Part 1 – Introducing the Problem

The Overlooked Impact of Programmable Money: How Smart Contracts Can Reshape Economic Models in Blockchain Ecosystems

The Invisible Friction in Crypto’s Monetary Logic

Despite the crypto ecosystem’s obsessive focus on token design, yield mechanics, and liquidity optimization, an underexplored problem sits at the core of smart contract-based economies: the underutilization of programmable money to create autonomous, adaptive economic models. Most smart contracts merely act as static execution engines—premised on basic conditional flows. What’s missing is a deeper integration between economic state and monetary policy — a dynamic framework where money doesn’t just respond to protocol inputs but autonomously governs itself based on the holistic state of the ecosystem.

We’re not talking about central bank analogs or oracle-fed interest tweaks. The issue is more exclusionary: smart contracts rarely manage money programmatically at the systemic level. They react, but don’t reason.

A Historical Oversight

If you trace DeFi’s history from the first Ethereum-based tokens to contemporary yield-farming ecosystems, smart contracts have primarily functioned as vaults, routers, and liquidity managers. Even DAOs, widely regarded as innovation incubators, tend to rely on off-chain governance to enforce value allocation mechanisms — rather than embedding adaptive logic directly into their monetary operations. The result is a patchwork of siloed logic: monetary behavior isn’t encoded through smart contracts as much as it’s monitored, tweaked, and socialized externally.

This legacy design bleeds inefficiencies into tokenomics. Without embedded smart logic to adjust supply, modify incentives, or rebalance capital flow autonomously, most protocols either under-respond to changes in market dynamics or overdepend on manual governance interventions — both of which introduce latency, and more worryingly, systemic fragility.

Why It Remains Overlooked

The core issue is architectural: current smart contract platforms don’t make deep economic programmability intuitive. Solidity contracts aren’t inherently built to consider system-wide state variables like macro liquidity, actor entropy, or volatility-dimensional capital flow. There’s also a psychological trap — builders tend to treat “monetary governance” as a social layer function, rather than a runtime artifact of code.

Interestingly, ecosystems like Radix are attempting to challenge this default. Through asset-oriented programming and built-in economic templates, they may pave the way for protocols to encode programmable monetary logic at a native scale. Readers interested in how architectures differ can explore https://bestdapps.com/blogs/news/unlocking-radix-the-future-of-defi-tokenomics.

The question is no longer whether money can be programmable — Turing completeness is a solved problem. The real question is: why aren’t we programming it to behave more intelligently? As we'll explore next, the limitations aren't purely technical. They're rooted in design paralysis, incentive misalignment, and underdeveloped behavioral tooling.

Part 2 – Exploring Potential Solutions

Smart Contract Architectures Under Pressure: Evaluating Emerging Solutions to Economic Coordination

The rise of programmable money promised a decentralized alternative to rigid economic models, but most smart contract platforms still incentivize static behaviors through overly simplified logic. To address this, new approaches are being explored to improve coordination, capital efficiency, and economic flexibility within blockchain-native environments.

Composable Account Abstractions

Account abstraction, particularly as conceptualized in ERC-4337, offers adaptive transaction execution models that decouple wallet logic from protocol-level execution. In theory, this allows for more expressive economic conditions — such as social recovery, dynamic gas fees, or conditional participation based on external data. While powerful, these abstractions often run into issues with complexity and implementation overhead. They are also inherently limited by the base layer’s design constraints — as seen in Ethereum’s opcodes or Solana’s runtime serialization.

Radix, with its asset-oriented smart contract architecture and native component model, attempts to solve this bottleneck by integrating programmability and composability at the protocol layer rather than relying on layered abstractions. For a deeper look, read https://bestdapps.com/blogs/news/a-deepdive-into-radix.

State Channels and Optimistic Execution

Off-chain coordination models like state channels allow low-latency, high-throughput interaction without congesting the underlying settlement layer. Though theoretically elegant, in practice they require synchronous availability of participants and add dispute-resolution overhead. Optimistic rollups attempt to bridge that gap by assuming honest behavior and requiring only fraud proofs if cheating is suspected. This works well in transactional contexts but struggles in programmable incentive systems where intent, not just result, matters.

Projects like Arbitrum and Optimism have shown promise, but their success revolves around minimizing trust assumptions — a still-evolving domain in dispute game design.

Zero-Knowledge Enabled Logic

Introducing privacy-preserving computation into smart contracts via zero-knowledge proofs theoretically enables conditional transfers, reputation-based participation, and selective disclosure without sacrificing decentralization. zk-SNARK-based solutions (e.g., Aleo, Zexe) aim to build full-stack private smart contracting platforms. However, trusted setup, limited expressiveness, and developer tooling remain primary bottlenecks. Moreover, the economics of proof generation are still resource-heavy and pose UX challenges.

Behavior-Driven Incentive Structures

Incentive structures that respond to behavioral metrics rather than static staked value are also gaining traction. Projects are experimenting with reputation-weighted governance, usage-based token distribution, and adaptable bonding curves. While this introduces dynamic capital allocation, it also opens the door to manipulation, sybil attacks, and emergent gameplay patterns — especially when behavior becomes predictable and gamified.

One key issue across all innovations is testing robustness in real actor environments — where incentives often produce unintended outcomes, not just inefficiencies.

Part 3 will investigate how some ecosystems are attempting to incorporate these innovations in production, and whether they hold up beyond testnet theory.

Part 3 – Real-World Implementations

Real-World Trials in Programmable Money: Smart Contracts in Action

Several blockchain startups and networks have attempted to operationalize programmable money through smart contracts, each with varying outcomes shaped as much by technical limitations as by tokenomics design.

Radix offers one of the more ambitious case studies. With its Scrypto programming language and the Radix Engine, the project sidesteps Ethereum’s EVM constraints by introducing asset-oriented smart contracts. However, despite technical elegance, Radix has faced friction in developer adoption. Object-oriented paradigms reduce bug surfaces, but without compatibility layers for Solidity, onboarding remains a hurdle. Smart contract builders from Ethereum ecosystems often find Radix’s environment too novel, creating a bottleneck in DeFi dApp growth. For more on Radix’s unique architectural philosophy, see A Deepdive into Radix.

Metis attempted to use Layer-2 scaling to ease programmable interactions but faced early criticism around transaction finality. Their DAC (Decentralized Autonomous Company) model aimed to automate payroll, auditing, and income distribution—all via smart contracts. The problem wasn’t feasibility; it was predictability. Gas spikes on Ethereum base layer intermittently impaired the deterministic behavior needed. Despite infrastructure-level improvements like Sequencer decentralization, deterministic automation across variable cost layers remains an open challenge.

Centrifuge managed more alignment between real-world outcomes and DeFi modeling. Its Tinlake platform tokenizes real-world assets—mainly invoices—and channels liquidity via programmable vaults. While successful in abstracting yield distribution logic through smart contracts, integrating off-chain legal entities proved complex. Notarial workflows needed to synchronize with on-chain triggers, causing occasional contract-enforcement mismatches. Identity-oriented upgrades and oracles mitigated some issues, but the long tail of off-chain complexity still haunts these hybrid models.

In contrast, projects like Arweave and Ocean Protocol pivoted purely toward data economies rather than financial flows. Their challenges were less about logic encoding and more about permanence and retrieval latency. While data monetization contracts exist, the infrequent invocation and asymmetric incentives (e.g., hoarding data vs. query fees) hinder real-time programmability.

The broader lesson? Programmable money doesn’t guarantee economic automation unless gas volatility, identity bridging, and external dispute resolution are tightly integrated or abstracted. Even the most expressive smart contract logic can choke without predictable runtime conditions or financial primitives.

Projects like Radix, even with deterministic execution and composability via blueprints, illustrate that technical readiness does not always net ecosystem traction. Integrating with legacy systems—be it legal enforcement or fiat rails—introduces friction that code can't resolve alone.

Next, the series will dissect how these real-world outcomes shape the long-term evolution of programmable money across Layer-1, Layer-2, and cross-chain ecosystems.

Part 4 – Future Evolution & Long-Term Implications

The Future of Programmable Money: Evolutionary Pathways and Infrastructure Synergies

The trajectory of programmable money—and the smart contracts that power it—is heading toward a multi-layered convergence of scalability, interoperability, and composability. And as it evolves, the friction points that have historically limited adoption—like gas inefficiency, oracles as single points of failure, and rigid governance models—are under active rearchitecture.

One of the key shaping forces lies in modular blockchain architecture. Instead of monolithic chains handling consensus, execution, and data availability as a bundled stack, networks are trending toward disaggregated roles. This opens the door for execution environments purpose-built for smart contracts to integrate with scalable data layers and customizable consensus protocols. Protocols optimizing for this separation, such as Radix, are positioning themselves to tackle both atomic composability and scalability simultaneously. For deeper understanding of such layered approaches, explore radix-xrd-revolutionizing-blockchain-scalability.

Anticipated advancements in parallel execution—especially via asynchronous VM models and fee-markets optimized for throughput rather than congestion—could decouple logical interdependencies from performance bottlenecks. This is directly relevant for complex DeFi protocols, where composability has often traded off with latency and finality guarantees. In these environments, auto-rebalancing smart contracts and protocol-native fee allocators are becoming primitives—not just add-ons.

Another major axis of development involves state sharding with verification abstraction. Instead of forcing every node to run every contract, zero-knowledge proofs are increasingly used to offload computational burden while ensuring verifiability. As ZK-Rollups and Validiums approach production maturity, their intersection with programmable money will enable localized state changes at global verifiability cost levels.

The friction, however, is non-trivial. Ethereum’s EVM architecture is inherently resistant to some forms of parallelism without rethinking its opcode design. Legacy compatibility constraints act as latency anchors. Meanwhile, cross-chain composability attempts often hit the wall of trust assumptions due to centralized relayers or unidirectional messaging limitations.

But composability is no longer restricted to intra-chain dynamics. With protocols pioneering intent-centric models and universal liquidity layers, value flows could become chain-agnostic. The key enabler? Robust identity infrastructure and modular governance wrappers that adapt to use-case-specific consensus assumptions and fallback mechanisms.

Smart contract wallets are also expected to mature into programmable agents—handling compliance-aware assets, delegated execution rights, and dynamic fee sponsorship. This shift demands a serious rethink of signer-permission architectures and automated transaction relays.

As these foundational layers recalibrate, the emerging question is: who decides the evolution of programmable money? Part 5 will excavate governance mechanisms, analyzing how decentralization, community tooling, and protocol control impact the trajectory of smart contract standards.

Part 5 – Governance & Decentralization Challenges

Governance and Decentralization in Smart Contract Economies: Navigating Fragile Power Structures

Governance in programmable money ecosystems remains a structural fault line that directly affects economic resilience and security. While smart contracts promise automation and trustlessness, they do not eliminate human coordination challenges—they merely shift the complexity into governance frameworks that, if poorly executed, invite attack vectors and systemic imbalance.

Centralized governance allows for fast decisions and deterministic upgrades but at the expense of resilience and censorship resistance. Typically governed by a foundation or core team, these systems can act swiftly in emergencies but risk regulatory capture, decision-making opacity, and community alienation. Worse, centralized admin keys can function as implicit kill-switches for otherwise “decentralized” smart contracts, undermining trust in economic finality.

In contrast, decentralized governance models—DAOs, council-based voting, or token-weighted consensus—prioritize inclusivity and resistance to capture. However, implementation is messy. Token-based voting often leads to plutocratic control, where a small number of holders dominate decision-making. This vulnerability incentivizes vote buying, Sybil resistance circumvention, and flash loan exploits that can manipulate governance outcomes. These are not theoretical—they’ve occurred repeatedly in DAO attacks, sparking response protocols that blur the line between decentralization and ad hoc centralization.

True decentralization also introduces coordination overhead. Protocols with high decision latency or unclear quorum definitions face stagnation. When governance is too passive or fragmented, critical updates—like patching logic flaws in smart contracts—can be dangerously delayed. The rigidity of on-chain policy, once praised for predictability, can backfire when urgent, nuanced human judgment is required. This paradox of governance fragility persists regardless of the L1 network in question.

Hybrid models, such as delegated governance and time-locked multisigs, offer some mitigation by blending technocratic oversight with wider community feedback. However, these tend to entrench existing political hierarchies and remain vulnerable to collusion. Formalizing off-chain checks and balances—like conflict resolution courts or structured appeals—is still a largely experimental domain.

Projects like Radix have taken steps toward more robust delegation mechanics and deterministic state sharding, but governance itself remains an evolving challenge. For deeper context, readers can explore Navigating Governance in the Radix Ecosystem.

Anyone designing smart contract-based economies must recognize: governance is not a bolt-on feature—it is the protocol. Solidity may encode rules, but incentives shape behaviors, and governance enforces agenda. Misalign these forces, and the system ossifies or self-harms.

In Part 6, we’ll explore how scalability solutions interface with these governance dynamics, and what engineering trade-offs are required to bring programmable money to layer-1 throughput at global scale.

Part 6 – Scalability & Engineering Trade-Offs

Blockchain Scalability Bottlenecks: Smart Contracts at the Edge of Performance

Implementing programmable money at scale reveals deep friction between core blockchain objectives—decentralization, security, and performance. Smart contracts are inherently resource-intensive, demanding consensus verification, deterministic execution, and persistent storage across a decentralized network. These design requirements make scaling a meaningful challenge.

The trilemma is unavoidable. Ethereum’s prioritization of decentralization and composability introduces latency and cost, especially under network congestion. Despite gas optimizations and EVM upgrades, deterministic execution across globally distributed nodes ultimately limits transaction throughput. Ethereum Layer-2 solutions like rollups offer improved throughput but introduce their own state management complexity, and sequencer centralization remains an unresolved point of failure.

In contrast, high-throughput Layer-1 chains like Solana trade decentralization for speed, leveraging Proof-of-History and a tightly coordinated validator set. While impressive in raw TPS, this approach concentrates control and raises concerns about censorship resistance and validator liveness. Solana’s entire architecture is optimized for performant dApps with minimal tolerance for slower, low-bandwidth nodes.

Meanwhile, architectures like Radix bring an innovative model—sharding by design rather than afterthought. Radix’s Cerberus protocol separates consensus from execution across shards, enabling global atomic composability without a central coordinator or complex cross-shard messaging. However, while Radix tackles the scalability trilemma with first-principles architecture, its ability to consistently deliver under adversarial network conditions still remains largely untested in production. For a more detailed examination of these design trade-offs, refer to Radix XRD: Revolutionizing Blockchain Scalability.

Consensus choice amplifies engineering constraints. Nakamoto-based PoW (as in Bitcoin) has security but is slow and energy-intensive. BFT-based PoS systems (e.g., Cosmos, Polkadot) promise faster execution but suffer from validator coordination issues and potential liveness failure under asynchrony.

Implicit in all this is the engineering problem of upgradeability. Unlike traditional software platforms, smart contract platforms must maintain immutable historical state. Contracts deployed today must remain compatible with the execution environment years into the future. This locks developers into rigid primitives—unless versioning and modular execution become native to the chain, a feature only a handful of chains have seriously explored.

As programmable money matures, we'll continue to see fragmentation in scalability strategies. No single architecture solves the trilemma fully. Every engineering path comes with layered trade-offs in composability, trust minimization, and validator participation. Choosing a chain to deploy serious financial logic isn't just a matter of speed—it’s a choice of what you're willing to sacrifice.

Next, we’ll dissect how regulatory coordination (or lack thereof) creates high-risk blind spots for developers and users relying on smart contract automation.

Part 7 – Regulatory & Compliance Risks

Smart Contract Regulation in the Wild: Cross-Jurisdictional Challenges for Programmable Money

As smart contracts become foundational to DeFi ecosystems, their legal and regulatory ambiguity across jurisdictions threatens the integrity and scalability of programmable money adoption. The crux of the issue lies in the automation of financial logic without centralized custodianship—who is held liable when code executes unlawfully or causes systemic damage? In traditional finance, liability is mediated by legal intermediaries. In contrast, decentralized environments challenge established notions of accountability.

Many smart contracts operate across jurisdictional borders, yet legal enforceability is rooted in the physical locality of actors. This dissonance creates enforcement vacuums. For instance, a lending protocol might be developed by a DAO in one country, operated by nodes across several continents, and utilized by users globally—introducing legal exposure in all involved jurisdictions. This distributed structure complicates compliance with Know Your Customer (KYC), Anti-Money Laundering (AML), and consumer protection laws.

Furthermore, these problems aren’t hypothetical. The SEC and other regional regulators have already taken aggressive enforcement actions against entities deemed to issue or trade unregistered securities via smart contracts. Their stance on decentralized protocols remains clear: "decentralized" in architecture does not imply immunity from centralized accountability. In EU zones, the Markets in Crypto Assets (MiCA) regulation introduces additional friction by requiring full transparency of smart contract function and upgradeability, effectively disincentivizing immutable codebases.

Adding to the complexity are regulations tied to data privacy, such as GDPR. Under this framework, the immutability of smart contracts may clash with the “right to be forgotten”—a fundamental data subject right. Developers implementing logic reliant on user-specific metadata are particularly vulnerable here.

Tax obligations are another grey area. Jurisdictions like the U.S. and Japan tax crypto gains as they’re realized, often via on-chain swaps facilitated entirely by smart contracts. However, the lack of reporting clarity in protocols could lead users to unknowingly commit tax fraud. This potential liability extends to front-end developers, floor governors, and even DAO members.

As more chains like Radix implement native smart contract features at the protocol level, understanding these legal nuances becomes critical. Radix (XRD): Pioneering the Future of dApps explores how design decisions influence regulatory exposure, particularly in user experience and deterministic transaction flows.

State-level interventions, meanwhile, have not always ended in policy success. The New York BitLicense, for example, inadvertently pushed developers offshore due to over-regulation. Programmable money risks a similar exodus unless frameworks adapt to decentralized realities rather than retrofitting old models onto new architectures.

Next, we will assess how the presence of programmable money—if allowed to scale under current or reformed regulatory structures—impacts macroeconomic policy, financial markets, and central banking.

Part 8 – Economic & Financial Implications

Programmable Money and the Redistribution of Economic Power in Blockchain Ecosystems

Programmable money—via smart contracts—is forcing a recalibration of traditional economic frameworks within DeFi. As protocol logic replaces intermediary roles, entire markets are being restructured, sometimes subtly, other times destructively.

In capital markets, yield primitives created by smart contracts have enabled automated, on-chain derivatives that were previously gatekept by established institutions. This has unlocked new opportunities for permissionless speculation, insurance, and structured products. For traders, this yields hyper-efficient exposure strategies. However, it also introduces parabolic tail risk—as observed in recursive lending or reflexive liquidations—driven by deterministic logic without human oversight.

Institutional capital is both drawn in and alienated. On one hand, composability allows new forms of institutional DeFi products, such as real-world asset-backed protocols or permissioned pools. On the other, the absence of finality guarantees and the reliance on oracles make these systems susceptible to manipulation. Liquidity providers (LPs), despite being early beneficiaries, are increasingly exposed to asymmetric risks due to MEV and fractured liquidity incentives.

For developers, programmability shifts focus from product-market fit to protocol-market conditions. Launching a DeFi app is no longer solely a UX challenge—it’s now a token engineering problem. Maladaptive tokenomics can sink valuable products. This is evident in ecosystems like Radix where radical changes in programming paradigms are enabling more deterministic outcomes in DeFi composition. For further analysis, see Unlocking Radix: The Future of DeFi Tokenomics.

For venture DAOs and on-chain funds, programmable escrows, vesting modules, and trustless governance mechanisms are upending how capital is deployed. While these innovations reduce custodial overhead, they simultaneously introduce governance attack vectors. Value-draining proposals, flash loan-driven governance hijacks, or miner-extractable value (MEV) attacks can create systemic risk within heavily composable ecosystems.

Moreover, as code becomes law, emergent behaviors like toxic flow arbitrage or parasitic interfaces appear. Protocols like Uniswap have faced such dynamics where front-end aggregators extract value without contributing back to the LP base—a phenomenon amplified by the robotic enforcement of smart contract terms.

Economic centralization may re-emerge under new guises. While protocols aim for decentralization, value often accrues at the application level—where a few key builders, token holders, or DAO participants wield disproportionate control over logic-modifying proposals.

Exploring how this shift reshapes social dynamics, the notion of consent in code execution, and the new forms of digital social contracts will be essential in understanding the broader consequences of programmable money.

Part 9 – Social & Philosophical Implications

Programmable Money and the Commodification of Code: Disrupting Economic Norms and Redrawing Risk Landscapes

The shift from static digital assets to programmable money introduces a profound change to capital markets. Smart contracts—atomic, self-executing code—serve not just as intermediaries but as active components in price discovery, asset management, and on-chain governance structures. Financial primitives are no longer broker-mediated; they’re automated, composable, and susceptible to subtle shifts in code logic—sometimes intentionally forked, sometimes fatally flawed.

We’re already seeing smart contracts commoditized across verticals. Developers can deploy tokenized debt auctions, streaming payments, or event-driven derivatives in minutes using frameworks like Radix’s Scrypto language. Protocols like Radix lower technical friction, expanding economic experimentation while introducing unknown forms of systemic risk. As noted in Unlocking Radix: The Future of DeFi Innovation, this opens expressive possibilities—but also inflates the economic surface area exposed to malicious exploits or uncaught logical errors.

For institutional investors, programmable money offers alpha in microseconds. Yield strategies like flash loan arbitrage or liquidity mining boost ROI, but reward only those controlling low-latency tech stacks and deep working capital. Ironically, while DeFi democratizes participation, its game-theoretic asymmetries still favor the best-capitalized players with execution edge. Value accrues faster to code literacy than fiat holdings. Without enforceable code audits or economic fail-safes, sophisticated actors may extract value from less informed participants—creating a familiar hierarchy under decentralized branding.

Retail traders operate in an unstable terrain. Revenue-generating dApps offer yield with open-source incentives, but smart contract logic is rarely scrutinized beyond audits—often outdated by protocol forks or third-party integrations. One malformed update can cascade through permissionless ecosystems. Meanwhile, large stakeholders can engage in liquidity farming and governance proposals that rewire reward schemes in their favor, leaving smaller participants with diluted token flows or slashing penalties they never agreed to vote on.

Developers themselves risk becoming collateral in speculative cycles. Their compensation often ties to volatile token emissions, yet their code becomes part of immutable financial logic. A misstep isn't just a software bug—it’s market exposure. Incentives for building responsibly are often weak compared to those for building fast.

Across stakeholder classes, programmable money amplifies both opportunity velocity and risk scalability. It incentivizes automation but externalizes edge-case liability. As a result, on-chain economies may evolve toward a state of high-frequency experimentation rather than sustainable growth.

This redefinition of money and markets invites harder questions about consensus, value, and trust. In the next section, we explore how programmable systems could shape society far beyond finance.

Part 10 – Final Conclusions & Future Outlook

The Fork Ahead: Will Programmable Money Become the Cornerstone of Blockchain Economies?

The exploration of programmable money and smart contracts has revealed both revolutionary potential and sobering limitations. At its core, the integration of autonomous, self-executing agreements challenges traditional intermediaries, unlocking vast speed, transparency, and composability. But these benefits have also exposed persistent frictions—namely, governance misalignments, rigidity in contract logic, and UX bottlenecks that continue to hinder adoption beyond crypto-native communities.

Best-case scenarios position programmable money as the financial substrate for a redefined economic model. In such a future, protocol-controlled treasuries, DAO-based revenue-sharing, and permissionless lending markets intertwine seamlessly across chains. Innovations like Radix’s asset-oriented architecture and linear scalability explored in more depth here could serve as blueprints for how infrastructure must evolve to support this future state. In this vision, smart contracts are not only efficient — they are composable economic primitives structuring the next century of digital commerce.

In contrast, the worst-case trajectory leads to a fragmented, siloed landscape. Under-governed DAOs collapse under coordination failures or token whale manipulation. Poorly audited contracts result in devastating exploits. Legal ambiguity throttles growth, while user apathy and opaque flows reinforce distrust. Without better risk abstractions and regulatory clarity, programmable money risks becoming a power user tool with minimal mainstream resonance.

Remaining questions are substantial: How do we embed dynamic governance into immutable software? Can we build smart contract templates that evolve with real-world logic rather than remain brittle snapshots? And ultimately, can financial automation reflect human intent—and account for its unpredictability?

For programmable money to transition from niche infrastructure to economic standard, several needs are non-negotiable. Human-readable contract languages, verified execution environments, audit transparency, and state-enforced backups for disputes must mature. Equally crucial is cross-chain composability that avoids liquidity obsolescence — many are focusing on this with layer-1 primitives, but none offer a comprehensive solution yet.

As the dust settles on the first decade of DeFi experimentation, programmable money stands at a crossroads. It has proven theoretical viability—now it must prove operational resilience and mass usability.

The final unanswered question remains: will programmable money become the backbone of a decentralized economy, or will it quietly fade into a web3 cautionary tale, a technological marvel that never found its product-market fit?

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