Jordi Visser

• Consider trimming Amazon (AMZN), Microsoft (MSFT), Alphabet (GOOGL/GOOG), and Meta (META), as heavy AI spending and financing needs could pressure valuations; shift some exposure toward AI infrastructure and agentic-computing beneficiaries.
• The clearest stock-level bullish view is Micron (MU): the speaker increased his position on expectations of strong memory demand through 2030, while acknowledging near-term technical and market risks.
• Maintain selective exposure to semiconductors and optical infrastructure; the speaker likes Corning (GLW) and remains cautiously constructive on SMH if its 200-day moving average holds.
• Eli Lilly (LLY) is a favored long-term longevity investment, supported by strong revenue growth and expanding GLP-1 demand; the speaker sees potential for it to become the S&P 500’s largest stock before 2030.
• The speaker favors Bitcoin (BTC) over the Nasdaq-100 (NDX) as a relative-value trade, but offers no price target and notes that crypto remains sensitive to rates and technology-market swings.

• Track crude oil and the 10-year Treasury yield as near-term context for Bitcoin (BTC) and SMH; the discussion links rising oil and yields to shifts in market positioning.
• The speaker views recent technology-sector pressure as positioning-driven, not evidence of an AI bubble, but provides no specific buy/sell recommendation or price target for BTC, SMH, or AI stocks.

• Consider gradually adding to AI compute and semiconductor exposure, including NVDA and MU, as a long-term theme; expect continued volatility, and treat the cited $1,500 MU scenario as highly speculative.
• Add Eli Lilly (LLY) to a healthcare watchlist for its AI-enabled drug-discovery efforts, while recognizing that biotech investments can be volatile.
• For Bitcoin (BTC), watch the $100,000 level as a potential catalyst, not a guaranteed target, and weigh adoption prospects against cybersecurity and upgrade risks.
• Monitor widening credit spreads and weakening corporate profits or margins; these would challenge the view that the sell-off is mainly a positioning reset.

• Favor diversified equities for long-term investing, but expect continued volatility while crowded trades and hedge-fund deleveraging unwind; the transcript gives no reliable end date.
• For AI exposure, consider NVIDIA (NVDA) or Micron (MU) as companies supported by reported compute and memory demand, while recognizing that crowded positioning can pressure prices even when business fundamentals are strong.
• If choosing between CoreWeave (CRWV) equity and bonds, the speaker prefers its bonds, citing financing risks for the stock; no bond target or specific entry price is provided.
• Treat Bitcoin (BTC) cautiously in the near term: the speaker expects it to remain range-bound until hedge-fund stress stabilizes and mentions a possible drift toward “75,” without specifying units or timing.

• Prioritize AI infrastructure, especially NVDA and MU, as the clearest way to participate in rising demand for compute and memory; the thesis depends on AI demand continuing to outpace supply.
• Watch LITE for its reported orders extending through 2029, and VST and CEG for potential exposure to data-center power demand; assess valuation and execution risks before investing.
• Favor selective exposure to technology and energy over rate-sensitive businesses, while keeping in mind that higher yields and market corrections remain significant risks.

• Consider NVIDIA (NVDA) for continued AI-compute demand and Micron (MU) for rising memory needs; track revenue growth, supply conditions, and management commentary, as both can be volatile.
• For less obvious AI-infrastructure exposure, watch Marvell (MRVL) and Rogers (ROG), whose opportunities are tied to efficient computing, data-center power, and heat management.
• Ethereum (ETH) and NEAR offer high-risk exposure to potential AI-agent payments and tokenized finance, but adoption remains uncertain and no price targets or timelines were provided.
• Treat Bitcoin (BTC), Ethereum, and Solana (SOL) as speculative: the speaker sees potential institutional interest but warns that sharp reversals are possible.

• Favor AI infrastructure and compute exposure, including Intel (INTC) and AMD (AMD), but avoid overpaying as valuations may compress.
• Consider a diversified crypto allocation around the AI-agent and tokenization theme; the speaker favors the broader crypto market over Bitcoin (BTC) alone, but gave no price targets.
• For a bearish trade, the speaker specifically suggested shorting weak private-credit or private-equity names, including Blue Owl (OWL); no target or timing was provided.
• Prefer large-cap technology over small caps for now, while monitoring credit spreads, jobless claims, and profit margins for signs that higher rates are causing broader stress.

Rotate new capital into primary layer-1 blockchains like Bitcoin (BTC), Ethereum (ETH), and Solana (SOL), where a recent crypto index breakout indicates a near-term 15% upside potential for BTC.

Add equity exposure to market infrastructure providers like Coinbase (COIN) and Robinhood (HOOD) to capture expanding fee revenue as 24/7 trading and tokenized assets gain regulatory traction.

Supplement digital asset allocations with specialized AI and privacy tokens, specifically Bittensor (TAO), Near Protocol (NEAR), and Zcash (ZEC), to capture the growth of autonomous AI agent transactions.

Invest in Eli Lilly (LLY) as a prime healthcare beneficiary that is leveraging AI agent networks to accelerate scientific discovery and monetize intellectual property.

Maintain core holdings in mega-cap tech (MAG-7) and semiconductor leaders like NVIDIA (NVDA) and Marvell Technology (MRVL) for rate-insulated stability, while directing fresh investment capital toward software and crypto rails.

Buy Robinhood (HOOD) to capitalize on a projected 31% upside driven by rapid on-chain fee growth and its expansion into AI-powered digital finance.

Build core positions in Ethereum (ETH) as the primary settlement layer for the emerging tokenized economy, utilizing Arbitrum (ARB) for higher-upside exposure to growing Layer-2 transaction volume.

Hold key AI compute leaders like NVIDIA (NVDA) and Microsoft (MSFT) to benefit from sustained hardware demand and a 22% rise in enterprise chip rental rates that support strong corporate cash flows.

Maintain broad market exposure through the S&P 500 (SPY), as exponential AI productivity and corporate margin expansion continue to outweigh short-term interest rate and inflation volatility.

Consider establishing a 5% to 10% allocation in Bitcoin (BTC) to capitalize on an expected momentum breakout above $82,000, while setting stop-losses if it falls below its 200-day moving average. Complement this with high-beta layer-1 networks like Ethereum (ETH) and Solana (SOL), or use Robinhood Markets (HOOD) for stock-based exposure to the growing real-world asset tokenization trend. Anchor your core artificial intelligence allocation in NVIDIA (NVDA), which continues to show market leadership near all-time highs. Accumulate key hardware and semiconductor suppliers like Dell Technologies (DELL), Micron Technology (MU), and Marvell Technology (MRVL) on price dips over a 12-month investment horizon. Maintain broad equity exposure through the S&P 500 (SPX) and Nasdaq (QQQ), using recent market consolidation as a buying opportunity backed by strong corporate earnings growth.

Accumulate Bitcoin (BTC) on pullbacks toward the $58,000 support level to establish a favorable entry point in the premier digital store of value.

Maintain core holdings in Ethereum (ETH) to benefit from institutional real-world asset tokenization, while utilizing Solana (SOL) for high-upside exposure to high-speed settlement and autonomous AI microtransactions.

Buy dips in NVIDIA (NVDA) during valuation pullbacks rather than chasing price spikes, taking advantage of its dominant AI compute moat and projected 70% revenue growth.

Rotate capital into enterprise AI software leaders like Palantir Technologies (PLTR) as market momentum broadens from hardware chips into operational enterprise applications.

Gain exposure to the tokenized finance super-cycle by investing in digital infrastructure platforms like Coinbase (COIN) that enable 24/7 capital distribution and tokenized private credit yields.

Maintain long positions in Bitcoin (BTC) and Ethereum (ETH) as core macroeconomic hedges following their technical breakouts above their 200-day moving averages, using MicroStrategy (MSTR) for amplified stock-based upside. Buy Marvell Technology (MRVL) as a top-conviction AI hardware play offering projected 3x to 4x multi-year upside as custom silicon and cloud networking demand expands. Accumulate Eli Lilly (LLY) as a core growth stock over a five-year horizon, backed by robust obesity treatment cash flows and AI-powered drug development that could expand industry valuation multiples from 12x–15x toward 20x–25x. Overweight Silver Miners (SIL) ahead of physical Silver (SLV) as an undervalued, low-multiple hedge against fiat currency inflation. Take tactical positions in high-performance crypto infrastructure operators such as Bitdeer (BTDR), Riot Platforms (RIOT), Hut 8 (HUT), and Iris Energy (IREN) to capture combined exposure to digital assets and AI-driven data center demand.

Capitalize on recent market panics by buying high-conviction semiconductor stocks like Micron Technology ($MU**)** below $900, with a medium-to-long-term price target of $1,500 to $1,600.

Target supply-chain infrastructure leaders like Corning ($GLW**)**, which recently hit its 200-day moving average and secured massive partnerships including a $6 billion deal with Meta.

Focus your investments on major hyperscalers—such as Amazon, Google, and Microsoft—that boast a combined $1.7 trillion backlog driven by insatiable AI compute demand.

Maintain disciplined position sizes and use phased entry strategies, as structural market volatility will remain elevated above historical averages.

Capitalize on structural artificial intelligence demand by ignoring short-term free cash flow dips and buying market leaders in cloud and semiconductor infrastructure. Accumulate shares of Marvell Technology (MRVL) to capture upcoming earnings growth from optical and photonic infrastructure upgrades. Consider a tactical entry in Applied Optoelectronics (AOI) following its recent market correction to benefit from data networking trends. Prepare for mainstream institutional integration by establishing or adding to positions in major cryptocurrencies like Bitcoin (BTC) and Ethereum (ETH) ahead of late-year catalysts. Finally, monitor retail liquidity shifts by tracking sentiment indicators like Dogecoin (DOGE) alongside your core technology and crypto allocations.

Investors should view the current tech volatility as a "speed crash" rather than a bear market, using the 40% correction in momentum to scale into high-conviction semiconductor names. Micron (MU) is a top-tier buy as rising DRAM prices and structural memory shortages drive significant upward earnings revisions. Avoid legacy software providers like Salesforce (CRM) and Adobe (ADBE), as their downward-sloping 200-day moving averages signal they are being disrupted by the shift to AI agents. Ethereum (ETH) represents the purest play on the "agentic" revolution, as AI agents will likely use its smart-contract infrastructure and tokens as native currency. Expect a major breakout for Bitcoin (BTC) and the broader crypto sector in late Q3 or Q4 as global regulatory shifts and institutional adoption provide long-term tailwinds.

Investors should prioritize NVIDIA (NVDA) as a high-conviction entry point, as it is currently trading at its lowest valuation in a decade while holding key technical support. Focus on "scarcity" assets like Micron (MU), SK Hynix, and Samsung (SMSN) to capitalize on persistent global memory shortages expected to last through 2030. Apple (AAPL) and Meta (META) are primary plays for the next wave of growth in consumer AI agents, which is projected to drive a massive 24x increase in data consumption. In the digital asset space, Bitcoin (BTC) remains a "no-brainer" long-term hold as it transitions into the foundational layer for AI-driven commerce and global tokenization. For a tactical retail sentiment indicator, watch for Dogecoin (DOGE) to break above its 200-day moving average to signal the return of broader market participation.

Investors should use current pullbacks to the 50-day moving average as entry points for high-quality AI infrastructure stocks like NVIDIA (NVDA) and Marvell (MRVL). The "easy money" phase has passed for memory leaders like Micron (MU), so focus should shift toward the AI application layer, specifically Healthcare and Insurance companies like Eli Lilly (LLY) and Chubb (CB). Technical indicators suggest a potential bottom for Bitcoin (BTC), making it a high-conviction rotation play alongside Gold and Silver to hedge against U.S. debt debasement. Monitor regional banks via the KRE ticker, as AI-driven automation is expected to trigger a wave of acquisitions and margin improvements within the sector. Despite hawkish market fears, the deflationary impact of AI productivity suggests the Federal Reserve may be less aggressive with rate hikes than currently anticipated.

Investors should rotate away from expensive Mag-7 hyperscalers like Microsoft (MSFT) and Alphabet (GOOGL) toward the "receivers" of AI capital, such as Micron (MU) and Vertiv (VRT). Eli Lilly (LLY) is a high-conviction long-term play, positioned to potentially become the world’s largest company as it leverages AI for drug discovery and dominates the GLP-1 market. While Micron (MU) remains a strategic asset in the AI memory shortage, focus on its transition to subscription-like revenue models rather than expecting rapid 10x gains. Avoid "catching the falling knife" in Bitcoin (BTC) until it clears its 200-day moving average, though you should prepare for a 2025 surge driven by AI agents using crypto for autonomous transactions. For broader exposure, look to Small Caps (IWM) and industrial names like Caterpillar (CAT), which are benefiting from a market rotation that favors infrastructure and domestic growth over high-multiple tech.