8 Stocks I'd Buy if I Were Starting a Tech Portfolio From Scratch Today

Eight AI-focused tech names are recommended as a core portfolio: Nvidia, AMD, Broadcom, Micron, TSMC, Alphabet, Meta, and ServiceNow — ServiceNow is noted as producing strong 20%+ growth. Nvidia is framed as the dominant AI infrastructure player (inference/agentic AI), AMD as a leader in data-center CPUs and rising GPU revenue, Broadcom for custom ASIC/TPU chips and data-center networking, Micron for high-bandwidth memory with emerging long-term contracts, and TSMC for near-monopoly advanced chip manufacturing and pricing power. Alphabet and Meta are highlighted for monetizing AI across search, cloud/TPUs and ads, supporting continued secular revenue upside across semiconductors, memory, cloud and SaaS.

Analysis

The immediate winners from AI’s next phase are not just GPU makers but the upstream and adjacent enablers that determine unit economics — HBM providers, ASIC foundry partners, network ASICs, and systems integrators that lower total cost of ownership for hyperscalers. That shifts profit pools: modest ASP compression in inference hardware can be more than offset by much higher unit volumes and recurring software/servicing revenue; companies that capture the software-to-hardware attach (or long-term HBM contracts) will compound free cash flow faster than pure silicon sellers.

Key second-order competitive dynamics to watch are customer concentration and lead time asymmetries. Hyperscalers increasingly demand vertically integrated stacks (chip+package+software), which raises switching costs for suppliers they commit to; conversely, long lead-times for advanced nodes and HBM create short-to-medium term supply tightness that can sustain pricing but also makes these names sensitive to a single large customer pause. Policy/export risk and a sudden architectural pivot to tiny, cheap LPUs or analog accelerators are low-probability but high-impact tail risks that would materially reprice winners within quarters.

From a timing perspective, tradeable catalysts cluster: near-term (0–6 months) = quarterly guides and large hyperscaler procurement announcements; medium (6–18 months) = TSMC/ASIC capacity expansions and finalized long-term HBM contracts; long (18–36 months) = enterprise adoption of agentic AI and software monetization cadence. The consensus is heavy on a few marquee names — that concentration makes a rotation into ASIC, memory-contracted suppliers, and workflow/software operators a high-conviction, asymmetric way to play the same structural trend with differentiated risk profiles.

Key Decisions for Investors

• Long AVGO (12–24 months): Buy shares or 12–18 month call spread (e.g., buy 12mo call, sell higher strike) to express ASIC/custom-chip uptake. Risk/reward ~ +30% upside if hyperscaler ASIC adoption accelerates; downside ~ -15% on deal slippage or macro slowdown. Set stop at -12% from entry to protect against rapid multiple compression.
• Long MU on a pullback or on announcement of multi-year HBM contracts (6–18 months): exposure via shares or 9–12 month calls. Reward: mean reversion to higher multiple given recurring HBM revenue; risk: memory cycle swing could inflict 30–40% downside. Size as tactical overweight (5–7% portfolio) with trailing stops.
• Pair trade — Long TSM / Short INTC (9–18 months): 1:1 notional to express manufacturing moat vs legacy CPU/accelerator execution risk. Target spread capture ~30% if TSMC sustains pricing and Intel misses its accelerator ramp; cut losses if spread moves adversely by 15%. Use options collars to cap downside.
• Rotational trade into software orchestration: Long NOW (12–18 months) selectively on continued ARR acceleration or positive AI-control announcements; size smaller due to valuation risk. If NOW fails to convert pilot AI projects into monetizable modules within 2 quarters, switch to owning Broadcom/TSM exposure instead.