There are several reasons this could be accurate: Everyone knows the $SPCX valuation is egregious that they haven't yet booked a profit, and that true data centers in space won't be until the 2030s (I'm speaking mega-scale). So look at Coreweave: they grew revenue in the triple digits last quarter, but the stock is flat. Why? Because the company is heavily in debt and is burning cash every quarter. So, it has an extreme valuation, but it grows extremely fast; it has a lot of debt and burns cash every quarter; doesn't that sound like $SPCX?

The first lockup period begins 70 days out. Just remember super investor Peter Lynch's great advice: "If you aren't willing to own a stock for ten years, don't even think about owning it for ten minutes."

$DDOG the Moat DDOG's platform is sticky, with a net revenue retention rate of 120% and continued adoption of its multi-product offerings. It has beaten consensus estimates in every reported quarter. The multi-product compounding is key: once a team instruments one layer (infra, logs, APM), the switching cost to rip it out grows dramatically. Analysts pointed to DDOG's purpose-built storage and query engines — including the Monocle metrics database and Husky event engine — as difficult to replicate, pushing back on concerns that open-source telemetry tools could commoditize the platform. The Agentic AI Kicker As of early 2026, DDOG's business model is increasingly shifting toward "Agentic AI" tiers, where customers pay for autonomous capabilities that investigate and resolve issues without human intervention — the Bits AI SRE Agent and Security Analyst — marking the transition from observability (knowing what's wrong) to actionability (fixing what's wrong). This is a second monetization layer on top of the core telemetry business. Here's why, within my framework specifically, $DDOG works over $SNOW: 1. Moat is harder to replicate. SNOW faces direct, credible substitution from Databricks, BigQuery, and Redshift — all competing for the same enterprise data budget. DDOG's Monocle Husky proprietary engines are not easily open-sourced away, and the multi-product lock-in compounds over time. 2. Margin structure is superior. 81% gross margins vs. ~65% means DDOG earns dramatically more on each dollar of revenue at scale. SNOW's consumption model is compute-heavy by nature — that ceiling doesn't go away. 3. AI complexity is a one-way ratchet. Every agentic AI deployment, every LLM in production, every new model version creates more demand for observability, not less. SNOW's tailwind (bigger models need more storage) is real, but DDOG's tailwind (more AI in production needs more monitoring) is structural and accelerating. 4. The Databricks overhang is real for SNOW. Once Databricks IPOs — likely H2 2026 — institutions will directly compare SNOW vs. Databricks with full public financials. Databricks is growing at 65% vs. SNOW's 30% and is already eating SNOW's ML pipeline customers. That's a valuation-compression risk on the horizon for SNOW specifically.

Also bought $WYFI and $VPG for the week. VPG sells sensors for humanoid robotics and physical AI, which is already benefiting from AI Capex and retail enthusiasm. $WYFI is a purchase Leopold made in Q1 and is one of the smallest neoclouds retrofitting data centers to serve compute, electricity, and tokens