
by @iltb_podcast
5 videos
The AI trade is shifting toward a one-year innovation cycle in compute and the critical physical infrastructure required to support it. Bottlenecks in fiber and specialized manufacturing are creating high-conviction opportunities as data center demand scales.
Capital is rotating away from legacy per-seat SaaS models toward usage-based AI platforms that automate complex workflows. Enterprise budgets are increasingly diverted from traditional applications into AI tokens and agentic software.
The autonomous vehicle (AV) sector is maturing into a physical AI play where platform utilization and neutral partnerships determine the winners. Free cash flow is being weaponized to consolidate the full travel and delivery stack.
AI-generated summary. Not investment advice. Learn more.

Investors should shift focus toward Private Equity and Alternative Credit, as these markets now offer the same scale as public markets but with less volatility and longer growth windows. Prioritize Energy, Infrastructure, and Real Estate assets that provide structured credit with equity upside, such as warrants, to capture higher yields of 7–10%. Be extremely cautious with long-duration tech bonds, as AI disruption creates significant "staying power" risk for legacy software giants like Salesforce (CRM) over a 30-year horizon. Maintain high levels of Liquidity to act as a strategic "hub" for opportunities, rather than attempting to forecast specific macroeconomic or geopolitical outcomes. Remain overweight on U.S. Equities to capitalize on "American Exceptionalism" driven by energy abundance and a structural culture of permissionless innovation.

Investors should prioritize Vertical AI platforms like Clay and Rogo AI that focus on "auditable" workflows and specialized data integration rather than generic chatbots. High-conviction opportunities lie in "infrastructure winners" like WorkOS and Vanta, which are essential for scaling enterprise AI leaders such as OpenAI, Anthropic, and Perplexity. Look for companies utilizing usage-based pricing models, as these better align investor returns with actual customer productivity and AI-driven output. In the fintech space, Ridgeline and Ramp are key assets to watch as they replace fragmented legacy tech stacks with unified, automated platforms for asset management and corporate expenses. When evaluating early-stage startups, favor founders who demonstrate "counter-positioning" by building complex, high-skill tools for experts rather than simplified products for the mass market.

Investors should prioritize Anthropic as a top-tier AI play, focusing on its dominance in the $500 billion AI-assisted coding market and its transition toward autonomous "agentic" software. NVIDIA (NVDA) remains a high-conviction core holding as it shifts to 1-year innovation cycles, maintaining a structural lead amidst a multi-year global compute shortage. To capture the "unsexy" infrastructure boom, look to Celestica (CLS) for its Google TPU partnership and Corning (GLW) for the massive fiber optic demand required by new data centers. Alphabet (GOOGL) offers a safer entry into the AI arms race due to its vertical integration with internal TPU chips and superior data-handling capabilities via Gemini. Conversely, reduce exposure to traditional SaaS and "per-seat" software providers like Salesforce (CRM), as enterprise budgets are being diverted away from legacy applications toward AI tokens and hardware.

Investors should consider Uber Technologies (UBER) as it transitions into a "physical AI" powerhouse, leveraging over $10 billion in free cash flow to dominate the autonomous vehicle (AV) and delivery sectors. By positioning itself as a neutral "go-to-market" partner for over 30 developers like Waymo, Lucid, and NVIDIA, UBER captures a 30% utilization advantage that makes it essential to the entire AV ecosystem. Monitor the growth of Uber One memberships and cross-platform bookings, as these high-retention tools are driving structural profitability over single-line competitors like DoorDash. For long-term exposure to the delivery drone and robotics shift, keep a 5-to-10-year outlook on specialized players like Joby Aviation and Zipline as battery density improves. Focus on UBER's expansion into the full travel stack, including Hotels and Trains, which aims to capture higher-margin consumer spending beyond simple ride-sharing.

Focus on the AI Stack by prioritizing infrastructure and semiconductors, specifically NVIDIA (NVDA), which remains attractive at approximately 15x 2027 projected earnings. Investors should look for "liquidity gaps" in corporate spinoffs, as institutional selling often creates undervalued entry points before management incentives drive the stock higher. In international markets, target Japan to capitalize on government-led corporate governance reforms that are forcing companies to unlock shareholder value. For stable, high-quality growth, look toward "gold standard" operators like Danaher (DHR) or niche value plays like Casey’s General Stores (CASY). Avoid localized European equities due to regulatory headwinds, instead favoring global champions like ASML or shifting to structured credit when equity volatility rises.
The 12 most-discussed assets across Invest Like The Best’s content on Kazuha (out of 34 total).
Aggregate of all sentiment-scored insights from Invest Like The Best in the last 30 days.
Kazuha indexes 5 posts from Invest Like The Best, with AI-extracted insights covering 34 distinct assets (stocks, ETFs, cryptocurrencies, and other investable assets).
Invest Like The Best's most-discussed assets on Kazuha are NVDA, GOOGL, CRM, META, SONY. See the "Top assets covered" section above for the full breakdown with sentiment.
Mostly bullish. In the last 30 days, Invest Like The Best had 33 bullish, 5 bearish, and 0 neutral takes across all assets they discussed (per AI-extracted sentiment scoring on Kazuha).
Invest Like The Best's publicly available content (podcast episodes, YouTube videos, or X/Twitter posts) is transcribed and analyzed by an LLM that extracts the assets discussed and the speaker's sentiment toward each one. Each insight links back to the original source.