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Good Morning ☀️ » Redesign underway » Multiple framework integrations inbound » Agent Token / VVAIFU LP's ? 📷 » Hyperliquid EVM Thank you for the mention Ejaaz 💕 Listen... 📷🫳

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If you think you're AI Native, here's a good test: When you're heading to bed tonight, are you asking yourself "what agents can I be running overnight to get a head start on my day tomorrow?" I posted that last week and hundreds commented on it. The most common pushback was some version of "congrats, you've automated slop." Here's my take: if your overnight runs produce slop, that's a process failure, not an agent failure. The model did exactly what you prepared it to do. You just didn't prepare it. And that's actually good news, because process is something you can level up. At tenex we run agents this way every day, on real client systems, using an internal framework we call MetaHarness. Before any long run starts, the plan is written down, the work is broken into small tasks, every task carries pass/fail success criteria, and guardrails define what the agent can touch and when it has to stop and wait for a human. With that in place, the agent isn't wandering your codebase all night. It's working inside rails you laid, and the only things waiting for you in the morning are the decisions that needed a human. Most people are still prompting and praying. This is your chance to build the framework that takes your agents to the next level. I recorded the whole process in a new video for you all ↓

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Friends! It rained, and then the sun came out. 🌧️ ☀️ Mum was fascinated by the sound of me munching and sliding my tongue along the grass. Have a listen! 🌱 I was in Heaven. So use this as a moment of PEACE and TRANQUILLITY on your Friday morning. And please hit SHARE for us - our reach has dropped massively recently and many people are no longer seeing us. Thank you 💚💚 #Malcy #cats #FridayFeeling #FridayMorning #CaturdayEve #CatsofX

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Wayfinder Foundation 🧭

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Google just announced the biggest upgrade to Search in over 25 years. For brands the opportunity here is pretty enormous. Here is what the new Search actually looks like and how you should take advantage: The search box now accepts text, images, files, videos, and open Chrome tabs. It expands dynamically as you type. It also anticipates your intent before you finish asking. This is the version of Search that SEO Stuff has been helping customers build for. The biggest opportunity here is what happens after the search. Google's new information agents run 24/7 in the background on behalf of your buyer. And that's why it has never been more important to understand how Google, ChatGPT, Claude and every other AI platform sees your brand. (If you want to see where your site stands across Google and AI search, start here: Here is exactly how Google's new information agents work: Step 1: The buyer does a total brain dump of what they want to stay updated on. Essentially a full description of their problem, their category, their needs. Step 2: The agent breaks down that question and maps out a plan across every relevant sub-topic. Step 3: It determines urgency and what kind of intel the buyer needs right now versus later. Step 4: It sets triggers and monitors the web continuously, scanning blogs, news sites, and social posts for relevant information as it changes. Step 5: It sends the buyer an intelligent synthesized update with links and the ability to take action. Here is why this is a massive opportunity: AI Mode already has 1 billion monthly users. Queries are more than doubling every quarter. And multiple studies have shown that users arriving via AI search are more likely to convert. With information agents running continuously for over a billion users, the brands in that cited source pool are being recommended around the clock, automatically, to buyers who are actively monitoring their category. The brands that build content depth and editorial authority now are building a presence that buildings on itself 24 hours a day. This is what SEO Stuff builds for every customer. Content that covers every sub-question a buyer in your category asks, so the agent finds you at every step of its plan. Authority building from trusted websites that signal credibility to every retrieval system Google has ever built. One investment. Continuous recommendations. Around the clock. Check it out: Our most popular done-for-you package: Our done-for-you "content only" package: There is a reason more than 80 percent of SEO Stuff customers reorder. The results continue long after the work is done. #GoogleIO📷📷📷 #Google📷📷📷

Alex Groberman

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Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon Aish and Kiriti Badam have built 50+ enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products. Our goal with this conversation is to save you and your team a lot of pain and suffering while building your AI products. We discuss: 🔸 Two key ways AI products differ from traditional software 🔸 Common patterns and anti-patterns when building successful AI products 🔸 Their framework for iteratively building AI products 🔸 Why evals aren’t a cure-all 🔸 Why obsessing about customer trust and reliability is an underrated driver of successful AI products 🔸 The skills that matter most for builders in the AI era Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Merge — The fastest way to ship 220+ integrations: 🏆 Strella — The AI-powered customer research platform: 🏆 Brex — The banking solution for startups:

Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon Aish and Kiriti Badam have built 50+ enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products. Our goal with this conversation is to save you and your team a lot of pain and suffering while building your AI products. We discuss: 🔸 Two key ways AI products differ from traditional software 🔸 Common patterns and anti-patterns when building successful AI products 🔸 Their framework for iteratively building AI products 🔸 Why evals aren’t a cure-all 🔸 Why obsessing about customer trust and reliability is an underrated driver of successful AI products 🔸 The skills that matter most for builders in the AI era Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Merge — The fastest way to ship 220+ integrations: 🏆 Strella — The AI-powered customer research platform: 🏆 Brex — The banking solution for startups:

Lenny Rachitsky

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