Kaitee's banner

Kaitee

@KaiteeShiks • 60,686 subscribers

Obsessed with how AI can actually grow a business, not just provide hype. I help founders and creators scale using digital strategy and better tools.

Shorts

Tried Gemini Omni on Buzzy earlier and the biggest difference isn’t the first generation. It’s the fact that the video remembers context while you keep editing it. Way closer to directing a scene than endlessly rerolling prompts.

Tried Gemini Omni on Buzzy earlier and the biggest difference isn’t the first generation. It’s the fact that the video remembers context while you keep editing it. Way closer to directing a scene than endlessly rerolling prompts.

17,654 views

Videos

Anya Rossi

sweetdream.ai

SweetDream.ai•Sponsored•Livecam

Watch Anya Live

Anya is streaming live right now! Join her private show and enjoy exclusive content.

Exclusive private shows

1.2k viewers online

Private Show

Join now for exclusive access

Free preview available • Premium content

One 12-page campaign brief became 3 distinct creator plans in about 2 minutes. Same campaign. Three different accounts. None of them could sound like a copy of the others. At first, I asked Viktor to summarize the brief. The summary was accurate, but it still left our team doing the difficult part: choosing separate angles, designing the demos, assigning responsibilities, checking the requirements, and making sure the posts did not overlap. So I changed the prompt and gave him the complete multi-creator rollout. Viktor created three separate campaign plans: One focused on creator operations. One focused on the creative workflow. One focused on team strategy and productivity. Each had its own hook, false start, screen-recording concept, story arc, captions, responsibilities, risks, and approval checklist. He mapped 42 requirements across the three placements, identified 14 missing details, and listed 9 actions that still needed human approval. Then I asked him to audit his own work. He caught a missing connection shot in one plan and raised the total risk count from 9 to 10 before we recorded anything. That part mattered more than getting a perfect answer on the first try. Content could see what needed to be written. Production had a shot list. Partnerships had the questions that needed clarification. Publishing had a checklist for everything that could block the posts. Viktor proposed the rollout. Our team still decides what gets approved and published. The result was three distinct creator campaigns planned from one 12-page brief in about 2 minutes. If an AI employee can plan the work and catch what he missed, where does assistance end and ownership begin? Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #CreatorOperations Paid Partnership

One 12-page campaign brief became 3 distinct creator plans in about 2 minutes. Same campaign. Three different accounts. None of them could sound like a copy of the others. At first, I asked Viktor to summarize the brief. The summary was accurate, but it still left our team doing the difficult part: choosing separate angles, designing the demos, assigning responsibilities, checking the requirements, and making sure the posts did not overlap. So I changed the prompt and gave him the complete multi-creator rollout. Viktor created three separate campaign plans: One focused on creator operations. One focused on the creative workflow. One focused on team strategy and productivity. Each had its own hook, false start, screen-recording concept, story arc, captions, responsibilities, risks, and approval checklist. He mapped 42 requirements across the three placements, identified 14 missing details, and listed 9 actions that still needed human approval. Then I asked him to audit his own work. He caught a missing connection shot in one plan and raised the total risk count from 9 to 10 before we recorded anything. That part mattered more than getting a perfect answer on the first try. Content could see what needed to be written. Production had a shot list. Partnerships had the questions that needed clarification. Publishing had a checklist for everything that could block the posts. Viktor proposed the rollout. Our team still decides what gets approved and published. The result was three distinct creator campaigns planned from one 12-page brief in about 2 minutes. If an AI employee can plan the work and catch what he missed, where does assistance end and ownership begin? Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #CreatorOperations Paid Partnership

36,870 views • 3 days ago

Nearly 3 hours of campaign planning recovered from one client brief. Viktor turned 7 pages into a complete execution plan in roughly 3 minutes. My first attempt did not work. I asked him to summarize the brief. The summary was accurate, but our team still had to turn it into deadlines, responsibilities, approvals, and next actions ourselves. That was the wrong way to delegate the work. So I changed the assignment and gave Viktor ownership of the complete campaign intake process. I uploaded a real client brief with every identifying detail permanently removed and asked him to prepare the work across partnerships, content, demo development, production, compliance, publishing, and reporting. He organized 29 deliverable and operational items, built the production timeline, separated responsibilities across 7 team functions, identified 14 information gaps, flagged 12 contradictions and risks, and prepared the approval queue. Partnerships can see what needs clarification. Content can see exactly what must be written. Production can see what needs to be recorded. Review can see every claim and restriction. Publishing can see every date, approval, disclosure, and reporting requirement. Viktor proposed the plan. Our team reviewed and approved it. That reduced around 3 hours of manual planning to roughly 3 minutes, with our team still controlling every external action. If an AI can turn a client brief into work the whole team can execute, is it still just helping? Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #CreatorOperations Paid Partnership

Nearly 3 hours of campaign planning recovered from one client brief. Viktor turned 7 pages into a complete execution plan in roughly 3 minutes. My first attempt did not work. I asked him to summarize the brief. The summary was accurate, but our team still had to turn it into deadlines, responsibilities, approvals, and next actions ourselves. That was the wrong way to delegate the work. So I changed the assignment and gave Viktor ownership of the complete campaign intake process. I uploaded a real client brief with every identifying detail permanently removed and asked him to prepare the work across partnerships, content, demo development, production, compliance, publishing, and reporting. He organized 29 deliverable and operational items, built the production timeline, separated responsibilities across 7 team functions, identified 14 information gaps, flagged 12 contradictions and risks, and prepared the approval queue. Partnerships can see what needs clarification. Content can see exactly what must be written. Production can see what needs to be recorded. Review can see every claim and restriction. Publishing can see every date, approval, disclosure, and reporting requirement. Viktor proposed the plan. Our team reviewed and approved it. That reduced around 3 hours of manual planning to roughly 3 minutes, with our team still controlling every external action. If an AI can turn a client brief into work the whole team can execute, is it still just helping? Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #CreatorOperations Paid Partnership

46,080 views • 9 days ago

I gave WorkBuddy one prompt: build a campaign dashboard I could actually use. It planned the app, created CreatorFlow, ran it locally, and tested it on my computer. The result is a working system for campaigns, approvals, deliverables, and payments. Built with Hy4 Preview.

I gave WorkBuddy one prompt: build a campaign dashboard I could actually use. It planned the app, created CreatorFlow, ran it locally, and tested it on my computer. The result is a working system for campaigns, approvals, deliverables, and payments. Built with Hy4 Preview.

57,125 views • 14 days ago

Seedance 2.5 is already available on CapCut, and Seedance 2.5 1080p is now live. But once AI starts generating more footage, manual editing becomes the next bottleneck. I’d batch-create assets with AI Image, turn them into different scenes with AI Video, then bring everything directly into the CapCut PC timeline. That’s where Edit Pilot comes in. Instead of repeating the same editing steps clip by clip, I can describe the changes I want and use conversational editing to handle repetitive modifications across selected footage. AI Edit handles local refinements, AI Extend gives scenes more time, and the multi-track timeline finishes captions, voiceover, color and export. More AI generation needs a smarter post-production workflow. #CapCutPC #AIVideoEditor #CapCutSeedance25 #Seedance251080p

Seedance 2.5 is already available on CapCut, and Seedance 2.5 1080p is now live. But once AI starts generating more footage, manual editing becomes the next bottleneck. I’d batch-create assets with AI Image, turn them into different scenes with AI Video, then bring everything directly into the CapCut PC timeline. That’s where Edit Pilot comes in. Instead of repeating the same editing steps clip by clip, I can describe the changes I want and use conversational editing to handle repetitive modifications across selected footage. AI Edit handles local refinements, AI Extend gives scenes more time, and the multi-track timeline finishes captions, voiceover, color and export. More AI generation needs a smarter post-production workflow. #CapCutPC #AIVideoEditor #CapCutSeedance25 #Seedance251080p

60,970 views • 24 days ago

Seedance 2.5 is already available in CapCut. Now Seedance 2.5 1080p is live too. I can already see this being useful for product content. One product image can become multiple angles, different environments and different shot sizes. Then instead of exporting everything and starting another editing workflow somewhere else, I can keep working in CapCut PC. Extend the scene with AI Extend, fix the awkward detail with AI Edit, and use Edit Pilot when there’s a pile of edits. 1080p gets you closer to the final look. The rest of the workflow gets you to the final video. #CapCutPC #AIVideoEditor #CapCutSeedance25 #Seedance251080p

Seedance 2.5 is already available in CapCut. Now Seedance 2.5 1080p is live too. I can already see this being useful for product content. One product image can become multiple angles, different environments and different shot sizes. Then instead of exporting everything and starting another editing workflow somewhere else, I can keep working in CapCut PC. Extend the scene with AI Extend, fix the awkward detail with AI Edit, and use Edit Pilot when there’s a pile of edits. 1080p gets you closer to the final look. The rest of the workflow gets you to the final video. #CapCutPC #AIVideoEditor #CapCutSeedance25 #Seedance251080p

67,213 views • 28 days ago

I ran one of my own React dashboards through Replay before treating it as ready to ship. It looked fine to me. Replay QA found a notifications button that looked completely functional but did nothing when clicked, accessibility issues across the UI, and a workflow where completing a task failed to update the activity feed. Those are exactly the little things that are easy to miss when you're focused on building. With Replay for Teams, this kind of QA can also run around your team's GitHub workflow and surface debugging context as you ship. The app can look finished in the editor. What matters is what actually happens in the browser. Replay for Teams is launching today. Check it out on Product Hunt:

I ran one of my own React dashboards through Replay before treating it as ready to ship. It looked fine to me. Replay QA found a notifications button that looked completely functional but did nothing when clicked, accessibility issues across the UI, and a workflow where completing a task failed to update the activity feed. Those are exactly the little things that are easy to miss when you're focused on building. With Replay for Teams, this kind of QA can also run around your team's GitHub workflow and surface debugging context as you ship. The app can look finished in the editor. What matters is what actually happens in the browser. Replay for Teams is launching today. Check it out on Product Hunt:

57,558 views • 25 days ago

Our launch decisions dropped from 3 days to 1. The workload stayed the same. The difference was what happened before our team logged in. We manage launches across content, partnerships, and operations. The problem was never a lack of information. It was getting the right context in front of everyone before a decision had to be made. At first, I treated Viktor like another assistant and kept giving him isolated tasks. That was the wrong approach. The moment it clicked was when our team gave him responsibility for the work surrounding each launch. He reviewed updates, organized pending approvals, surfaced blockers, and prepared the context before standup. Viktor proposed the next steps. Our team reviewed and approved them. Now, instead of spending three days gathering information across different people and conversations, we can often make the decision within one. 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 #FutureOfWork Paid Partnership

Our launch decisions dropped from 3 days to 1. The workload stayed the same. The difference was what happened before our team logged in. We manage launches across content, partnerships, and operations. The problem was never a lack of information. It was getting the right context in front of everyone before a decision had to be made. At first, I treated Viktor like another assistant and kept giving him isolated tasks. That was the wrong approach. The moment it clicked was when our team gave him responsibility for the work surrounding each launch. He reviewed updates, organized pending approvals, surfaced blockers, and prepared the context before standup. Viktor proposed the next steps. Our team reviewed and approved them. Now, instead of spending three days gathering information across different people and conversations, we can often make the decision within one. 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 #FutureOfWork Paid Partnership

52,018 views • 24 days ago

We increased the number of client projects our team could comfortably manage without adding another person. The bottleneck turned out to be coordination, not headcount. I work with a team that's constantly juggling campaigns, client work, and internal reviews across Slack. At first, I kept Viktor away from anything important. I thought he'd be useful for internal tasks, but I wasn't ready to trust him with live work. That turned out to be the wrong approach. Once we started giving him recurring responsibilities, everything changed. Now he prepares weekly reports, keeps track of outstanding work, surfaces issues before they become problems, and gets everything ready for review. The team stays in control. Every decision still goes through us. But we spend far less time organizing work and a lot more time moving it forward. That's when I realized we hadn't added another AI tool. We'd added capacity. Seats are for tools. Employees are priced on output. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #AgencyLife Paid Partnership.

We increased the number of client projects our team could comfortably manage without adding another person. The bottleneck turned out to be coordination, not headcount. I work with a team that's constantly juggling campaigns, client work, and internal reviews across Slack. At first, I kept Viktor away from anything important. I thought he'd be useful for internal tasks, but I wasn't ready to trust him with live work. That turned out to be the wrong approach. Once we started giving him recurring responsibilities, everything changed. Now he prepares weekly reports, keeps track of outstanding work, surfaces issues before they become problems, and gets everything ready for review. The team stays in control. Every decision still goes through us. But we spend far less time organizing work and a lot more time moving it forward. That's when I realized we hadn't added another AI tool. We'd added capacity. Seats are for tools. Employees are priced on output. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #AgencyLife Paid Partnership.

57,401 views • 1 month ago

Virality isn’t 1,000 people opening the same link. It’s 1,000 people making their own version. My friend needed a simple way to track small wins. One sentence into Eazo AI → 6 directions → one working app → live on the Feed. People don’t just like it. They can use it, change it, and publish their own version. Videos spread through sounds. Memes spread through templates. Playable content spreads through remix. The next post is an app. 🧵

Virality isn’t 1,000 people opening the same link. It’s 1,000 people making their own version. My friend needed a simple way to track small wins. One sentence into Eazo AI → 6 directions → one working app → live on the Feed. People don’t just like it. They can use it, change it, and publish their own version. Videos spread through sounds. Memes spread through templates. Playable content spreads through remix. The next post is an app. 🧵

48,953 views • 29 days ago

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 every day. That worked for a while. Until it didn't. The turning point wasn't asking Viktor better questions. It was giving him one recurring responsibility. Stay on top of every active project. Now he keeps track of progress, highlights anything that's stalled, prepares updates before meetings, and gives the team one place to review what actually needs attention. Nobody has to chase information anymore. The work is already organized before we start. That one change probably saved more time than any prompt I've ever written. 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 #Operations Paid Partnership.

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 every day. That worked for a while. Until it didn't. The turning point wasn't asking Viktor better questions. It was giving him one recurring responsibility. Stay on top of every active project. Now he keeps track of progress, highlights anything that's stalled, prepares updates before meetings, and gives the team one place to review what actually needs attention. Nobody has to chase information anymore. The work is already organized before we start. That one change probably saved more time than any prompt I've ever written. 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 #Operations Paid Partnership.

59,483 views • 1 month ago

I think we've been approaching AI web search the wrong way. Instead of searching for information... I tried assigning an entire research task. I built a Web Search Agent to track the biggest AI launches from the past week. Here's what happened.

I think we've been approaching AI web search the wrong way. Instead of searching for information... I tried assigning an entire research task. I built a Web Search Agent to track the biggest AI launches from the past week. Here's what happened.

58,149 views • 1 month ago

My AI app looked ready to ship. Replay QA proved otherwise. Before launching, I connected the GitHub repo to Replay QA, let it run through the app like a real user, and within a few minutes it surfaced issues I would've never noticed by manually clicking around. What I liked most wasn't just finding bugs. It showed exactly what happened in the browser, explained the likely root cause, and gave enough context to fix the issue without guessing. Instead of running a one-time check, I connected the repo so Replay QA can keep testing every time I push changes or open a PR. No Playwright setup. No complicated pipeline configuration. Just a practical QA gate before users ever find the problems. If you're building with Cursor, Claude Code, Codex, Lovable, Bolt, Replit, or any AI coding workflow, this is worth adding before your next launch. Replay

My AI app looked ready to ship. Replay QA proved otherwise. Before launching, I connected the GitHub repo to Replay QA, let it run through the app like a real user, and within a few minutes it surfaced issues I would've never noticed by manually clicking around. What I liked most wasn't just finding bugs. It showed exactly what happened in the browser, explained the likely root cause, and gave enough context to fix the issue without guessing. Instead of running a one-time check, I connected the repo so Replay QA can keep testing every time I push changes or open a PR. No Playwright setup. No complicated pipeline configuration. Just a practical QA gate before users ever find the problems. If you're building with Cursor, Claude Code, Codex, Lovable, Bolt, Replit, or any AI coding workflow, this is worth adding before your next launch. Replay

64,294 views • 1 month ago

In Partnership with Viktor. An agency added $133,752 in new annual recurring revenue in its first 30 days with Viktor. No new hires. No new service line.

In Partnership with Viktor. An agency added $133,752 in new annual recurring revenue in its first 30 days with Viktor. No new hires. No new service line.

74,596 views • 2 months ago

$Did this one on hard mode. two different camera systems intercut in the same 30 seconds, normal third-person following her, and the enemy's surveillance feed watching her. Most models just flatten that into one look. this kept them telling apart, which is the only reason i'm posting it. Rain plus neon is basically a reflection stress test and it survived. wet road, screen light bouncing off metal, digital grain in the smoke. prompt: A cyberpunk action film clip, montage, following a young hacker carrying an encrypted chip across a neon megacity while armed drones and corporate agents close in. Elevated roads, holographic ad districts, rainy back alleys, an underground market, a maglev station, a rooftop server room, the whole city under giant screens, cabling and steam. Dense cyberpunk cinematic look. Electric blue, magenta, fluorescent cyan, industrial black. Cold, sharp, highly reflective — rain, neon and screen light refracting into complex highlights on metal, digital grain and glitch scanning in the smoke. Cross-cut between third-person follow and enemy surveillance POV. Fast handheld, drone dives, whip pans, HUD inserts, quick push-ins, glitch transitions. Heavy bass electronic score, glitch noise, alarms, mechanical beeps, gunfire, footsteps in water. You can run the same thing at$

Did this one on hard mode. two different camera systems intercut in the same 30 seconds, normal third-person following her, and the enemy's surveillance feed watching her. Most models just flatten that into one look. this kept them telling apart, which is the only reason i'm posting it. Rain plus neon is basically a reflection stress test and it survived. wet road, screen light bouncing off metal, digital grain in the smoke. prompt: A cyberpunk action film clip, montage, following a young hacker carrying an encrypted chip across a neon megacity while armed drones and corporate agents close in. Elevated roads, holographic ad districts, rainy back alleys, an underground market, a maglev station, a rooftop server room, the whole city under giant screens, cabling and steam. Dense cyberpunk cinematic look. Electric blue, magenta, fluorescent cyan, industrial black. Cold, sharp, highly reflective — rain, neon and screen light refracting into complex highlights on metal, digital grain and glitch scanning in the smoke. Cross-cut between third-person follow and enemy surveillance POV. Fast handheld, drone dives, whip pans, HUD inserts, quick push-ins, glitch transitions. Heavy bass electronic score, glitch noise, alarms, mechanical beeps, gunfire, footsteps in water. You can run the same thing at

16,725 views • 16 days ago

Built a small research playground with Nimble API. You enter a prompt: → Research OpenAI competitors → Find AI startups in (Any country of your choice) → Analyze the AI coding agent market The app turns it into a structured research report with summaries, findings, and source cards. Here's the workflow 👇

Built a small research playground with Nimble API. You enter a prompt: → Research OpenAI competitors → Find AI startups in (Any country of your choice) → Analyze the AI coding agent market The app turns it into a structured research report with summaries, findings, and source cards. Here's the workflow 👇

35,212 views • 2 months ago

Every AI agent I've used has the same bug: It forgets everything. Not after a month. Sometimes after a single session. This week I tested Memanto, an open-source memory companion for AI agents, and it completely changed how I think about agent workflows. 👇 Moorcheh.ai #ad

Every AI agent I've used has the same bug: It forgets everything. Not after a month. Sometimes after a single session. This week I tested Memanto, an open-source memory companion for AI agents, and it completely changed how I think about agent workflows. 👇 Moorcheh.ai #ad

37,566 views • 3 months ago

@Profound is hosting what might become the first major Marketing Engineering hackathon on June 6 in NYC, and honestly, it feels like we’re watching the birth of an entirely new role in tech in real time. The marketers who can build. The engineers who understand distribution. The people replacing repetitive growth work with agents and systems. • $40K in prizes • Only 50 spots • Judges from Ramp, Stripe & MongoDB • Winners get an interview at Profound The challenge: Find a marketing workflow that’s impossible to scale manually, then build an agent/system to run it. What makes this interesting is it’s completely platform-agnostic. Everyone gets access to Profound, but you can also build with Cursor, Claude Code, Python, n8n, LangChain, raw APIs, or whatever stack you want. They’re judging the best build, not the tooling. Honestly feels less like a normal hackathon and more like the first public glimpse of what AI-native marketing teams will look like over the next few years. Apply:

@Profound is hosting what might become the first major Marketing Engineering hackathon on June 6 in NYC, and honestly, it feels like we’re watching the birth of an entirely new role in tech in real time. The marketers who can build. The engineers who understand distribution. The people replacing repetitive growth work with agents and systems. • $40K in prizes • Only 50 spots • Judges from Ramp, Stripe & MongoDB • Winners get an interview at Profound The challenge: Find a marketing workflow that’s impossible to scale manually, then build an agent/system to run it. What makes this interesting is it’s completely platform-agnostic. Everyone gets access to Profound, but you can also build with Cursor, Claude Code, Python, n8n, LangChain, raw APIs, or whatever stack you want. They’re judging the best build, not the tooling. Honestly feels less like a normal hackathon and more like the first public glimpse of what AI-native marketing teams will look like over the next few years. Apply:

42,468 views • 4 months ago

Most AI builders underestimate how expensive transcription becomes once their product starts scaling. For a lot of teams, speech-to-text quietly turns into one of the biggest infrastructure bills. Just tested **Velma Transcribe** from Modulate and the pricing is surprisingly low compared to typical STT APIs. If you're building: • voice agents • AI assistants • support bots transcription costs matter a lot. Velma claims dramatically lower pricing while still competing with models like Deepgram, ElevenLabs, and AssemblyAI. You can compare the models side by side here:

Most AI builders underestimate how expensive transcription becomes once their product starts scaling. For a lot of teams, speech-to-text quietly turns into one of the biggest infrastructure bills. Just tested Velma Transcribe from Modulate and the pricing is surprisingly low compared to typical STT APIs. If you're building: • voice agents • AI assistants • support bots transcription costs matter a lot. Velma claims dramatically lower pricing while still competing with models like Deepgram, ElevenLabs, and AssemblyAI. You can compare the models side by side here:

50,886 views • 6 months ago

Most AI Agents can Talk..... Very few can actually do anything. You can spin up an agent in minutes… but the second you want it to: 🔴 Create a GitHub issue ⚪ Update Notion 🟡 Send a Slack message 🔵 Log actions properly 🟣 Handle auth securely You’re suddenly building integrations for weeks. This is why Merge Agent Handler caught my attention. It gives your AI agent real tool access across thousands of platforms through one integration, but the part I actually care about is this: Production-ready security + full audit logs out of the box. You can see every tool call. Every API request. Every response. So your agent isn’t just “connected”..... it’s monitored and controlled. If you’re building agents that need to take real actions, this is worth looking at: Video shows it in action 👇

Most AI Agents can Talk..... Very few can actually do anything. You can spin up an agent in minutes… but the second you want it to: 🔴 Create a GitHub issue ⚪ Update Notion 🟡 Send a Slack message 🔵 Log actions properly 🟣 Handle auth securely You’re suddenly building integrations for weeks. This is why Merge Agent Handler caught my attention. It gives your AI agent real tool access across thousands of platforms through one integration, but the part I actually care about is this: Production-ready security + full audit logs out of the box. You can see every tool call. Every API request. Every response. So your agent isn’t just “connected”..... it’s monitored and controlled. If you’re building agents that need to take real actions, this is worth looking at: Video shows it in action 👇

49,963 views • 6 months ago

Here is why Nimble has 1.1M Claude plugin installs… I tested the Nimble Studio for a few minutes and immediately understood the appeal. Instead of manually scraping sites or fighting APIs, Nimble lets AI agents pull structured live data from platforms like TikTok, YouTube, Instagram, Reddit, and more. I tried pulling trending AI tool content and it turned messy social pages into a clean dataset almost instantly, complete with engagement metrics, creators, hashtags, and trends. The interesting part is how natural it feels. You’re basically giving AI agents the ability to interact with live web data in a usable format instead of static search results. That’s why the 1.1M installs matter. It solves a real problem for developers, researchers, marketers, and teams building AI workflows around real-time internet data.

Here is why Nimble has 1.1M Claude plugin installs… I tested the Nimble Studio for a few minutes and immediately understood the appeal. Instead of manually scraping sites or fighting APIs, Nimble lets AI agents pull structured live data from platforms like TikTok, YouTube, Instagram, Reddit, and more. I tried pulling trending AI tool content and it turned messy social pages into a clean dataset almost instantly, complete with engagement metrics, creators, hashtags, and trends. The interesting part is how natural it feels. You’re basically giving AI agents the ability to interact with live web data in a usable format instead of static search results. That’s why the 1.1M installs matter. It solves a real problem for developers, researchers, marketers, and teams building AI workflows around real-time internet data.

28,590 views • 3 months ago