AI reveals flaws in our mental models, forcing us to rethink.

More info ≠ Better AI. Better context= Better AI One of the biggest mistakes is flooding models with everything — entire documents, long transcripts, endless background. The result? Noise, confusion, and wasted tokens. Context engineering is about precision, not volume. The right 200 words will outperform a raw 20,000 every time. Reducing context from full review logs to only the 3 most relevant excerpts improved accuracy and cut token usage by half! The lesson: signal beats noise. Context isn’t about giving the model more — it’s about giving it what matters. Question: How do you filter for relevance in your AI workflows? #AI #ContextEngineering #AppliedAI #FutureOfWork #GenerativeAI

In an age of information overload, how will AI reshape our access to knowledge? Instead of passively receiving data, imagine AI curating a personalized stream, selecting what it anticipates we need to know. This "concierge-style" approach could transform productivity, offering tailored support for both professional and personal endeavors. It raises intriguing questions about the balance between convenience and potential filter bubbles. Curious to hear how others are thinking about this evolution? #AI #ArtificialIntelligence #Productivity #FutureOfWork #Innovation

You don’t know how our brain thinks (biologically or technically), right? But you can know how an AI thinks—layer by layer. Think of it like a relay race : First : Words turn into numbers (AI’s language). Next: Attention kicks in—“Which word matters most here?” Next: Layers refine meaning—like zooming in on a photo until it’s crystal clear. Next: Output—AI guesses the next word, again and again, until full thoughts appear. Billions of micro-decisions → one intelligent response. LLMs don’t understand like us humans. But they’re an incredible mirror, reflecting back our patterns of thought. Watch the video 🎥 to see this idea in action. #AI #ArtificialIntelligence #MachineLearning #DeepLearning #LLM #TechExplained #AIForEveryone #FutureOfAI #GenAI

The Prompt Era Guide is live. We built it to answer one question: how do you speak to machines so they truly understand you? Inside, you’ll find the art and science of prompt engineering, distilled into frameworks, examples, and strategies that help you turn ordinary inputs into extraordinary outcomes. This guide isn’t just about prompts. It’s about rethinking how we work with AI, and how businesses can unlock clarity, creativity, and competitive edge in the new era of intelligence. Explore the full guide here: https://lnkd.in/dKnn9eMP #TechResearchOnline #PromptEra #PromptEngineering #AI

Thrilled to share that the Prompt Era Guide is finally live! I had the chance to be closely involved in bringing this together, and it’s incredible to see it out in the world. It’s more than a guide, it’s a deep dive into how prompt engineering is reshaping the way we work with AI, and how businesses can harness it for sharper, smarter outcomes. Check it out here: https://lnkd.in/dEsAe3R3 #PromptEra #AI #TechResearchOnline

“When convenience becomes a crutch, we risk losing the very skills that define us.” Artificial Intelligence can simplify everything—from writing to decision-making—but overreliance has a hidden cost. • Critical thinking takes a back seat • Creativity is replaced by quick, machine-made answers • Problem-solving muscles grow weaker This video calls for balance: AI as a tool, not a substitute for human intellect. How do we protect curiosity and independent thought in an AI-driven world? #AI #CriticalThinking #HumanIngenuity #ResponsibleTech #FutureOfWork

AI agents are revolutionizing industries, but can they outsmart context overload. • While they excel in problem-solving, overloading them risks losing the human insight that drives innovation. • Are we automating away our edge. #AIInnovation #FutureOfWork #DigitalTransformation #BusinessStrategy #AI

🚦 𝗘𝘀𝗰𝗮𝗽𝗶𝗻𝗴 𝗧𝘂𝗻𝗻𝗲𝗹 𝗩𝗶𝘀𝗶𝗼𝗻 𝗶𝗻 𝗟𝗟𝗠𝘀 Here's what researchers just discovered: When large language models reason step by step, they often fall into 𝘵𝘶𝘯𝘯𝘦𝘭 𝘷𝘪𝘴𝘪𝘰𝘯 — the first few words push them down a single (sometimes wrong) path. Just making that chain longer doesn’t magically fix it. 𝗧𝗵𝗲 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗺𝗼𝘃𝗲: 🔀 Run several shorter reasoning paths in parallel. Or simply ask the same question multiple times differently. 🔀 Combine the results (majority voting or summarization). 🔀 Get better answers without retraining the model. Think of it as “parallel brainstorming” for AI. Instead of betting everything on one long chain of thought, let multiple perspectives compete. Sometimes the best way forward isn't to think harder in one direction, but to think differently in many directions all at once. 🤖 𝗪𝗵𝗮𝘁’𝘀 𝘆𝗼𝘂𝗿 𝗴𝗼-𝘁𝗼 𝘁𝗿𝗶𝗰𝗸 𝗳𝗼𝗿 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗮𝗻𝘀𝘄𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝗟𝗟𝗠𝘀? Source -> https://lnkd.in/ehH4yS7R #AI #GenAI #LLMs #TechStrategy #Parallelism

🤖 Scaling won’t get us to AGI. In this week’s Roundup, Anthony explores why AI pioneers like Yann LeCun believe the next frontier isn’t about bigger models but about reasoning, memory, and planning. Key takeaways: 1️⃣ Scaling existing LLMs = diminishing returns 2️⃣ True AGI will demand breakthroughs in reasoning & long-term memory 3️⃣ Businesses need design-first AI strategies (that’s why we’re building DevReady.Ai) 🎥 Watch the full roundup linked in the comments! #AI #AGI #ResponsibleAI #DevReadyAi

🚀 From 10 Hours to Just 1 Hour! That’s the power of AI when you use it smartly. In today’s world, time is the most precious resource. The right AI tools don’t just save hours—they give you back freedom to think, create, and grow. 💡 In my latest video, I break down how AI can cut down your workload dramatically and help you focus on what truly matters. #AI #Productivity #TimeManagement #ArtificialIntelligence #WorkSmarterNotHarder #navneetmishra