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- π‘The $32B Security Bet That Changes Everything
π‘The $32B Security Bet That Changes Everything
PLUS: Why Wall Street's AI doubts create your biggest opening in 18 months
Welcome back to the only newsletter that treats your inbox like a board meeting - no fluff, just the intelligence that compounds.
Featured Tool π
Spent Saturday nerding out on this.
Free tool that scrapes Reddit and shows you - in about 2 minutes - every mention of your brand across the entire platform.
The unfiltered stuff.
Good, bad, brutally honest.
I've been checking what people say about competitors when they think no one's watching. It's... eye-opening.
Emailed the founder. He hooked me up with early access.
Secret Code: reddit2026
Within 5 minutes, truly understand how your business is doing on Reddit.
For CTOs testing developer tool launches or API-first products where Reddit communities drive early adoption: this is huge.
CTO Quick Hits π―
π The US is burning more energy per AI compute unit than β¦ everyone
π° Google locked in $32B for Wiz. Cloud security as ..offense?
π Wall Street's cooling on AI stocks
π¦ SoftBank's back in AI deal-making mode
π΅ OpenAI is building an AI to generate music from text prompts -
π Cloudflare integrated CrowdStrike's SOAR platform
π + 3 other stories you might like below
The Big Picture πΌοΈ
π‘ Energy Efficiency Is the New Talent War.
The US is falling behind in AI energy efficiency - not by a little, but by margins that will compound into structural cost disadvantages.
While competitors optimize compute per watt, American infrastructure still treats energy as an afterthought rather than a core product constraint.
For CTOs: your cloud bill isn't just an operational expense anymore. MIT Technology Review's analysis shows energy strategy is becoming as critical as your talent strategy was five years ago.
The companies winning AI deployment races aren't just hiring the best ML engineers - they're architecting for energy efficiency from day one.
Your move: Audit your inference costs by energy footprint, not just by model accuracy. The gap is widening.
π‘ Google Just Made Security a Product Differentiator.
Google's $32B bet on Wiz isn't about adding another security vendor to the portfolio.
TechCrunch's breakdown of the acquisition approval reveals a chess move: turning cloud security from a compliance checkbox into a sales weapon against AWS and Azure.
This matters because security used to be the thing you proved you had. Now it's the thing you sell with.
For infrastructure buyers, security posture is transitioning from "do we trust them?" to "can we leverage their security as our competitive advantage?"
For CTOs: If you're evaluating cloud providers in 2025, security isn't a feature comparison anymore - it's a go-to-market accelerator. Ask vendors how their security infrastructure becomes your customer-facing differentiator, not just your internal safeguard.
π‘ Wall Street's Doubt Is Your 18-Month Window.
Wall Street is losing faith in AI, and that's the best news you've heard all quarter.
When public markets get skeptical, hype tourists exit, valuations normalize, and talent becomes available again.
The last time this happened - during the crypto winter - the serious builders got 18 months of clear air while everyone else panicked. Same pattern, different vertical.
SoftBank's return to AI deal-making only amplifies this: expect a fresh wave of overvalued, under-engineered "AI startups" that will crater in 12-24 months, creating acquisition targets and talent pools for the patient.
Strategic implication: The noise is clearing. The companies building real AI infrastructure - not just OpenAI wrappers - now have runway to compound advantages while competitors chase the next shiny thing.
π‘ The Fundamentals Still Win.
While everyone obsesses over the latest model release, Dijkstra's manuscripts remind us that engineering discipline beats feature velocity.
The CTOs winning right now aren't the ones deploying AI fastest - they're the ones who understand distributed systems well enough to avoid the scaling disasters their competitors will hit in 18 months.
NYU's new AI architecture for faster image generation and Terminal-Bench 2.0's testing framework prove the same thesis: innovation happens when you optimize the boring parts, not when you chase the flashy demos.
For rising tech leaders: Master your fundamentals now. When the next AI hype cycle crashes, the engineers who understand first principles will be the ones left standing.
The Bottom Line π
This week's signal: the gap between AI tourism and AI infrastructure is widening fast.
Google's betting $32B that security becomes a revenue driver, not a cost center.
Wall Street's skepticism is clearing the field for serious builders. Energy efficiency is becoming the constraint that separates scaling companies from stalling ones.
Your move: What's your AI infrastructure readiness score? More importantly - while your competitors chase headlines, what foundational advantage are you building that compounds over the next 18 months?
Hit Reply And Tell Me π¬
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