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Comment "Call" and I'll send you the link Cold calls fail when you sound like a salesperson instead of a source of useful information. Specific observations keep people on the line longer than polite introductions ever will. Relevance earns attention. Random pitches lose it. @aipbi - AI Content #SalesTips #ColdCalling #BusinessCommunication #SalesWisdom #OldMoneyThinking ExecutionMatters ClosingDeals EntrepreneurMindset
Don't cold call a business and say, hey, this is Joe from Sales Corp, how are you today
View DetailsTurning Shipping Containers Into a Forest Courtyard Home
10.5cm x 10cm 11.5cm x 10cm 12.5cm x 10cm 13.5cm x 10cm
View DetailsPricing without value context is just a number they'll negotiate. Pricing with value context is an investment that makes sense. When you quantify what the problem costs them first, show what changes when it's solved second, and present the investment last, price stops being the objection. The ROI math has already been done in their head before you ever state the number. @aipbi – AI Content #SalesStrategy #PricingStrategy #BusinessWisdom #ClosingDeals #OldMoneyThinking ValueBasedSelling ExecutionMatters
When you present pricing before value, you're asking them to justify a cost
View Detailscreatorsearchinsights This might be the most disturbing TRUE CRIME documentary streaming right now A latenight radio DJ vanished live on air and the tape was never supposed to be heard again ttruecrimeddocumentarymmysteryscarystory
There's an insane new documentary on Disney Plus you should watch this weekend
View DetailsEveryone so afraid to use their hands. It’s the only place we can transfer the energy to the club 🤷🏻♂️ #golf #골프 #ゴルフ #fyp #golftips
I'm saying cocking the wrist, the wrist here, then it's a snap at the, at the base of the...
View Details😂😂 ☕️☕️ . . . . . 🔥 Comment or DM me SOBRIETY to grab your free copy of my 9 page Beginner’s Guide To Food Sobriety and take the food addiction self assessment and also learn the what, the why and the principles of food sobriety.🔥
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View DetailsSatya Nadella frames AI not as a tool upgrade — but a structural rewrite of how work happens. He compares today’s moment to the PC revolution: Before PCs: • Faxes • Interoffice memos • Manual aggregation After PCs: • Excel • Email • Standardized workflows Now, AI is triggering the next shift. At LinkedIn, Nadella describes collapsing multiple roles — product manager, designer, frontend and backend engineer — into a single full-stack builder. Why it matters: • Fewer handoffs • Faster iteration • Higher idea throughput • One person, end-to-end ownership This isn’t about replacing people. It’s about changing the work artifact and the workflow at the same time. That’s where productivity actually compounds. Follow to learn the latest insights on VC, finance, tech, and markets. Credits: Satya Nadella, All-In Podcast (Davos) Edited for educational purposes. No ownership claimed. For informational purposes only — not financial or investment advice.
At LinkedIn, we used to have product managers, we had designers, we had front-end engineers, and...
View DetailsThe way we code just changed You used to work on one thing at a time Finish it Move to the next thing Thats over Now you can launch multiple AI coding agents simultaneously each one building a different feature autodeploying test environments All while you review the work from your phone Youre not coding anymore Youre managing a team of AI developers The people who figure this out first will move at a completely different speed than everyone else
Today, I'll show you the ultimate vibe coding setup that lets you seamlessly code on your...
View DetailsNot the chicken nugs! (Via @nbcsportssoccer) #dad #kids #chicken #funnyvideos
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View DetailsToday’s case study: @lululemon just launched NFL-branded leggings and hoodies while their stock is down 50%. Critics might call it smart partnering. I call it what it is—borrowed relevance disguised as strategy. If you want the full breakdown on what Lululemon’s NFL bet teaches about brand strategy, comment NFL and I’ll send it directly xx
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View DetailsYou think my troops are gonna help you?🐶 [dog reels, funny dogs, dog voiceover, denzel clips, funny pet videos, dog mischief, Labradors] #dogfunny #dogimpressions #dogreactions #funnydogreels #dogsofinsta
You got one problem though, Jake
View DetailsI’m so passionate about this because notion literally changed my life...
Here's what to do if you tried to use Notion, but it actually made things harder instead of easier
View Detailsit wasn’t as bad as I thought it would be… I thought the cost would be much higher because of the expensive model I'm using (projecting $3K) this is probably the most expensive app I've ever launched because of the cost, usually it is only a few hundred dollars because of the tools that I use really good lesson since I plan on launching a few more AI products in the future and need to account for the testing period where I'm eating all of that cost 🥲 #softwaredeveloper #coding #appdesign
This is how much it cost me to launch my app
View DetailsComment “app” for a link to the iOS app. Thanks guys. #ai #focus
This is how I turned my website into an iPhone app without changing any code, making an app with...
View DetailsHe grew to a Principal Eng (IC8) at Meta then created Claude Code at Anthropic I interviewed Boris Cherny for his full career story, link in bio if you're interested!
Can you explain latent demand
View DetailsApple’s CLaRa system fundamentally reimagines RAG architecture by solving the semantic similarity problem that plagues traditional retrieval systems. Standard RAG approaches chunk documents, create static embeddings, and hope queries match semantically similar content—a critical flaw that forces workarounds like HyDE and query decomposition. CLaRa eliminates this by transforming documents into Memory Tokens: compressed representations of pure content stripped of filler and syntax, distinct from raw text. The breakthrough lies in its trainable Query Reasoner. Rather than matching queries directly to documents, it generates hypothetical ideal answers and queries against appropriate Memory Tokens. This component learns from the database itself through training runs, continuously improving retrieval accuracy. The system essentially operates as HyDE amplified—hypothetical document embeddings merged with dynamic, learnable retrieval—while running on modest model sizes. Technical highlights: - Memory Tokens replace static chunk embeddings with compressed content representations - Query Reasoner generates ideal answers before retrieval, not after - Direct database-to-reasoner training loop enables continuous optimization - Achieves superior results without requiring massive computational resources
Apple just quietly solved one of the biggest bottlenecks in RAG
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