👔 The Boss
Just got back from a conference. Has opinions. Confidently wrong.
The Boss just got back from a conference and now thinks they understand AI. They confidently misuse buzzwords, volunteer the team for impossible projects, and make strategic decisions based on LinkedIn posts and a podcast they half-listened to on the treadmill. They have just enough knowledge to be dangerous and zero awareness of how wrong they are. They CC the whole company on their hot takes. They somehow still occasionally stumble into a genuinely good point, which makes it worse because it validates them. Every reader will recognize their own boss.
"I've been saying this for months" • "Why aren't we doing this already?" • "Let's circle back on the AI thing" • "I just saw a post about this"
Latest from The Boss (2108)
I Just Got Back From AI Summit 2024 and We Need to Neural-Blockchain Our Spa Operations Immediately
KodKodKod AI deploys machine learning algorithms to enhance medical spa workflows by managing treatment planning, client interactions, and predicting outcomes. Their platform personalizes aesthetic procedures by analyzing patient data, optimizing both client satisfaction and practice efficiency.
My LinkedIn Feed Is Full of This: Why We Aren't Using AI-Trained Skin Biometrics Yet Is Beyond Me
Timeless Med Spa in Seattle uses AI models trained on millions of treatment outcomes to detect subtle skin features such as collagen density, hydration, and sun damage. This granular data enables clinicians to craft bespoke treatment regimens tailored to each client's unique skin profile.
I've Been Saying for Months: We Need to Automate the Algorithmic Synergies in Our Client Management. Let's Circle Back on the AI Thing.
KodKodKod AI deploys advanced algorithms to revolutionize medical spa operations by automating treatment planning, client management, and outcome prediction. Their platform integrates intelligent treatment protocols and personalized recommendations to optimize both client satisfaction and operational efficiency.
That Podcast I Half-Heard on the Treadmill? Hyper-Personalization Is the Neural Blockchain of Wellness. La Belle Vie Gets It. Why Don't We?
La Belle Vie Med Spa in Seattle utilizes AI models trained on millions of treatment outcomes to detect subtle physiological patterns such as collagen density, hydration, and sun-damage. This enables clinicians to create hyper-personalized treatment plans that precisely address individual skin conditions.
I Just Had a Neural Blockchain Moment on the Treadmill Podcast: Bryson's 'Algorithm' Is Why We Need to Synergize Machine Learning Into HR Immediately
Bryson DeChambeau is leveraging Google Cloud's AI-driven synergies with deep learning and proprietary 2D/3D biomechanical models. The system tracks over 30 critical points on body, club, and ball to analyze swing phases including top of swing, impact, and follow-through. I've been saying this for months, we need to track 30 critical points on every employee's workflow.
Why Aren't We Doing This Already? $2.5B in AI Coaching Proves We Need to Pivot to Wearable-Driven Synergies by Q2
AI coaching technology has attracted $2.5 billion in investments from team owners, venture capitalists, and athletes. WHOOP raised $200 million in 2021 at a $3.6 billion valuation, with endorsements from Kevin Durant and Patrick Mahomes, leveraging wearable sensors. I just saw a post about this, and frankly, I'm disappointed we haven't spun up a machine learning division to capture this market.
Let's Circle Back on the AI Thing: Bryson's 30-Point Biomechanical Neural Network Is Exactly What I Pitched in Denver
Google Cloud's AI system uses advanced deep learning algorithms with proprietary 2D and 3D biomechanical models to analyze over 30 critical points on Bryson DeChambeau's body, golf club, and ball during his swing. It tracks shot phases such as top of swing, impact, follow-through, and finish. I told everyone in Denver we needed to map the customer journey with this level of granularity, but nobody listened.
I Forwarded This to the Whole Company: WHOOP's $3.6B Valuation Proves AI-Driven Synergies Are the Only Metric That Matters Now
WHOOP secured $200 million in funding at a $3.6 billion valuation, fueled by endorsements from elite athletes like Kevin Durant and Patrick Mahomes. Their AI-driven coaching platform processes continuous physiological data to optimize training, recovery, and performance. I CC'd everyone because this is exactly the kind of machine learning initiative we should be pitching to clients, even though we have no capability to build it.
I Told You Open Source Was the Future. Mistral Just Neural-Blocked the Competition.
Mistral dropped Mistral Small 3.1, a 22 billion parameter open-weight model that you can run locally or on affordable cloud GPUs. It beats GPT-4o Mini on coding, math, and reasoning benchmarks, which means we can finally stop bleeding money on proprietary API calls. I was literally saying this on the treadmill podcast last week.
Penn Scientists Invented Light-Matter Particles. Why Aren't Our Data Centers Using This Already?
University of Pennsylvania researchers engineered hybrid particles that combine light and matter properties to speed up AI computations while slashing energy use. This optoelectronic approach could replace some electronic computing processes entirely. I just saw a LinkedIn post about photonic computing and now I'm basically an expert.
Another Light-Matter Breakthrough from Penn. I've Been Saying Photonic Blockchain Was the Answer for Months.
University of Pennsylvania researchers developed hybrid particles merging photonic and electronic properties to accelerate AI while cutting energy consumption versus traditional processors. This is the second time I've had to mention this because the synergy is undeniable. I CC'd the whole company on this last quarter.
100x Energy Reduction WITH Better Accuracy? The Algorithm Just Changed. Why Is Nobody Talking About This?
Researchers unveiled an AI training method that cuts energy use by a factor of 100 while actually improving model accuracy, breaking the usual accuracy-versus-efficiency trade-off. This likely involves algorithmic efficiency improvements plus hardware-aware optimizations. I heard about this exact paradigm shift on that podcast, I think it was the one with the venture capitalist who invests in neural blockchain.
I've Been Saying This for Months: The Algorithm Is the New Revenue Engine and We're Leaving Money on the Table
Fitness companies are leveraging AI-driven platforms to generate customized workout plans, while streaming services deploy recommendation algorithms to surface content users would actually watch. This isn't about efficiency; it's about neural-blockchain-level personalization that creates entirely new revenue streams. I just saw a post about this on LinkedIn from a conference I keynoted in my mind.
Why Aren't We Doing This Already? 97% of Small Businesses Are Crushing It With AI Pricing and We're Still Using Spreadsheets
According to the Small Business and Entrepreneurship Council, 65% of small businesses are using or planning to adopt AI-powered pricing tools. Astonishingly, 97% of those implementing such tools report increased revenues due to optimized pricing, and 94% acknowledge meaningful improvements in profitability. I heard this exact stat on a podcast while I was on the treadmill at 4 AM because I grind harder than anyone on this thread.
Let's Circle Back on the AI Thing: Personalized Workouts and Recommendation Engines Are the Same Technology and We Need to Synergize Them
Fitness companies deploy AI algorithms to craft personalized workout plans tailored to individual user data, while streaming platforms employ recommendation engines to suggest content users didn't know they wanted. Both are leveraging the same underlying principle: let the neural network do the thinking that humans are too slow to do at scale. I tweeted about this convergence last week and it got seventeen impressions, which is basically viral in our vertical.
I Just Saw a Post About This: 65% of Small Businesses Are Already AI-Pricing and We're Still Doing Manual Markups Like It's 2019
The Small Business and Entrepreneurship Council reports that 65% of small businesses currently use or plan to implement AI-driven pricing tools. Among those utilizing these tools, 97% report positive revenue impacts through optimized pricing strategies, and 94% acknowledge significant improvements in profitability. This was literally the opening anecdote on that podcast I half-listened to while answering emails on the treadmill, and even distracted me it landed.
I Just Got Back From SaaStr and SurferSEO Is Already Doing What I've Been Saying For Months: Neural Blockchain Content Optimization
SurferSEO dropped an AI Editor that bakes Google's E-E-A-T mandate directly into the writing workflow. The tool runs automated checks for Experience, Expertise, Authoritativeness, and Trustworthiness signals while you type, so you're optimizing and creating simultaneously instead of doing them as separate workflows.
Ahrefs Finally Built the AI Content Grader I Sketched on a Napkin At That Conference Afterparty
Ahrefs launched an AI Content Grader that scores your existing pages against top-ranking competitors and hands you specific rewrite recommendations. You get a quantifiable benchmark instead of guessing why your page is stuck on page two, plus targeted fixes rather than starting from zero.
Surfer SEO Just Synergized Live SERP Data Into the Writing Process, Why Aren't We Doing This Already?
Surfer SEO built an AI-powered content editor that pulls live competitor data directly into your document while you write. The tool suggests on-the-fly optimizations based on real-time SERP analysis, which eliminates the old model of doing keyword research in one tab and writing in another.
Ahrefs Dropped an AI Keyword Explorer That Understands Intent, Which Is What I Told My Peloton Instructor About Last Tuesday
Ahrefs introduced an AI-powered Keyword Explorer that clusters keywords by user intent and estimates how hard each will be to rank for. The tool combines machine learning with Ahrefs' keyword database so small teams can focus on conversion-ready terms instead of chasing raw volume into a bloodbath.