24 Predictions for Crypto and AI in 2026

比推Опубликовано 2025-12-31Обновлено 2025-12-31

Введение

The author, Benedic, founder of Meridian, presents 24 predictions for 2026 as a public commitment to test his judgment. He will delete the article if more than 6 predictions are proven wrong upon review next year. He discloses holdings in some mentioned assets and expresses interest in angel investment. Key predictions are categorized: **Mainstream Assets:** Quantum computing will challenge Bitcoin; Ethereum's relevance and price will decline; Solana will lead in synthetic assets and retain retail users; Monad will succeed as a Layer 1; Binance new coins will underperform stocks. **Application Layer:** Hyperliquid will gain market share in perpetuals, but overall growth slows; prediction markets won't expand beyond sports/politics; on-chain tokenized crypto options will hit $10B volume; Base will abandon SocialFi. **Infrastructure:** Robinhood's L2 will stagnate; Base will drop its L2 focus; privacy middleware integrated with embedded wallets will gain popularity; Coinbase or Stripe will solve fiat on-ramps for stablecoins. **Solana Ecosystem:** Protocol-integrated block building will advance; routing aggregators and DEXs/market makers will vertically integrate; tokenized stocks will scale significantly outside the US. **AI (Crypto):** AI assistants will become default in apps, a key differentiator; AI-written smart contracts will lower development barriers, spurring mechanism design innovation; ChatGPT will become more modular with a popular crypto plugin. **AI (Non-C...

Author: Benedic, Founder of Meridian

Original Title: Predictions for 2026


Preface

This is my first attempt at writing 24 predictions for 2026, aiming to hold myself accountable through public commitment. If the accuracy rate falls below 18 items (i.e., more than 6 errors) upon verification next year, I will delete this article. At that time, I will evaluate each item one by one and publish the results.

I hold positions in some of the assets and companies mentioned in this article. If you are building in these directions, I look forward to discussing the possibility of angel investment with you.

Mainstream Assets

- The quantum computing narrative will become a serious challenge for Bitcoin in 2026, as its community is too decentralized to propose credible solutions.

- Ethereum's market attention will continue its multi-year decline and begin to show substantial price weakness.

- Solana will shed its meme coin chain label and become the leading platform for real-world synthetic asset trading, while maintaining the largest retail user base.

- Monad will establish itself as an influential Layer 1, with its year-end price significantly higher than the Coinbase ICO price. Apart from Tempo, other execution layers launched in 2025 or early 2026 will fail to gain lasting market appeal or attention.

- The strategy of buying a basket of new Binance coins will significantly underperform the strategy of buying stocks.

Application Layer

- Hyperliquid will capture market share from centralized perpetual contract platforms, but the overall growth rate of the BTC/ETH/altcoin perpetual contract market will be relatively slow.

- Prediction markets will fail to expand significantly beyond sports and major political events, gradually fading from the mainstream view.

- Some form of on-chain tokenized crypto options product will reach a trading volume of $10 billion.

- Base will abandon SocialFi and revert to being an ordinary wallet.

Infrastructure

- Robinhood's Layer 2 will make little progress due to reduced demand for regulatory arbitrage in the current political environment.

- Base will abandon its Layer 2 positioning.

- Some privacy middleware located below the application layer and vertically integrated with embedded wallets will become quite popular.

- Coinbase or Stripe will completely solve the fiat on-ramp issue for stablecoins in third-party applications.

Solana Ecosystem

- Block building will take a significant step toward protocol integration. Jito and Harmonic will adjust their strategies and both successfully launch new business lines beyond block building.

- We will see vertical integration between routing aggregators and decentralized exchanges/professional market makers.

- Tokenized stocks will gain a foothold and achieve significant scale in markets outside the U.S.

AI (Crypto Field)

- AI assistants will significantly improve and become the default configuration in most mainstream consumer applications. By the end of the year, a key differentiator among applications will be the quality of their AI assistants.

- Multiple smart contracts almost entirely written and tested by Claude will gain massive attention. Twelve months from now, the barrier to writing smart contracts will feel 10 times lower than it does now, sparking a renaissance in mechanism design.

- ChatGPT will become more modular and agentic (via plugins), and one crypto use case within it will rapidly gain popularity.

AI (Non-Crypto Field)

- Anthropic will surpass OpenAI in revenue and become the highest-valued AI lab.

- Google will solve the post-training problem, and Gemini Flash will become the most popular model for global non-coding agent tasks.

- Nearly all AI companies selling to enterprises will realize they are competing with each other. This collapse of the imagination space will make competition exceptionally fierce.

- Meta will launch a new consumer AI product that tops the App Store download charts.

- (Low probability but I believe its value is relatively underestimated compared to consensus) A new paradigm beyond "giving LLMs detailed prompts and a series of specialized tools" will emerge and greatly shake up which startups in the field have value.

Original link:https://www.bitpush.news/articles/7599494

Связанные с этим вопросы

QWhat is the author's main prediction regarding Bitcoin in 2026?

AThe author predicts that the quantum computing narrative will become a serious challenge for Bitcoin in 2026, as its community is too decentralized to propose a credible response.

QAccording to the author, which blockchain will become the dominant platform for real-world synthetic asset trading while retaining the largest retail user base?

AThe author predicts that Solana will shed its meme coin chain label and become the dominant platform for real-world synthetic asset trading, while continuing to have the largest retail user base.

QWhat significant development does the author foresee for AI assistants in consumer applications by the end of 2026?

AThe author predicts that AI assistants will be significantly improved and become the default configuration in most mainstream consumer applications, with the quality of the AI assistant becoming a key differentiator between applications by the end of the year.

QWhich company does the author predict will surpass OpenAI in revenue and become the highest-valued AI lab?

AThe author predicts that Anthropic will surpass OpenAI in revenue and become the highest-valued AI lab.

QWhat is the author's prediction about the future of Base's Layer 2 and its SocialFi focus?

AThe author predicts that Base will abandon its Layer 2 positioning and also abandon its SocialFi focus, reverting to being a regular wallet.

Похожее

How to Do Research Well: Deliberately Practice the Real Skills That Matter

No one truly teaches you how to do research. You're often given a desk, a pre-selected problem, and vague instructions to "create something new." Consequently, many people reverse-engineer the job based on visible outputs—papers, posts, announcements—learning only how to *appear* like a researcher rather than how to *become* one. True research capability is built from stacking small, trainable skills, nearly all of which can be developed through deliberate practice. **Pick Your Own Problem:** Most researchers absorb problems from advisors or trends, lacking the underlying reasoning. Choosing a problem you genuinely care about, as John Schulman advises, leads to original work. Develop "taste" like a muscle: predict experiment outcomes, guess paper results from methods, and track which findings remain important over time. **Upgrade Your Inputs:** Relying on shared reading lists (arXiv hot lists, filtered group chats) leads to unoriginal conclusions. Undervalued old literature often holds crucial insights (e.g., MoE, LSTM, backpropagation). Richard Sutton's "The Bitter Lesson" or Claude Shannon's 1952 talk on creative thinking are more predictive than lengthy modern surveys. Breadth matters as much as depth: draw from neuroscience, mechanism design, hardware knowledge, and honest statistics. Read papers directly, especially appendices and limitations sections. **Write Everything Down:** As Paul Graham noted, writing exposes flaws in seemingly mature ideas. Writing is the cheapest defense against self-deception. Following Feynman's principle, Darwin programmatically wrote down facts contradicting his theory to combat memory bias. Maintain a detailed log of hypotheses, setups, predictions, results, and updated understandings. Reviewing past logs fosters essential humility.

marsbit56 мин. назад

How to Do Research Well: Deliberately Practice the Real Skills That Matter

marsbit56 мин. назад

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

On June 15th, shares of Zhipu AI surged dramatically on the Hong Kong stock market, peaking at a 47.6% gain before closing 32.82% higher. This sharp increase was directly triggered by two recent industry events. On June 12th, Anthropic announced it was suspending global access to its latest flagship models, Claude Fable 5 and Claude Mythos 5, to comply with a U.S. government export control order. The next day, Zhipu AI announced it would open access to its latest open-source flagship model, GLM-5.2, under the permissive MIT license. The Anthropic incident highlighted a critical issue beyond raw model capability: the risk of sudden, unpredictable loss of access to advanced AI models, especially for developers and enterprises deeply integrated with them. This has shifted industry and market focus toward factors like stability, sustainable access, and controllability. Zhipu's move, promoting "frontier intelligence for all," positions its openly available model as a reliable and accessible alternative. The GLM-5.2 model emphasizes "Long Horizon Task" capabilities with a 1M context window, targeting complex, multi-step coding and engineering workflows where maintaining context is crucial. Analysts note this event exposes the risk of dependency on closed-source models subject to single jurisdictional controls, potentially accelerating a shift toward domestic base models and localized deployments. The market's reaction signals a new valuation dimension in AI: providers who can offer stable, long-term, and sustainably accessible AI capabilities are gaining strategic importance.

marsbit1 ч. назад

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

marsbit1 ч. назад

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

In May 2026, Alipay announced over 300 million AI payment transactions. Shortly after, WeChat opened its mini-programs for AI integration, sparking controversy by requiring developer source code access. This highlights their diverging approaches to AI integration. Alipay is testing "Project Treasure," an optional AI-native interface replacing traditional app grids with a conversational window. Users can command complex tasks (e.g., "book a ride and order coffee") handled end-to-end by AI. This shift follows an abandoned standalone AI app, focusing instead on enhancing its existing user base. For unmodified mini-programs, Alipay's AI uses "screen-reading" to simulate user interactions, bypassing the need for developer overhaul. It also introduced "Token Pay" for micro-transactions and "AI Wallets" for autonomous agent spending. WeChat, prioritizing its core social function, is taking an embedded approach. Its AI agent will operate within existing contexts like group chats and official accounts, assisting without a separate interface. To enable this, WeChat offers developers two paths: granting source code access for direct AI control ("Automatic Mode") or manually encapsulating services into standardized "Skills." Both place significant burden on developers. Key differences emerge in handling legacy services: WeChat demands developer cooperation (code or labor), while Alipay's screen-reading offers immediate, if potentially less stable, compatibility. Alipay's 3 billion AI transactions demonstrate user acceptance of AI-driven commercial actions. The divergent strategies may reshape mini-program ecosystems—Alipay passively "AI-fying" services, WeChat potentially favoring resource-rich developers—and set competing technical standards. Ultimately, the competition centers on where users entrust the command to "help me get things done."

marsbit1 ч. назад

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片