Compensation Innovation: The traditional compensation playbook for engineers is outdated. New models that directly reward AI-augmented output will attract top talent and drive efficiency.
Builder/Investor Note: Founders should re-evaluate their incentive structures. Investors should seek companies experimenting with these models, as they may achieve outsized productivity.
The "So What?": The productivity gap between AI-augmented and non-AI-augmented engineers will widen. Companies that adapt their incentives will capture disproportionate value in the next 6-12 months.
Strategic Shift: Successful AI integration means identifying and solving *your* organization's specific SDLC bottlenecks, not just boosting code completion.
Builder/Investor Note: Prioritize psychological safety and invest in AI skill development. For builders, this means dedicated learning time; for investors, look for companies that do this well.
The "So What?": The next 6-12 months will separate organizations that merely *adopt* AI from those that *master* its strategic application and measurement, driving real competitive advantage.
Strategic Implication: AI integration is a company-wide transformation, not a feature. Organizations must re-architect processes, tools, and culture to compete.
Builder/Investor Note: Prioritize internal tooling that democratizes AI experimentation. Look for companies establishing "model behavior" as a distinct, cross-functional discipline.
The "So What?": The next 6-12 months will reward builders who bake AI security and user control into product design from day one, recognizing that technical mitigations alone are insufficient.
AI's real-world impact will accelerate in 2026, particularly in "conservative" professional services and fundamental sciences, despite market volatility.
Builders should focus on truly novel consumer agent experiences and niche robotics applications, while investors should eye AI IPOs with caution and consider energy efficiency plays.
The next 6-12 months will clarify the geopolitical AI race and expose the true infrastructure bottlenecks, shaping the industry's long-term trajectory.
Strategic Shift: The fintech market is moving from "digitizing everything" to "optimizing everything with AI." This means a focus on efficiency, personalization, and solving deep-seated financial problems.
Builder/Investor Note: Opportunities abound in B2B AI software for financial institutions and in consumer fintechs that prioritize "excellence" over mere access. However, the escalating AI fraud threat demands significant investment in defensive technologies.
The "So What?": Over the next 6-12 months, expect a surge in AI-powered financial products and services, but also a corresponding increase in the sophistication and volume of financial fraud. The battle for trust and security will define the winners.
Strategic Shift: The market will increasingly demand AI models evaluated on human-centric metrics, not just technical benchmarks. Companies prioritizing user experience and safety will gain a competitive edge.
Builder/Investor Note: Investigate companies developing or utilizing advanced, demographically representative human evaluation frameworks. These are crucial for building defensible, user-aligned AI products.
The "So What?": Over the next 6-12 months, expect a growing focus on AI safety, ethical alignment, and nuanced human preference data. The "Wild West" of AI evaluation is ending, paving the way for more robust, trustworthy systems.
Strategic Implication: The next frontier in AI is agentic, and progress hinges on fundamental pre-training innovation, not just post-training optimizations.
Builder/Investor Note: Focus on teams with deep experience in scaling and debugging large models, as this is a high-capital, high-risk endeavor. Builders should prioritize developing new benchmarks for agentic capabilities.
The "So What?": The industry needs to move beyond next-token prediction and static benchmarks to unlock truly capable, self-correcting AI agents in the next 6-12 months.
Shift in AI Development: The focus moves from syntax-aware code generation to execution-aware reasoning, enabling more robust and intelligent code agents.
Builder/Investor Note: Prioritize tools and platforms that support explicit execution modeling and highly asynchronous, high-throughput RL training for agentic systems.
The "So What?": AI that can simulate complex systems internally will drastically reduce development and testing costs, accelerating innovation in software and distributed systems over the next 6-12 months.
Strategic Shift: AI-driven kernel generation is not replacing human genius but augmenting it, allowing experts to focus on novel breakthroughs while AI automates the application of known optimizations across a complex hardware landscape.
Builder/Investor Note: Focus on robust validation and hardware-in-the-loop systems. Claims of "AI inventing new algorithms" in this domain are premature. The real value is in automating the "bag of tricks" for heterogeneous compute.
The "So What?": This technology is critical for scaling agentic AI workloads. Expect significant investment in tools that abstract hardware complexity and enable efficient, automated optimization, driving down the cost of AI inference in the next 6-12 months.
The erosion of the American dream, fueled by inflationary policies and monopolistic capitalism, is driving a political shift towards candidates who advocate for transparent, common-sense economic policies and modern regulatory clarity for emerging technologies like crypto.
Support political candidates who champion clear, updated regulatory frameworks for digital assets and advocate for increased market competition across industries.
The fight for crypto clarity is now intertwined with broader economic and political reform. Understanding this intersection is crucial for investors and builders navigating a landscape where policy decisions directly impact market viability and individual prosperity over the next 6-12 months.
Politically influenced central banking is returning, making monetary policy an electoral tool. Fed decisions will reflect political priorities, potentially leading to aggressive rate cuts.
Re-evaluate portfolio sensitivity to political intervention. Position for lower long-term rates, but prepare for increased market volatility.
The incoming Fed chair signals a re-alignment of monetary policy with executive branch goals. Expect policy to prioritize affordability and electoral success.
The US is pivoting from a QE-fueled, government-led economy to a "free market" model under the new Fed Chair, Kevin Warsh. This means a potential reduction in the Fed's balance sheet (QT) and lower rates without yield curve control (YCC), leading to decreased US dollar liquidity.
Adopt a phased, data-driven allocation strategy. Michael Nato recommends an 80% cash position, deploying first into Bitcoin (65% target) at macro lows (around 65K-58K BTC, MVRV < 1, 200WMA touch), then into high-conviction core assets (20%), long-term holds (10%), and finally "hot sauce" (5%) during wealth creation.
The current "wealth destruction" phase, while painful, presents a rare opportunity to accumulate assets at generational lows, provided one understands the macro shifts and adheres to a disciplined, multi-stage deployment plan.
The financial world is splitting into two parallel systems: opaque TradFi and transparent onchain finance. Value is migrating to platforms that can simplify and distribute onchain financial products globally.
Invest in or build applications that prioritize mobile-native experiences, abstract away crypto complexities (like gas fees), and offer tangible real-world utility for onchain assets.
The future of finance is onchain, and "super apps" like Jupiter are building the necessary infrastructure and user experiences to onboard the next billion users.
Crypto's initial broad vision has narrowed to specific financial use cases, while AI and traditional markets capture broader attention. This means builders must focus on tangible value and investors on proven models.
Identify projects with novel token distribution models (like Cap's stablecoin airdrop) or those building consumer-friendly applications within new ecosystems (like Mega ETH) that address past tokenomics failures.
The industry is past its naive, speculative phase. Success hinges on practical applications, robust tokenomics, and competing with traditional finance, not just abstract ideals.
The Macro Shift: From unbridled, community-driven idealism to a pragmatic, business-focused approach. Early crypto imagined a world where "everything is a thing on Ethereum," but reality has narrowed its primary use cases to finance and trading, forcing a re-evaluation of tokenomics and community models. This shift is also driven by AI capturing mindshare and traditional finance co-opting blockchain tech.
The Tactical Edge: Re-evaluate token distribution models. Instead of relying on inflationary yield farming that creates sell pressure, explore innovative approaches like Cap's "stable drop" (airdropping stablecoins, then inviting participation in a token sale) to align incentives and attract long-term holders. Focus on building real products with defensible business models, even if they lean more "business" than "protocol."
