Director of WACC

[Director of WACC @DirectorOfWACC]

solar selloff is completely algo driven on THE PAST. The algos are “correctly” pricing in weaker residential demand amid higher for longer interest rates.

Roof solar is highly rate sensitive because it relies on consumers dealt with higher borrowing costs which HISTORICALLY has slowed the segments demand but…

That view completely underestimates a powerful, multi year structural tailwind with the explosive growth in electricity demand from data centers

|sorry I’m sick of the word tailwind or bottleneck from twitter FURUS as well, so I apologize for using it|

This demand is shifting the solar investment thesis toward utility scale and commercial projects, which are far less rate sensitive and benefit from direct PPAs with hyperscalers who seemingly can’t stop hiking CAPEX

OPINIONS I VALUE THAT CONFIRM MY THESIS:

Gartner projects global data center electricity consumption will rise 26% in 2026 alone, reaching 565 TWh (up from 447 TWh in 2025).

AI-optimized servers are expected to consume more power than conventional servers by 2027 and approach half of all data center power by 2030.

IEA base case: Global data center electricity use roughly doubles to 945 TWh by 2030.

Lawrence Berkeley National Lab: U.S. data centers could account for 9.5–15.3% of total U.S. electricity by 2030

Wood Mackenzie Utilities see 60 GW of new large loads data centers coming online by 2030 equivalent to 8% of current U.S. peak demand.

EIA: U.S. power demand is forecast to hit new records in 2026 and 2027, with commercial demand for Data centers overtaking residential for the first time.

Thesis confirmed through hyper scaler action:

Google, Meta, Microsoft, are actively signing large solar PPAs often hundreds of MW per deal sometimes colocated with battery storage precisely because solar + storage offers the fastest path to new, cost-competitive clean power.

Think about why $TE bought that storage company?

Beyond raw demand growth, solar stands out on the attributes that will matter most in the 2030s:

Speed to market: Utility scale solar projects can reach commercial operation in 18–24 months, versus 3-7+ years for gas plants, nuclear, or major grid upgrades.

Cost: Utility-scale solar PPA prices in key markets (ERCOT) are often in the $35 to 55/MWh range highly competitive and providing longterm price certainty that data center operators WANT

The hidden angle is the environmental profile that Trump admin doesn’t give a fuck about but will become more of a reason to be bullish further looking if we transition back to democrat US or someone with more energy logic than Trump

…Solar has near-zero operational water use and no direct greenhouse gas emissions or water pollution during generation.

Gas fired generation requires significant water for cooling and produces emissions. Data centers themselves are water-intensive for cooling , powering them with solar reduces the overall system water footprint compared to gas heavy alternatives.

As water stress intensifies in key regions, this advantage will grow in regulatory and ESG importance.

My bottom line:

This sell off appears to be disproportionately discounting the residential slowdown while under-appreciating the scale and durability of datacenter driven power demand.

AI is not a marginal use case it’s creating never before seen electricity needs that will require every scalable, lowcost, lowwater rapidly deployable resource available. Solar checks every box.

My investments to capitalize:

$TE $35 2030 PT
$RUN $50PT 2030 PT
$FSLR $525 2030 PT

With fucking care,
D-WACC

[Director of WACC @DirectorOfWACC]

@TheBronxViking woahh

[Director of WACC @DirectorOfWACC]

@elonmusk SimpMaxxing

[Director of WACC @DirectorOfWACC]

$TE just delivered a strong set of first quarter results this morning, and in my view, the numbers meaningfully de-risk the story. Revenue came in at $177.6 million well ahead of expectations, driven by solid production ramp at the G1 Dallas facility. The company posted its first-ever positive net income from continuing operations and a record Adjusted EBITDA of $9.1 million. This is the operational proof point I have been waiting to see.

My near term price target sits at $12 to $15 per share

Three things stood out to me after combing through the report and guidance:

First, G1 Dallas is now clearly past the inflection point.
Management reaffirmed guidance for 3.1–4.2 GW of production this year and indicated they’re positioned to hit the high end. In my opinion this visibility on a fully operational U.S. factory removes a major execution risk.

Second, G2 Austin Phase 1 remains on schedule for initial cell production in Q4 2026. Once that facility scales, T1 will have a clear path to the $375–$450 million run-rate EBITDA they’ve laid out for 2027, and potentially $650–$700 million at full 5 GW per site.

Those are MASSIVE numbers for a company of this size.

Third, the external backdrop is unusually favorable. Domestic content incentives, tariffs, and Section 232 developments continue to create a structural pricing advantage for U.S. made solar modules. Add in growing power demand from data centers and AI infrastructure, and T1 is a major WINNER.

From a valuation standpoint, if the company executes on the EBITDA trajectory management has outlined, a 15–25× forward EBITDA multiple is well within reason for a high growth domestic manufacturing leader. That math easily supports the bull-case targets I’ve outlined.

[Director of WACC @DirectorOfWACC]

$NRGV earnings summary and my take
Revenue 156% YoY, record $1.35 BILLION backlog (up 108%), and >80% of it is now owned & operated assets AND high-margin recurring revenue.

Assets under management >1.1 GW and they’re guiding to $180M+ annual recurring EBITDA run-rate (ahead of plan).

Just the new 100 MW AI data center deals alone should add another $65M recurring EBITDA soon.

Stock is selling off for absolutly ZERO reason.

At a conservative 10x on that EBITDA you’re already looking at $10+ per share minimum as they flip fully into cash-flowing IPP + AI power mode.
love this setup

[Director of WACC @DirectorOfWACC]

CoreWeave isn’t just another cloud. It’s the specialized “picks and shovels” for the AI gold rush — building the high-performance backbone that lets the biggest AI companies move at warp speed. The infrastructure behind tomorrow’s intelligence.

$CRWV 🚀#AI #CoreWeave #GPU

Ever wonder what powers the AI revolution? Meet $CRWV — CoreWeave, the Essential Cloud for AI. While AWS, Azure & Google do everything, CoreWeave does one thing at world-class level: massive-scale GPU infrastructure built exclusively for AI training & inference.

CoreWeave owns & operates 40+ specialized data centers packed with hundreds of thousands of the latest NVIDIA GPUs (H100/H200, Blackwell GB200, and soon Vera Rubin). Ultra-low latency networking, liquid cooling, high-speed InfiniBand — everything optimized so AI models train and run faster and cheaper than on general clouds.

Why it matters: Training & running frontier models like Claude, Llama, or GPT requires insane parallel compute that only dense GPU clusters can deliver. CoreWeave gives AI labs and enterprises instant access to this power — often getting the newest NVIDIA chips first and at better economics. 4/ Proof in the pudding: Just expanded a $21 Billion deal with Meta through 2032 for AI inference (total Meta commitment now ~$35B)

Fresh multi-year agreement with Anthropic to power Claude models....

Serves 9 of the top 10 AI providers

[Director of WACC @DirectorOfWACC]

$SNOW Why Snowflake's Largest Clients Are So Sticky
Snowflake's Net Revenue Retention (NRR) stands at 125% as of FY2026 (meaning the average existing customer base spent 25% more year-over-year). This is driven by very low churn and strong expansion, especially among big enterprises. Here's why the platform becomes deeply entrenched ("land and expand" in action):
Data Gravity and Massive Switching Costs
Once petabytes (or hundreds of petabytes, as in AT&T's case) of critical business data are loaded, governed, and optimized in Snowflake, moving it elsewhere is extremely expensive, time-consuming, and risky. Data is replicated across multiple clouds if needed, but the central governed repository creates strong inertia.
Multi-Cloud Flexibility + No Vendor Lock-in to One Hyperscaler
Customers can run on AWS, Azure, or Google Cloud (or across them) without rewriting queries or moving data. This appeals to large enterprises wary of single-cloud dependency.
Usage-Based Pricing Aligns with Value (and Encourages Growth)
Customers pay for what they consume (compute + storage). As they add more users, run more complex queries, ingest more data, or launch AI workloads, spend naturally grows — without forced seat licenses. AI features (used by >9,100 accounts) are accelerating this.
Network Effects via Snowflake Marketplace and Data Sharing
Large customers share live, governed data securely with partners, suppliers, or even internal teams. This creates ecosystem lock-in — the more data/products available in the Marketplace, the harder it is to leave.
Seamless Expansion into New Workloads
Starts with analytics → moves to data engineering, ML, unstructured data, app development (Snowpark), and now full AI/LLM pipelines (Cortex, NeMo integration with NVIDIA, agentic AI). Each new capability increases consumption without a full rip-and-replace.
Strong Governance, Security, and Compliance
Features like row-level security, dynamic data masking, and zero-copy cloning are critical for regulated industries (finance, healthcare, telecom). Enterprises trust Snowflake as their single source of truth for sensitive data.
Proven ROI and Operational Leverage
Case studies frequently cite major cost savings (e.g., AT&T's 35–84% reductions in specific areas) alongside faster insights and new capabilities. Once teams experience "it just works" across the organization, adoption spreads virally.
In short, Snowflake's largest clients treat it as a foundational AI Data Cloud rather than a simple database. The combination of data gravity, consumption-based economics, and continuous platform expansion makes churn rare and expansion the norm — which is why the $10M+ cohort is growing rapidly and why NRR remains solidly above 120%.
This stickiness supports Snowflake's long-term growth story but also means revenue can be somewhat concentrated in a smaller number of very large accounts.

[unusual_whales @unusual_whales]

Venu Krishna, US equities strategy head at Barclays, raised his price target for the end of 2026 to 7,650, provided the war in Iran gets resolved in the next few month

[Director of WACC @DirectorOfWACC]

U.S. prosecutors charge three individuals tied to $SMCI (including a co-founder) in an alleged scheme to smuggle $NVDA chips to China.

[Director of WACC @DirectorOfWACC]

@Bubblebathgirl @atrupar its called AI Paul... ya fuckin nit wit. Go play some 5d chess

[Director of WACC @DirectorOfWACC]

AI Circle Jerk continued Tesla edition $TSLA

[Director of WACC @DirectorOfWACC]

@RJCcapital $TSSI checks every box @RJCcapital

[Director of WACC @DirectorOfWACC]

@unusual_whales Granted income tax revenue far outweighs tariff revenue-it would be impossible.

[Director of WACC @DirectorOfWACC]

@TrumpDailyPosts

[Director of WACC @DirectorOfWACC]

@unusual_whales The other 50 million went to the person actually writing it #autopen

[Director of WACC @DirectorOfWACC]

@unusual_whales He created this months ago for 5mil and no one bit

[Director of WACC @DirectorOfWACC]

and I mean really really quickly.

[Director of WACC @DirectorOfWACC]

Not an $XRP maxi but the weekly chart downtrend breakout has me thinking we test 2.8$ quickly.

[Director of WACC @DirectorOfWACC]

@unusual_whales He’s ready for $ASML to smoke earnings

[Director of WACC @DirectorOfWACC]

@MoonTrades7