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Our team was spending around 6+ hours every week figuring out where projects actually stood. The work wasn't the problem. Finding the latest context was. I run a team where multiple projects move at the same time, so keeping everyone aligned used to mean checking dozens of Slack conversations...

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Kaitee

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59,483 次观看 • 7 天前 •via X (Twitter)

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The first campaign Viktor reviewed caught problems we didn't even know were there. We're a digital marketing team managing campaigns across multiple ad platforms, and before every launch someone on the team would manually check tracking, landing pages, targeting, budgets, creatives, and campaign settings. It was repetitive work, but missing just one detail could turn into wasted budget or inaccurate reporting. Instead of asking Viktor to help with individual checks, we gave him ownership of our entire campaign launch QA workflow. The first thing that stood out wasn't how quickly he worked. It was how thorough he was. Across one month, Viktor completed QA for 30 campaigns, executed 330 automated checks, and identified 47 issues, including 14 critical errors that could have affected campaign performance before a single campaign went live. By the time our team stepped in, all that was left was reviewing his findings and approving the launch. That completely changed the way we approached campaign launches. Instead of spending 65 hours every month on manual QA, our workflow was reduced to just 10.5 hours of strategic review giving our team back an estimated 54.5 hours to focus on optimization instead of repetitive checks. The biggest takeaway wasn't the time we saved. It was knowing every campaign went through the same level of quality control before launch. That's the difference we've started seeing between an AI assistant and an AI employee. An assistant waits for prompts. An AI employee owns recurring work while your team focuses on the decisions that matter most. Every campaign your team launches without this is a risk someone on your team is quietly absorbing. A copilot helps you work. An AI employee works when you don't. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #MarketingOps #DigitalMarketing Paid Partnership
0:58

The first campaign Viktor reviewed caught problems we didn't even know were there. We're a digital marketing team managing campaigns across multiple ad platforms, and before every launch someone on the team would manually check tracking, landing pages, targeting, budgets, creatives, and campaign settings. It was repetitive work, but missing just one detail could turn into wasted budget or inaccurate reporting. Instead of asking Viktor to help with individual checks, we gave him ownership of our entire campaign launch QA workflow. The first thing that stood out wasn't how quickly he worked. It was how thorough he was. Across one month, Viktor completed QA for 30 campaigns, executed 330 automated checks, and identified 47 issues, including 14 critical errors that could have affected campaign performance before a single campaign went live. By the time our team stepped in, all that was left was reviewing his findings and approving the launch. That completely changed the way we approached campaign launches. Instead of spending 65 hours every month on manual QA, our workflow was reduced to just 10.5 hours of strategic review giving our team back an estimated 54.5 hours to focus on optimization instead of repetitive checks. The biggest takeaway wasn't the time we saved. It was knowing every campaign went through the same level of quality control before launch. That's the difference we've started seeing between an AI assistant and an AI employee. An assistant waits for prompts. An AI employee owns recurring work while your team focuses on the decisions that matter most. Every campaign your team launches without this is a risk someone on your team is quietly absorbing. A copilot helps you work. An AI employee works when you don't. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #MarketingOps #DigitalMarketing Paid Partnership

Kylie

92,501 次观看 • 22 天前

We wanted to know if Viktor could own a real job. Our first pilot reduced a five-client reporting workflow from 12 to 15 hours of manual work to roughly an hour of team review. We're a digital marketing team managing paid media performance and client reporting, so we decided to test Viktor on one recurring workflow that every agency knows too well. Weekly reporting. Viktor didn't just summarize data. He produced a complete five-page report with an executive summary, funnel insights, channel performance, recommendations, and a final review checklist. Our team's job became reviewing and approving the work instead of building every report from scratch. That was the moment we stopped thinking about AI as another chat window. The real value wasn't getting better answers. It was handing off a recurring job and getting consistent work back every week while keeping our team in control of the final decision. Most AI tells you what to do. Viktor does it. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #FutureOfWork Paid Partnership.
0:47

We wanted to know if Viktor could own a real job. Our first pilot reduced a five-client reporting workflow from 12 to 15 hours of manual work to roughly an hour of team review. We're a digital marketing team managing paid media performance and client reporting, so we decided to test Viktor on one recurring workflow that every agency knows too well. Weekly reporting. Viktor didn't just summarize data. He produced a complete five-page report with an executive summary, funnel insights, channel performance, recommendations, and a final review checklist. Our team's job became reviewing and approving the work instead of building every report from scratch. That was the moment we stopped thinking about AI as another chat window. The real value wasn't getting better answers. It was handing off a recurring job and getting consistent work back every week while keeping our team in control of the final decision. Most AI tells you what to do. Viktor does it. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #FutureOfWork Paid Partnership.

Sean Wallace

51,510 次观看 • 27 天前

An agency added $133,752 in new annual recurring revenue in its first 30 days. No new hires. No new service line. That number made me stop scrolling. I spend a lot of time researching AI tools. The biggest time sink isn't testing them. It's comparing features, checking updates, and turning scattered information into something useful. So I tried Viktor Viktor is an AI employee that works inside Slack. I asked it to research the latest AI video generation tools, compare their features, pricing, and best use cases. Instead of starting from a blank page, I had a structured proposal waiting for review. I kept the final approval. Viktor handled the work. That reminded me of Nico Torres, Founder of Authority Makers. His team used Viktor to run work that simply wasn't getting done before, adding $133,752 in new annual recurring revenue in the first 30 days without adding headcount. Most AI tells you what to do. Viktor does the work. Try free at Viktor. $100 in credits included, no card. Full link in the first comment. #AIemployee #AITools #Productivity Paid Partnership
0:26

An agency added $133,752 in new annual recurring revenue in its first 30 days. No new hires. No new service line. That number made me stop scrolling. I spend a lot of time researching AI tools. The biggest time sink isn't testing them. It's comparing features, checking updates, and turning scattered information into something useful. So I tried Viktor Viktor is an AI employee that works inside Slack. I asked it to research the latest AI video generation tools, compare their features, pricing, and best use cases. Instead of starting from a blank page, I had a structured proposal waiting for review. I kept the final approval. Viktor handled the work. That reminded me of Nico Torres, Founder of Authority Makers. His team used Viktor to run work that simply wasn't getting done before, adding $133,752 in new annual recurring revenue in the first 30 days without adding headcount. Most AI tells you what to do. Viktor does the work. Try free at Viktor. $100 in credits included, no card. Full link in the first comment. #AIemployee #AITools #Productivity Paid Partnership

Sam brown

45,645 次观看 • 2 天前

I realized we weren't waiting on clients. We were waiting on approvals. I run a digital marketing agency, and before every campaign launch the same thing happened. Someone asked if the creative had been approved. Someone else checked whether the copy was signed off. Another person chased budget approval. Then somebody opened three different spreadsheets just to figure out what was still missing. Launching the campaign wasn't stressful. Figuring out whether we were actually ready to launch was. For a while, I assumed that was just part of running an agency. The bigger we got, the more Slack messages we sent. The more follow-ups we wrote. The more time disappeared into checking whether everyone else had done their part. Everything changed when I stopped using Viktor as another AI tool and gave him ownership of our approval and launch coordination workflow. Now my team hands Viktor the campaign requirements. He tracks every approval, follows up automatically, flags blockers before they delay launches, verifies every asset, runs launch readiness checks, and prepares the final launch confirmation before anyone on the team reviews it. Last month that meant coordinating 10 campaigns across 5 clients, completing 40 approval workflows and preparing 90 launch deliverables before our team stepped in. What used to consume 83.5 hours of manual work now requires a fraction of that effort, reducing manual work by 88%. The biggest shift wasn't moving faster. It was no longer wondering whether a campaign was actually ready to launch. Most campaign delays aren't a capacity problem. They're an approval problem nobody assigned to anyone. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #AgencyOps #Marketing Paid Partnership
0:45

I realized we weren't waiting on clients. We were waiting on approvals. I run a digital marketing agency, and before every campaign launch the same thing happened. Someone asked if the creative had been approved. Someone else checked whether the copy was signed off. Another person chased budget approval. Then somebody opened three different spreadsheets just to figure out what was still missing. Launching the campaign wasn't stressful. Figuring out whether we were actually ready to launch was. For a while, I assumed that was just part of running an agency. The bigger we got, the more Slack messages we sent. The more follow-ups we wrote. The more time disappeared into checking whether everyone else had done their part. Everything changed when I stopped using Viktor as another AI tool and gave him ownership of our approval and launch coordination workflow. Now my team hands Viktor the campaign requirements. He tracks every approval, follows up automatically, flags blockers before they delay launches, verifies every asset, runs launch readiness checks, and prepares the final launch confirmation before anyone on the team reviews it. Last month that meant coordinating 10 campaigns across 5 clients, completing 40 approval workflows and preparing 90 launch deliverables before our team stepped in. What used to consume 83.5 hours of manual work now requires a fraction of that effort, reducing manual work by 88%. The biggest shift wasn't moving faster. It was no longer wondering whether a campaign was actually ready to launch. Most campaign delays aren't a capacity problem. They're an approval problem nobody assigned to anyone. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #AgencyOps #Marketing Paid Partnership

Tyler Wayne

80,376 次观看 • 14 天前

An agency added $133,752 in new annual recurring revenue in its first 30 days with Viktor. No new hires. No new service line. I spend most of my time testing AI tools for content and outbound work, so I don't say that lightly. Every team I talk to has the same problem. The strategy is fine. The relationships are fine. What's missing is capacity, the high-value work sitting on the backlog because nobody has the hours to own it. I've watched teams try to fix that by hiring, or by bolting on another tool that just answers questions and calls it done. Then I read what happened at Authority Makers. Nico Torres, the founder, didn't hire and didn't add a service line. He gave Viktor the outbound and lead gen work that had been sitting untouched. $133,752 in new ARR in the first 30 days. Same team, same strategy. The only thing that changed was who was doing the work. Most AI tells you what to do. Viktor does it. Tell me I'm wrong. Try free at Viktor. $100 in credits, no card. Full link in my first reply. Paid Partnership
1:02

An agency added $133,752 in new annual recurring revenue in its first 30 days with Viktor. No new hires. No new service line. I spend most of my time testing AI tools for content and outbound work, so I don't say that lightly. Every team I talk to has the same problem. The strategy is fine. The relationships are fine. What's missing is capacity, the high-value work sitting on the backlog because nobody has the hours to own it. I've watched teams try to fix that by hiring, or by bolting on another tool that just answers questions and calls it done. Then I read what happened at Authority Makers. Nico Torres, the founder, didn't hire and didn't add a service line. He gave Viktor the outbound and lead gen work that had been sitting untouched. $133,752 in new ARR in the first 30 days. Same team, same strategy. The only thing that changed was who was doing the work. Most AI tells you what to do. Viktor does it. Tell me I'm wrong. Try free at Viktor. $100 in credits, no card. Full link in my first reply. Paid Partnership

Alex Moore

31,672 次观看 • 25 天前

Excited to announce Viktor in Microsoft Teams. This week we crossed $20M in annualized revenue run rate. In Slack. One app, no sales team, no rollout. Now Viktor goes where the rest of the working world actually is. 320 million people work in Microsoft Teams. The biggest org chart on earth – departments, approval chains, the manager and the manager's manager. Here's what we actually built for them: the first AI where the barrier to entry is zero. You don't learn it. You don't prompt it. You don't even have to understand what AI can do. You Mention Viktor like a coworker, and the finished work comes back. In fact, you don't even need to mention Viktor. Viktor makes everyone AI-native. No course, no manual, no learning curve – the value comes to you, you don't reach for it. That's the mission: bring our rebellious optimist to the people who need him most. The operators and managers buried inside big companies. The frontline. The ones who were never shown what this could actually do for them – until today. Workspaces are where agents belong. Not apps. Viktor is live in Microsoft Teams. $100 in credits to start, no card. The AI for the rest of us – now where the rest of us report to someone.
1:21

Excited to announce Viktor in Microsoft Teams. This week we crossed $20M in annualized revenue run rate. In Slack. One app, no sales team, no rollout. Now Viktor goes where the rest of the working world actually is. 320 million people work in Microsoft Teams. The biggest org chart on earth – departments, approval chains, the manager and the manager's manager. Here's what we actually built for them: the first AI where the barrier to entry is zero. You don't learn it. You don't prompt it. You don't even have to understand what AI can do. You Mention Viktor like a coworker, and the finished work comes back. In fact, you don't even need to mention Viktor. Viktor makes everyone AI-native. No course, no manual, no learning curve – the value comes to you, you don't reach for it. That's the mission: bring our rebellious optimist to the people who need him most. The operators and managers buried inside big companies. The frontline. The ones who were never shown what this could actually do for them – until today. Workspaces are where agents belong. Not apps. Viktor is live in Microsoft Teams. $100 in credits to start, no card. The AI for the rest of us – now where the rest of us report to someone.

Fryd Wiatrowski

689,842 次观看 • 1 个月前

An agency added $133,752 in new ARR in 30 days. No new hires. Just work that wasn't getting done before. We run an AI-focused X account testing tools and workflows that actually save teams real time, not just add more steps. Most AI tools stop after giving you an answer. We wanted to see what happened when you gave one actual work to do. We added Viktor to our Slack workspace and connected him to our existing tools. Instead of bouncing between apps, we handed him work directly inside the workspace our team already uses. He started producing real outputs, not just suggestions. We asked him to summarize this week's AI news. He came back with a structured briefing: biggest stories, why they matter, key takeaways, and a thread-ready digest, all posted directly into Slack. It felt less like chatting with an AI and more like handing work to a teammate. We also ran a workflow that normally means switching between several apps and manually stitching everything together. Viktor handled it in the same place our team already collaborates. Reports, summaries, deliverables, done. That's what makes him different. The value isn't better answers. It's an AI employee who executes work that would otherwise sit on someone's to-do list. Nico Torres, Founder of Authority Makers, saw it in month one: $133,752 in new ARR from outbound work Viktor ran that previously had no one running it. Tell me I'm wrong, but this is what a non-human hire actually looks like in practice. Get started free at Viktor. $100 in credits included, no card. #AIemployee #AIWorkflows #ProductivityTools Paid Partnership
0:24

An agency added $133,752 in new ARR in 30 days. No new hires. Just work that wasn't getting done before. We run an AI-focused X account testing tools and workflows that actually save teams real time, not just add more steps. Most AI tools stop after giving you an answer. We wanted to see what happened when you gave one actual work to do. We added Viktor to our Slack workspace and connected him to our existing tools. Instead of bouncing between apps, we handed him work directly inside the workspace our team already uses. He started producing real outputs, not just suggestions. We asked him to summarize this week's AI news. He came back with a structured briefing: biggest stories, why they matter, key takeaways, and a thread-ready digest, all posted directly into Slack. It felt less like chatting with an AI and more like handing work to a teammate. We also ran a workflow that normally means switching between several apps and manually stitching everything together. Viktor handled it in the same place our team already collaborates. Reports, summaries, deliverables, done. That's what makes him different. The value isn't better answers. It's an AI employee who executes work that would otherwise sit on someone's to-do list. Nico Torres, Founder of Authority Makers, saw it in month one: $133,752 in new ARR from outbound work Viktor ran that previously had no one running it. Tell me I'm wrong, but this is what a non-human hire actually looks like in practice. Get started free at Viktor. $100 in credits included, no card. #AIemployee #AIWorkflows #ProductivityTools Paid Partnership

Farlane

101,043 次观看 • 25 天前

lando talking about how special it feels for him to win constructors’ titles after starting with the team in tougher times and their dominance 🥹❤️‍🩹 “i mean another one is just a great thing. it's another constructor feels the same as the first, because to get the first was quite an achievement if you still look at where we were just three years ago. we've overtaken every team in terms of development. we've outdone them by a long way in terms of development, and in a time when it's almost harder to do than ever, with more restrictions and less wind tunnel time, all of those different things, budget cap, that's really been more in our favor over the last five years comparing to the budget that the other teams could run at. but in a time when it should be more difficult than ever to dominate, that's exactly what the team have done and given us, by a long way, the best car on the grid. i mean, it's always a very nice thing to say. every driver that gets to say that always puts a smile on your face. but we've also done very well as a team in terms of drivers between oscar and myself pushing each other and delivering every single weekend. and you don't see that on any other team. so i think we're also very proud of that as drivers. but for me, i've been with mclaren since i started. especially it was a very different time and different place then to where we are now. so that journey makes it more special to know the downs because that's a lot of what it was back then to see the rise that we've had to see the teamwork, the changes, the atmosphere difference and the leadership from zak, from andrea especially, has turned things around and made us as a team the best in the world. and that's something that many people don't ever get to say”
1:53

lando talking about how special it feels for him to win constructors’ titles after starting with the team in tougher times and their dominance 🥹❤️‍🩹 “i mean another one is just a great thing. it's another constructor feels the same as the first, because to get the first was quite an achievement if you still look at where we were just three years ago. we've overtaken every team in terms of development. we've outdone them by a long way in terms of development, and in a time when it's almost harder to do than ever, with more restrictions and less wind tunnel time, all of those different things, budget cap, that's really been more in our favor over the last five years comparing to the budget that the other teams could run at. but in a time when it should be more difficult than ever to dominate, that's exactly what the team have done and given us, by a long way, the best car on the grid. i mean, it's always a very nice thing to say. every driver that gets to say that always puts a smile on your face. but we've also done very well as a team in terms of drivers between oscar and myself pushing each other and delivering every single weekend. and you don't see that on any other team. so i think we're also very proud of that as drivers. but for me, i've been with mclaren since i started. especially it was a very different time and different place then to where we are now. so that journey makes it more special to know the downs because that's a lot of what it was back then to see the rise that we've had to see the teamwork, the changes, the atmosphere difference and the leadership from zak, from andrea especially, has turned things around and made us as a team the best in the world. and that's something that many people don't ever get to say”

ray

35,603 次观看 • 10 个月前

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!
1:37

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Harjot Gill

4,775,791 次观看 • 3 个月前

Mew : These days, I’ve been going to the gym a lot because the movie I’m currently shooting requires a strong physique. The upcoming projects I’ll be shooting also require it, so I've been working out frequently and playing sports too. 🗣️: How many projects are you shooting right now? Mew : Just shooting one project is already exhausting enough 😂 Yesterday, I went to Saraburi for shooting. The production van picked me up from home at 3 AM, we started shooting there at 6 AM, and I got home around 11 PM. 🗣️: So, you can't take on multiple filming projects at the same time anymore? Mew : I really can’t anymore. If I do multiple projects, I feel like I don’t have any time to rest or even work out. There was a time when I shot 2–3 projects one after another, and I had no time to go to the gym or do anything else. So I feel like shooting one project at a time is better. It helps me focus more too. Especially when shooting movies, every scene is very important, so I have to put a lot of work into it.
1:12

Mew : These days, I’ve been going to the gym a lot because the movie I’m currently shooting requires a strong physique. The upcoming projects I’ll be shooting also require it, so I've been working out frequently and playing sports too. 🗣️: How many projects are you shooting right now? Mew : Just shooting one project is already exhausting enough 😂 Yesterday, I went to Saraburi for shooting. The production van picked me up from home at 3 AM, we started shooting there at 6 AM, and I got home around 11 PM. 🗣️: So, you can't take on multiple filming projects at the same time anymore? Mew : I really can’t anymore. If I do multiple projects, I feel like I don’t have any time to rest or even work out. There was a time when I shot 2–3 projects one after another, and I had no time to go to the gym or do anything else. So I feel like shooting one project at a time is better. It helps me focus more too. Especially when shooting movies, every scene is very important, so I have to put a lot of work into it.

💞

16,692 次观看 • 2 个月前

Building your own AI team can cost $10,000+ before it produces anything useful. Then comes the infrastructure, integrations, millions of tokens, maintenance, and people needed to keep it running. Viktor just turned that entire model upside down. It gives B2B teams an AI workforce that lives inside Slack or Teams, connects with 3,000+ tools, and completes actual jobs across reporting, audits, campaigns, creative briefs, and outbound. You do not spend hours prompting it. You assign the job. Viktor creates the deliverable, posts it in the channel, waits for approval, and ships it. This is the gap almost every AI company missed. Everyone kept talking about intelligent agents, while businesses were still waiting for AI that could reliably do the work inside the systems they already use. Viktor is not selling the idea of an AI employee. It built one. An agency reportedly added $133,752 in new recurring revenue within its first 30 days using it, without hiring more people or adding a new service line. OpenClaw beater? Maybe. But the bigger story is that practical AI has finally started catching up with the promises. Try it free at Viktor. You get $100 in credits with no card required. Full link in my first reply (Paid Partnership by Viktor)
0:53

Building your own AI team can cost $10,000+ before it produces anything useful. Then comes the infrastructure, integrations, millions of tokens, maintenance, and people needed to keep it running. Viktor just turned that entire model upside down. It gives B2B teams an AI workforce that lives inside Slack or Teams, connects with 3,000+ tools, and completes actual jobs across reporting, audits, campaigns, creative briefs, and outbound. You do not spend hours prompting it. You assign the job. Viktor creates the deliverable, posts it in the channel, waits for approval, and ships it. This is the gap almost every AI company missed. Everyone kept talking about intelligent agents, while businesses were still waiting for AI that could reliably do the work inside the systems they already use. Viktor is not selling the idea of an AI employee. It built one. An agency reportedly added $133,752 in new recurring revenue within its first 30 days using it, without hiring more people or adding a new service line. OpenClaw beater? Maybe. But the bigger story is that practical AI has finally started catching up with the promises. Try it free at Viktor. You get $100 in credits with no card required. Full link in my first reply (Paid Partnership by Viktor)

Eyisha Zyer

61,517 次观看 • 22 天前

Mark Cuban says he thought Kyrie Irving was a “team killer” before they traded for him “Honestly, before I did the work, I thought he was a team killer. There was no point, no reason for me to talk to people about him. It was just like, hey, if he doesn't want to play when the Mavs come to town, great. If things don't work out on another team, great” “But when the opportunity to trade for him came, it was like, okay, let's do the work. Nico did the work. Jason Kidd knew him. It was like, ‘Okay, let me talk to folks.’ And when you talk to players, they loved him. Nobody had a bad word to say about Kyrie that ever stepped on the court” “To me, that was all we needed to know. Then from there, all the things you say, ‘What went wrong in Boston? What went wrong in Brooklyn?’ A lot of that is maturity, but a lot of it was circumstances too. How often is COVID going to hit” “What we learned was you just let Kyrie be Kyrie. He's got a heart of gold. He's got a huge heart and he wants to help people. It wasn't a hard decision”
1:06

Mark Cuban says he thought Kyrie Irving was a “team killer” before they traded for him “Honestly, before I did the work, I thought he was a team killer. There was no point, no reason for me to talk to people about him. It was just like, hey, if he doesn't want to play when the Mavs come to town, great. If things don't work out on another team, great” “But when the opportunity to trade for him came, it was like, okay, let's do the work. Nico did the work. Jason Kidd knew him. It was like, ‘Okay, let me talk to folks.’ And when you talk to players, they loved him. Nobody had a bad word to say about Kyrie that ever stepped on the court” “To me, that was all we needed to know. Then from there, all the things you say, ‘What went wrong in Boston? What went wrong in Brooklyn?’ A lot of that is maturity, but a lot of it was circumstances too. How often is COVID going to hit” “What we learned was you just let Kyrie be Kyrie. He's got a heart of gold. He's got a huge heart and he wants to help people. It wasn't a hard decision”

dank

235,377 次观看 • 1 个月前

Jensen Huang: "Nvidia runs 7,500,000 agents for 75,000 people." that's 100 AI workers for every human employee. he goes further than that. "for the very first time, we have useful AI." not AI that answers questions. AI that does the work. and he's not talking about people who occasionally prompt ChatGPT. he means people who actually run agents in parallel. most people don't know you can already do this. one button. one prompt. up to 300 agents working at the same time. it's called Kimi Agent Swarm. 100 CVs tailored to 100 job descriptions. one prompt. 40 research papers into a 100,000-word review. one prompt. 30 landing pages for 30 businesses. one prompt. $40,000-$100,000 worth of work. one sitting. full breakdown in the article below.
1:05:45

Jensen Huang: "Nvidia runs 7,500,000 agents for 75,000 people." that's 100 AI workers for every human employee. he goes further than that. "for the very first time, we have useful AI." not AI that answers questions. AI that does the work. and he's not talking about people who occasionally prompt ChatGPT. he means people who actually run agents in parallel. most people don't know you can already do this. one button. one prompt. up to 300 agents working at the same time. it's called Kimi Agent Swarm. 100 CVs tailored to 100 job descriptions. one prompt. 40 research papers into a 100,000-word review. one prompt. 30 landing pages for 30 businesses. one prompt. $40,000-$100,000 worth of work. one sitting. full breakdown in the article below.

Dep

11,924 次观看 • 2 个月前

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!
28:01

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!

JJ Englert

29,809 次观看 • 4 个月前

There is a massive advantage to hiring young people, and Shopify was the first company to figure it out, says Pragmatic Engineer's Gergely Orosz. "Shopify's Head of Engineering Farhan Thawar told me that he saw something interesting years back. Shopify was so early to AI. They got Copilot licenses for everyone, with no cost limit. But they didn't see many teams using it." "But there was this one team that was using it a lot more. There was an intern on the team. They onboarded the intern and gave the intern his two-week task and the intern was done in a day. And they're like, 'How did you do that?' He's like, 'Oh well I just used AI? What's next?'" "And suddenly the people on the team felt stupid, right? So they started to learn from the intern and use AI." "The next thing Farhan did was hire an intern for every single Shopify team. This is why Shopify had a thousand interns."
1:27

There is a massive advantage to hiring young people, and Shopify was the first company to figure it out, says Pragmatic Engineer's Gergely Orosz. "Shopify's Head of Engineering Farhan Thawar told me that he saw something interesting years back. Shopify was so early to AI. They got Copilot licenses for everyone, with no cost limit. But they didn't see many teams using it." "But there was this one team that was using it a lot more. There was an intern on the team. They onboarded the intern and gave the intern his two-week task and the intern was done in a day. And they're like, 'How did you do that?' He's like, 'Oh well I just used AI? What's next?'" "And suddenly the people on the team felt stupid, right? So they started to learn from the intern and use AI." "The next thing Farhan did was hire an intern for every single Shopify team. This is why Shopify had a thousand interns."

TBPN

135,588 次观看 • 6 个月前

Jeff Bezos explains the “releasing the work” framework he used to build Amazon In the early days of Amazon, Jeff Bezos had too many ideas. Then Jeff Wilke, a new Amazon executive at the time, told his boss, “Jeff, you have enough ideas to destroy Amazon.” “This was just a shocking idea for me,” Bezos recalls. “As a founder, I had the great luxury of always being able to hire my tutors. I would hire these experienced, senior executives . . . And I would listen to them and they would teach me.” When Bezos asked Wilke what he meant by this, Wilke responded, “You have to release the work at the right rate so that the organization can accept it.” Bezos reflects on this point: “Every time I released an idea, I was creating a backlog of work in process. And because it was just stacking up, it was adding no value. In fact, it was creating distraction . . . This sounds so obvious, but it was not obvious to me at the time. And this was a profound insight for me. So I started prioritizing the ideas better, keeping lists of them, and keeping ideas to myself until the organization was ready for the ideas.” He continues: “I also started figuring out how to build an organization that can be ready for more ideas. That’s about having the right senior team and leadership and giving those people the executive bandwidth so they could do more ideas per unit of time. And that is what we built. We built a company that’s very good at inventing and doing more than one thing at a time. And as the company gets bigger, you do want to be able to do more than one thing at a time. But that idea of ‘releasing the work’ was very profound for me. It made us operationally more effective while still being inventive.” Video source: Reuters (2025)
3:03

Jeff Bezos explains the “releasing the work” framework he used to build Amazon In the early days of Amazon, Jeff Bezos had too many ideas. Then Jeff Wilke, a new Amazon executive at the time, told his boss, “Jeff, you have enough ideas to destroy Amazon.” “This was just a shocking idea for me,” Bezos recalls. “As a founder, I had the great luxury of always being able to hire my tutors. I would hire these experienced, senior executives . . . And I would listen to them and they would teach me.” When Bezos asked Wilke what he meant by this, Wilke responded, “You have to release the work at the right rate so that the organization can accept it.” Bezos reflects on this point: “Every time I released an idea, I was creating a backlog of work in process. And because it was just stacking up, it was adding no value. In fact, it was creating distraction . . . This sounds so obvious, but it was not obvious to me at the time. And this was a profound insight for me. So I started prioritizing the ideas better, keeping lists of them, and keeping ideas to myself until the organization was ready for the ideas.” He continues: “I also started figuring out how to build an organization that can be ready for more ideas. That’s about having the right senior team and leadership and giving those people the executive bandwidth so they could do more ideas per unit of time. And that is what we built. We built a company that’s very good at inventing and doing more than one thing at a time. And as the company gets bigger, you do want to be able to do more than one thing at a time. But that idea of ‘releasing the work’ was very profound for me. It made us operationally more effective while still being inventive.” Video source: Reuters (2025)

Startup Archive

675,266 次观看 • 10 个月前

Matt Damon says Christopher Nolan's The Odyssey was so demanding that only one person visited the set in six months. Ben Affleck. "You were the only guest in six months of shooting." Damon says the reason was simple. "The workload was incredible." "It was such an ambitious project that there was no time for anything else." He called it the most demanding movie he's ever made. "I've never worked on a film that required every single person to give maximum effort." Then he put it into perspective. "Every location on that movie would've been the hardest location on any other movie I'd ever done." "And every day of work was harder than any day on any other movie I'd ever worked on." Even Ben Affleck joked that it reminded him of when they were kids, calling each other to ask: "So... what's it like shooting your movie?"
0:55

Matt Damon says Christopher Nolan's The Odyssey was so demanding that only one person visited the set in six months. Ben Affleck. "You were the only guest in six months of shooting." Damon says the reason was simple. "The workload was incredible." "It was such an ambitious project that there was no time for anything else." He called it the most demanding movie he's ever made. "I've never worked on a film that required every single person to give maximum effort." Then he put it into perspective. "Every location on that movie would've been the hardest location on any other movie I'd ever done." "And every day of work was harder than any day on any other movie I'd ever worked on." Even Ben Affleck joked that it reminded him of when they were kids, calling each other to ask: "So... what's it like shooting your movie?"

Nitesh

747,430 次观看 • 29 天前

lando about the DSQ: “from what i had to do in the race, there was already some expectation that it might happen. so it wasn't a shock, it wasn't a surprise. we knew we were having a lot more issues than we ever expected during the race and that led to already the expectation that some things might not be as we expect. maybe it would have hurt more if we won the race, but we didn't so it didn't change. it doesn't change anything. there's no point being too sad about it. of course everyone in the team was a bit gutted about the result because there's a lot of effort that goes into it. so yeah it's the same for everyone but like 0.1 millimeters or whatever, it's like a piece of paper. so it was frustrating but actually i was quite okay, just excited to go again this weekend. it doesn't change anything i want to try and win in qatar and try and win in abu dhabi. so yeah it sucks, but that's life sometimes”
1:03

lando about the DSQ: “from what i had to do in the race, there was already some expectation that it might happen. so it wasn't a shock, it wasn't a surprise. we knew we were having a lot more issues than we ever expected during the race and that led to already the expectation that some things might not be as we expect. maybe it would have hurt more if we won the race, but we didn't so it didn't change. it doesn't change anything. there's no point being too sad about it. of course everyone in the team was a bit gutted about the result because there's a lot of effort that goes into it. so yeah it's the same for everyone but like 0.1 millimeters or whatever, it's like a piece of paper. so it was frustrating but actually i was quite okay, just excited to go again this weekend. it doesn't change anything i want to try and win in qatar and try and win in abu dhabi. so yeah it sucks, but that's life sometimes”

ray

214,829 次观看 • 8 个月前

Every AI agent you've tried has amnesia. It does one task, forgets everything, and tomorrow you start from zero. That's not an employee. That's a temp you have to retrain every single morning. Hyperagent by Airtable is the first platform I've used that actually fixes this. Here's what got me: 1. Agents that compound. Each agent has memory. The one running today is smarter than the one you shipped three weeks ago. Same prompt, same integrations, but weeks of your judgment baked in. 2. Real deliverables, real receipts. You don't get a chat transcript. You get finished work with the cost and runtime printed right on it. A full research report for under ten bucks. Try getting that invoice from an agency. 3. A fleet, not a chatbot. Build a specialist for outreach, another for research, another for reporting. Give each one its own tools, its own memory, and its own budget cap so nothing runs away with your credits. 4. Deploy to Slack and your whole team uses the agent you built. One competitive intel agent, @ mentioned by everyone. Airtable runs its own data team this way. 5. Each agent gets its own cloud machine with a real browser and code execution. It works while you sleep. No babysitting, no local setup, no laptop that has to stay open. I put it to work in the video below. Watch what it builds. The teams treating agents as durable assets instead of one-off prompts are going to lap everyone else. This is the first tool that actually treats them that way. #ad Hyperagent
2:29

Every AI agent you've tried has amnesia. It does one task, forgets everything, and tomorrow you start from zero. That's not an employee. That's a temp you have to retrain every single morning. Hyperagent by Airtable is the first platform I've used that actually fixes this. Here's what got me: 1. Agents that compound. Each agent has memory. The one running today is smarter than the one you shipped three weeks ago. Same prompt, same integrations, but weeks of your judgment baked in. 2. Real deliverables, real receipts. You don't get a chat transcript. You get finished work with the cost and runtime printed right on it. A full research report for under ten bucks. Try getting that invoice from an agency. 3. A fleet, not a chatbot. Build a specialist for outreach, another for research, another for reporting. Give each one its own tools, its own memory, and its own budget cap so nothing runs away with your credits. 4. Deploy to Slack and your whole team uses the agent you built. One competitive intel agent, @ mentioned by everyone. Airtable runs its own data team this way. 5. Each agent gets its own cloud machine with a real browser and code execution. It works while you sleep. No babysitting, no local setup, no laptop that has to stay open. I put it to work in the video below. Watch what it builds. The teams treating agents as durable assets instead of one-off prompts are going to lap everyone else. This is the first tool that actually treats them that way. #ad Hyperagent

Leonard Rodman

94,961 次观看 • 24 天前

Elon Musk was asked what the economy looks like in ten years. He didn’t describe a boom or a crash. He gave a date. Musk: “Money won’t matter in 2036.” He isn’t predicting collapse. He’s predicting so much supply that accounting can no longer describe it. Musk: “You need the end effectors in the form of humanoid robotics.” End effectors. Hands. Every economy that ever existed was capped by the number of hands available and the hours inside them. That cap is most of human history. Famine was a hands problem. Empire was a hands problem. Slavery was the worst answer anyone ever gave to a hands problem. Musk: “you can go from intelligence manifesting itself only digitally to shaping atoms.” Intelligence has been stuck behind glass since the first computer. Every idea it ever had still needed human hands to carry it out. Musk: “you have a sort of a quasi-infinite economy.” The interesting part isn’t whether the abundance arrives. It’s what money turns out to have been. Not paper. Not a number in an app. A dollar is a claim on somebody else’s hours. Every price you ever paid was a bid on a piece of a stranger’s life. Every wage you ever earned was somebody bidding on yours. So “money won’t matter” is not a sentence about currency. It’s a sentence about need. If nobody has to buy your hours, the claim has nothing left to point at. Musk: “You want money for food, housing, transport, entertainment.” That list is accurate, and it is the smallest a person has ever been reduced to. A stomach and an address. Nobody has ever wanted only that. Under every paycheck was a second thing that never printed on the stub. Proof that a stranger somewhere needed something only you could give. The economy was the largest machine ever built for making strangers necessary to each other. The goods were the byproduct. Every ancestor of yours worked so the next one wouldn’t have to. Nobody ever wrote down what to do on the day someone finally didn’t. We already know what happens when the supply arrives and the necessity leaves. We have run it one person at a time for a century. The retired man with a full account and nothing waiting for him in the morning. The lottery winner who comes apart with every need met. Nobody in that condition was ever cured by more. Musk: “There’s no analogy or metaphor that I think illustrates the magnitude of change that we’re going to experience here.” He’s right, and it runs deeper than economics. Every era before this one organized itself around scarcity. Take scarcity out and there is nothing left to compare it to. Notice what abundance never touches. Anything that can be copied falls to zero. What remains is everything that can’t. Land. Rank. Being first. The attention of one specific person who could be spending it somewhere else. Abundance doesn’t kill money. It strips it down to the only things it was ever really buying. The goods, the services, the things we spent ten thousand years calling wealth, turn out to have been the easy part. So the question waiting in 2036 isn’t how you’ll get by. Provision is handled. It’s what you answer when nothing requires you and everything is given. Most of us were never chosen. We were needed, and needed was close enough to live on. That difference has never once been tested. Abundance is the test. Nothing will be missing. You will be.
1:53

Elon Musk was asked what the economy looks like in ten years. He didn’t describe a boom or a crash. He gave a date. Musk: “Money won’t matter in 2036.” He isn’t predicting collapse. He’s predicting so much supply that accounting can no longer describe it. Musk: “You need the end effectors in the form of humanoid robotics.” End effectors. Hands. Every economy that ever existed was capped by the number of hands available and the hours inside them. That cap is most of human history. Famine was a hands problem. Empire was a hands problem. Slavery was the worst answer anyone ever gave to a hands problem. Musk: “you can go from intelligence manifesting itself only digitally to shaping atoms.” Intelligence has been stuck behind glass since the first computer. Every idea it ever had still needed human hands to carry it out. Musk: “you have a sort of a quasi-infinite economy.” The interesting part isn’t whether the abundance arrives. It’s what money turns out to have been. Not paper. Not a number in an app. A dollar is a claim on somebody else’s hours. Every price you ever paid was a bid on a piece of a stranger’s life. Every wage you ever earned was somebody bidding on yours. So “money won’t matter” is not a sentence about currency. It’s a sentence about need. If nobody has to buy your hours, the claim has nothing left to point at. Musk: “You want money for food, housing, transport, entertainment.” That list is accurate, and it is the smallest a person has ever been reduced to. A stomach and an address. Nobody has ever wanted only that. Under every paycheck was a second thing that never printed on the stub. Proof that a stranger somewhere needed something only you could give. The economy was the largest machine ever built for making strangers necessary to each other. The goods were the byproduct. Every ancestor of yours worked so the next one wouldn’t have to. Nobody ever wrote down what to do on the day someone finally didn’t. We already know what happens when the supply arrives and the necessity leaves. We have run it one person at a time for a century. The retired man with a full account and nothing waiting for him in the morning. The lottery winner who comes apart with every need met. Nobody in that condition was ever cured by more. Musk: “There’s no analogy or metaphor that I think illustrates the magnitude of change that we’re going to experience here.” He’s right, and it runs deeper than economics. Every era before this one organized itself around scarcity. Take scarcity out and there is nothing left to compare it to. Notice what abundance never touches. Anything that can be copied falls to zero. What remains is everything that can’t. Land. Rank. Being first. The attention of one specific person who could be spending it somewhere else. Abundance doesn’t kill money. It strips it down to the only things it was ever really buying. The goods, the services, the things we spent ten thousand years calling wealth, turn out to have been the easy part. So the question waiting in 2036 isn’t how you’ll get by. Provision is handled. It’s what you answer when nothing requires you and everything is given. Most of us were never chosen. We were needed, and needed was close enough to live on. That difference has never once been tested. Abundance is the test. Nothing will be missing. You will be.

Dustin

39,098 次观看 • 13 天前