A new economic model is emerging where AI and crypto converge, transforming how value is created and distributed.
AI Is Becoming Specialized, Not Generalized. Forget one-size-fits-all AI. The future is in niche, fine-tuned models trained on proprietary data for specific tasks like DeFi optimization and on-chain security, making generic models like ChatGPT look like a blunt instrument.
Your Wallet Is Your Paycheck. Crypto wallets are becoming the interface for a new data economy. Users will transition from being unpaid data sources to active contributors who get rewarded with tokens for training specialized AI models.
Redefine AGI from Consciousness to Commerce. Forget Turing tests. The real benchmark for AGI is its ability to automate ~95% of white-collar work. The biggest missing piece isn't reasoning, but the capacity for continuous, on-the-job learning.
Prepare for an Economic Singularity. Post-AGI growth won't be an incremental bump; it will be an explosive shift to 20%+ annual growth, driven by infinitely scalable AI labor. The bottleneck won't be human demand but the ambitions of the agents controlling the AI.
The AGI Race Is More Industrial Revolution than Cold War. AGI is not a single bomb but a transformative process. The key risk isn't one nation nuking another, but advanced AIs playing nations against each other, much like the East India Company did in India.
Decentralize R&D for Efficiency. Using token-incentivized networks like Bittensor radically cuts costs and accelerates the initial drug discovery phase by tapping a competitive, global talent pool.
Go Upstream for Bigger Wins. Targeting root "behavioral" causes of disease instead of just symptoms creates drugs with multi-condition applications, unlocking massive, previously unseen market potential.
Innovate on Existing Rails. The fastest path to impact is by building on proven systems. Focusing on small molecules and using industry-standard validation partners creates a practical bridge between the worlds of crypto and traditional pharma.
Stagflation is Here: The Fed is poised to cut rates into rising inflation, an unorthodox move that signals how boxed-in monetary policy has become.
The Two-Tiered Economy is Real: Capital is flowing to the "productive frontiers" of AI and tech, while legacy industries and the un-invested class get crushed. Policy is exacerbating this divide.
Be Tactical, but Bet on the Ponzi: Expect a choppy August as euphoria cools. The long-term game, however, remains the same: bet on the assets that benefit from a global flight out of failing fiat and into productive, scarce technologies.
Crypto Is a Niche, Not a Foundation. AI builders are actively scrubbing crypto references from their branding to close enterprise deals. The market has decided: for now, crypto’s role is a payment rail, not the core agent stack.
Bet on Native Protocols, Not Browsers. Browser-based agents are a dead end. The future belongs to agent-native protocols like MCP that enable efficient, bidirectional communication, mirroring the shift from mobile web to native apps.
The AI Race Is a Power Race. The real bottleneck for AGI isn't just chips; it's energy. China's massive infrastructure build-out poses a strategic challenge to the West, which is betting on innovation in nuclear to keep pace. The future of AI may be decided by who can build power plants the fastest.
Energy is the New Scarcity. The race for AI supremacy is a race for power. Platforms like Akash that efficiently harness distributed, underutilized energy offer the only scalable alternative to the centralized model's impending energy crisis.
The Tech is Maturing Rapidly. Asynchronous training and ZK-proofs (championed by projects like Jensen) are making permissionless global compute networks a reality. The performance gap with centralized systems is closing fast.
The Mainstream is Buying In. A confluence of academic acceptance (at conferences like ICML) and favorable government policy (the White House's pro-open-source stance) is creating powerful tailwinds. The narrative has shifted from if decentralized AI is possible to how it will be implemented.
RLVR is the New SOTA for Solvable Problems: For tasks with clear right answers (code, math), RLVR is the state-of-the-art training method. The community is focused on scaling it, while RLHF remains the domain of fuzzy, human-preference problems.
The Future is Search-Driven: GPT-4o’s heavy reliance on search is not a bug; it’s a feature. The hardest problem is no longer giving models tools, but training them to learn when to use them.
Agents Need More Than Skills: The next leap in AI requires training for strategy, abstraction, and calibration. The goal is an AI that doesn’t just answer questions but efficiently plans its own work without wasting compute.
China's Open-Source Models are Winning on Price & Performance. Chinese models offer ~90% of the intelligence of top US proprietary models for a fraction of the cost, driving massive global adoption and threatening to commoditize the model layer. An American open-source champion is desperately needed to compete.
The "Cost is No Object" Compute Buildout is Reshaping the Market. A handful of private companies are spending at a loss to capture market share, fueled by VC. This creates a "sport of kings" dynamic that public companies can't match and makes pick-and-shovel players like Nvidia the biggest winners.
The US Tariff Strategy is Working. Contrary to consensus, the administration's tariff gambit has secured favorable trade deals with the EU and Japan, generating hundreds of billions in revenue without causing significant consumer inflation, and setting the stage for a major renegotiation with China.
Biology is the ultimate API for AI. The most impactful AI will be fed not just digital data but real-world biological signals. Companies are building the infrastructure to bring a user's biology online, turning abstract health data into a constant, actionable feed.
Engagement metrics are being rewritten. Forget Daily Active Users. The new model is "intense, intentional engagement" during periods of need. Growth is a function of trust and real-world impact, where the best champions are users who have been genuinely helped.
AI's role is augmentation, not automation. The goal isn't to replace doctors or therapists but to empower them. By translating noise into signal, AI lets human experts skip the data-sifting and focus on what they do best: solving problems.
Treasury Tactics: The "treasury company" model is the new "low float, high FDV" game, but relies on continued premium valuations and favorable debt markets; watch out for stress when debt matures.
Sui's Pragmatism: Sui’s handling of the Cetus hack signals that newer chains may prioritize decisive action and recovery over decentralization purity in crises, a trend likely to continue.
Solana's Evolution: Solana’s major consensus upgrade, developed by former critics, showcases a pragmatic, engineering-first approach focused on performance and validator accessibility, potentially strengthening its L1 position.
Crypto Delivers Utility: Stablecoins move trillions monthly, proving crypto's real-world value beyond speculation for fast, cheap global payments.
AI Rewrites Web Economics: AI's direct-answer capability breaks the old ad-traffic model. Crypto offers tools to build the new economic "covenant" required.
Bet on Category Kings: Tech markets are "winner-take-all." Focus on the dominant player in any credible category, especially those led by founders with unique, "earned secrets."
Build Real, Not Just Rallies: Prioritize long-term, sustainable businesses with tangible revenue models over chasing fleeting crypto trends.
Utility Tokens Trump Speculation: Design tokens to solve core project problems or incentivize user behavior, not merely for market hype.
Solana's Next Wave: Infrastructure for Reality: Leverage crypto as a backend for innovative solutions to real-world problems, targeting broader, non-crypto native audiences.
Trust is Quantifiable: AI investors can build dynamic trust scores by systematically paper-trading community signals, effectively rewarding proven alpha generators.
Beyond Wallet Snooping: "Social copy wallet" systems can unearth expert insights without needing direct access to individual wallet addresses, thus broadening the discoverable talent pool.
Community as a Vetted Oracle: The collective intelligence of crypto communities, when filtered through a performance-based trust layer, can power sophisticated AI investment decisions.
ETH: Trade the Chart, Doubt the Core. Ethereum’s technicals may offer a trading setup, but deep-seated skepticism about its fundamental delivery persists.
Worldcoin Warning: The massive FDV and emission schedule for Worldcoin scream "sell pressure," making it a risky long-term hold despite any hype.
Invest with Edge: Focus on revenue-generating altcoins and areas you understand; it's okay to miss out on trades where you lack a clear advantage.
Fund Smarter, Not Harder: Tau's SNS tokens let Bittensor subnets raise capital by tokenizing a slice of future emissions, not their core alpha tokens, sidestepping immediate sell pressure.
DTA Means Business: The Dynamic TAO model is a crucible, compelling Bittensor subnets to graduate from emission-chasers to product-driven, revenue-focused ventures.
Unlocking Subnet Investing: SNS tokens, via LayerZero, promise to simplify access to subnet investments, potentially onboarding a wave of new capital and users to the Bittensor ecosystem from other chains.
