Written by: Pyrs Carvolth, Christian Crowley, a16z
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 results rarely match the technological 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: they started in public chains and are now painfully shifting toward enterprise solutions. 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.
So, 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 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 minimizing downside risk.
Why? Because 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 tech—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 or company-level investments are involved, 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,” but more by “what is unlikely to fail.” This explains why many “better” technologies struggle to gain traction. The hurdle isn’t technical superiority but whether using the technology makes the decision-maker’s job 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 solely by technical conviction; organizational dynamics matter more.
In large organizations, decisions focus less on benefits and more on 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 require ongoing validation and solid justification. Engaging reputable third parties provides external endorsement, distributes responsibility, and offers credible backing when decisions are questioned later. Most Fortune 500 companies operate this way, with substantial consulting budgets 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 Make Decisions?
Enterprise 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 across organizations; the 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 fit with existing systems?
- How do I explain this to executives, regulators, or the board?
Therefore, for truly innovative 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.
For example, consider online gambling platforms. With the rise of prediction markets, crypto “salespeople” (like onboarding service providers) might see online sports betting platforms as natural enterprise clients. But to do so, you must understand that the regulatory frameworks for sports betting differ from prediction markets, including licensing in different states. Knowing that state regulators have varying attitudes toward crypto, payment service providers realize their clients aren’t just the engineering or business teams wanting access to crypto liquidity, but 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 hesitate to ask your product advocates (those who like your product) how they plan to 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 clear benefits and risk frameworks, so stakeholders have ready-made answers. Asking questions reveals who needs to be convinced and helps craft a seemingly safe, reassuring “consent” path.
The Role of Consulting Firms
Often, new technologies reach enterprise buyers through intermediaries: consulting firms, system integrators, auditors, and other third parties. They 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 and offering practical advice.
Founders often feel frustrated or suspicious, thinking consulting firms slow down progress, add unnecessary steps, or influence decisions for their own benefit. That’s true! But the reality is, 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 just adding “blockchain” to a project will bypass this decision-making layer.
This pattern has influenced enterprise decisions for decades. Even if you sell a blockchain solution, this logic remains. Our experience with Fortune 500 companies, major banks, and asset managers repeatedly shows that ignoring this layer can lead to strategic mistakes.
A typical example is Deloitte’s partnership with Digital Asset: by collaborating with a trusted consulting firm like Deloitte, Digital Asset’s blockchain infrastructure is rebranded into familiar enterprise language—governance, risk, compliance. For institutional buyers, the involvement of a credible third party validates the technology and clarifies the path to implementation.
Don’t Use the Same Pitch for Everyone
Because decision-makers are highly sensitive to their own needs—especially downside risks—you must tailor your pitch: don’t use the same sales deck, PPT, or framework for every potential client.
Details matter. Two large banks may look 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 pitch signals you haven’t taken the time to understand their specific project definition. Without tailored messaging, organizations will find it hard to believe your solution fits their needs.
Another serious mistake is the “start from scratch” approach. In crypto, founders often envision a completely new future: replacing legacy systems entirely with decentralized, better technology. But in reality, traditional infrastructure is deeply embedded in workflows, 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 grows: bigger decisions require larger coalitions.
Successful cases we’ve seen involve founders first adapting to the client’s current environment, rather than demanding the client conform to an ideal. When designing entry points, aim 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 the solution passes procurement and is officially deployed, pursuing bigger goals later is entirely feasible.
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.
Large enterprises don’t put all their eggs in emerging infrastructure; instead, they run multiple experiments simultaneously. They allocate small budgets to several vendors, test various solutions within innovation departments, or run pilots without touching core systems. This approach preserves options and limits exposure.
But for founders, there’s a subtle trap: being chosen 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 technical advantages but also professionalism.
Why Expertise Trumps Purity
In such markets, clarity, predictability, and credibility often outweigh pure innovation: technical superiority alone rarely wins. That’s why professionalism is critical—it reduces uncertainty.
By professionalism, 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 the ideals of decentralization or crypto ethos, enterprises view technology deployment through this lens.
This isn’t resistance to change; it’s a rational response to organizational incentives.
Obsessing over ideological purity—whether “decentralization,” “trustlessness,” or other crypto principles—rarely convinces institutions bound by law, regulation, and reputation. Expecting enterprises to fully embrace a “complete vision” overnight is unrealistic and hasty.
Of course, there are examples of breakthrough tech combined with ideological purity. LayerZero’s recent launch of the Zero chain aims to address scalability and interoperability for enterprise adoption while maintaining core principles of decentralization and permissionless innovation.
But Zero’s real innovation isn’t just architecture; it’s organizational design. Instead of building a one-size-fits-all network and expecting enterprises to adapt, it collaborates with key partners to create dedicated “Zones” for specific use cases like payments, settlement, and capital markets.
Zero’s architecture, team commitment to these applications, and LayerZero’s brand credibility have significantly reduced concerns among large traditional financial institutions. As a result, firms like Citadel, DTCC, and ICE have announced partnerships.
Founders often interpret enterprise resistance as mere conservatism, bureaucracy, or shortsightedness. Sometimes that’s true, but often there’s another reason: most institutions are rational actors focused on operational stability. 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 the enterprise’s current state.
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 modernized 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 proven use cases—not through overnight replacement. That’s the reality of enterprise change.
Successful founders are those who understand how to implement in phases, not those demanding a complete vision from the start.
