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

Large enterprises 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 projects without touching core systems. This approach preserves options and limits exposure.

But for founders, there’s a subtle trap: being selected doesn’t mean being adopted. Many crypto companies are just one of several options for enterprise testing; pilots are fine, but scaling isn’t necessary.

The real goal is to be the “most likely to succeed” hedge. Achieving this requires not only technological advantage but also professionalism.

Why expertise beats purity

In these markets, clarity, predictability, and credibility often outweigh pure innovation: technical superiority alone rarely wins. That’s why expertise is critical—it reduces uncertainty.

By expertise, we mean designing and presenting products with full awareness of institutional realities (legal constraints, governance processes, existing systems) and operating within those frameworks. Following established practices signals that the product is governable, auditable, and controllable. Whether or not this aligns with blockchain or crypto ideals, enterprises see it this way.

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

Obsessing over ideological purity—whether “decentralization,” “minimal trust,” or other crypto principles—rarely convinces institutions bound by law, regulation, and reputation. Expecting enterprises to fully embrace a “complete vision” in one go is overly ambitious.

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

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 co-designs dedicated “Zones” for specific scenarios like payments, settlements, and capital markets with key partners.

The architecture, team collaboration willingness, and LayerZero’s brand all help reduce concerns from large traditional financial institutions. These factors have led firms like Citadel, DTCC, and ICE to become partners.

Founders often interpret enterprise resistance as mere conservatism, bureaucracy, or lack of vision. Sometimes that’s true, but often there’s another reason: most institutions aren’t irrational—they aim 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 but the one that best fits existing enterprise realities.

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

Enterprise transformation rarely happens overnight. Looking back at the 2010s “digital transformation”: despite the technology existing for years, most large companies still modernize core systems gradually, often spending huge sums on consulting. Large-scale digital transformation is a step-by-step process, achieved through controlled integration and expansion based on mature use cases, not a complete overhaul overnight. That’s the reality of enterprise change.

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