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RIP Zapier AI agents now operate inside your actual workflows, Notion, Slack, Discord, whatever. I spun one up to turn Slack threads into docs, summaries, and tasks fully automated. Absolutely cracked. 5 powerful examples + Link to try:

Robin Delta

87,065 subscribers

46,686 次观看 • 1 年前 •via X (Twitter)

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RIP operations team. AI agents now live inside Gmail, Discord, Slack or HubSpot... reading emails, filing tickets, answering questions & triggering workflows. You don’t need to code anything. Here’s how to build & deploy one in 5 mins: 🧵

RIP operations team. AI agents now live inside Gmail, Discord, Slack or HubSpot... reading emails, filing tickets, answering questions & triggering workflows. You don’t need to code anything. Here’s how to build & deploy one in 5 mins: 🧵

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🔥 Introducing Skywork Mobile App 5.0—the world’s first native mobile app for Super AI Agents. - Meet VoiceNotes: Turn a single voice memo into clean summaries, transcripts, and visual notes. - Super Agent: Carry a crew of expert minds in your pocket. Run up to 3 expert agents in parallel to tackle complex tasks instantly. Skywork App 5.0 is now available for both iOS and Android.

Skywork

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I compiled 200+ n8n automation templates you can copy & paste into your business or sell to other companies. Just straight plug-and-play systems for: – Lead gen -Content creation – Email outreach – CRM updates – AI workflows – Slack/Discord bots …and more. Follow + Reply “n8n” and I’ll send it over. This is completely FREE. Don't even want your email.

I compiled 200+ n8n automation templates you can copy & paste into your business or sell to other companies. Just straight plug-and-play systems for: – Lead gen -Content creation – Email outreach – CRM updates – AI workflows – Slack/Discord bots …and more. Follow + Reply “n8n” and I’ll send it over. This is completely FREE. Don't even want your email.

Damian Player

9,135,509 次观看 • 1 年前

Today we're introducing Slite as the first self-maintaining Knowledge Base Your wiki docs go outdated everyday, and your agents depend on them for your most ambitious workflows. Slite monitors your docs' accuracy from all other work tools (slack, jira, linear, codebase, etc) while you sleep and updates them. It even directly talks to your AI agents to give them accurate context without burning their context window or tool calls. You've been trying to build this 'company brain' for months now with hacky MVPs This is the final version of what you need, already built to be collaborative, headless, and secure. Check it out and HMU if you need this for your team, I'll be running personal onboardings for the next few days!

Today we're introducing Slite as the first self-maintaining Knowledge Base Your wiki docs go outdated everyday, and your agents depend on them for your most ambitious workflows. Slite monitors your docs' accuracy from all other work tools (slack, jira, linear, codebase, etc) while you sleep and updates them. It even directly talks to your AI agents to give them accurate context without burning their context window or tool calls. You've been trying to build this 'company brain' for months now with hacky MVPs This is the final version of what you need, already built to be collaborative, headless, and secure. Check it out and HMU if you need this for your team, I'll be running personal onboardings for the next few days!

Christophe Pasquier 🇺🇦

17,796 次观看 • 1 个月前

Postman's AI-readiness Playbook is one of the most important documents you can read today as a developer! We are headed into an era where every website must be "Agent-ready". - Agents will make purchases, not humans. - Agents will find the best options, not humans. - Agents will fill out job applications, not humans. The same applies to APIs. While human devs can hustle through poor docs and broken endpoints, most Agents can’t (yet). They need: - Predictable structures - Machine-readable metadata - Standardized behavior Postman's 90-day AI readiness playbook details how to turn your APIs into reliable, AI-ready tools. My two biggest takeaways from the Playbook: 1) Automatic documentation (Week 3): Once you standardize your API format, Postman’s Spec Hub automatically generates and validates API docs for both humans and AI agents without any manual work. 2) Seamless AI tooling (Week 9): Turn your validated specs into hosted, function-style endpoints, letting AI agents invoke your APIs like native commands. Find the link to the Playbook in the comments. Thanks to the Postman team for partnering on today's post!

Postman's AI-readiness Playbook is one of the most important documents you can read today as a developer! We are headed into an era where every website must be "Agent-ready". - Agents will make purchases, not humans. - Agents will find the best options, not humans. - Agents will fill out job applications, not humans. The same applies to APIs. While human devs can hustle through poor docs and broken endpoints, most Agents can’t (yet). They need: - Predictable structures - Machine-readable metadata - Standardized behavior Postman's 90-day AI readiness playbook details how to turn your APIs into reliable, AI-ready tools. My two biggest takeaways from the Playbook: 1) Automatic documentation (Week 3): Once you standardize your API format, Postman’s Spec Hub automatically generates and validates API docs for both humans and AI agents without any manual work. 2) Seamless AI tooling (Week 9): Turn your validated specs into hosted, function-style endpoints, letting AI agents invoke your APIs like native commands. Find the link to the Playbook in the comments. Thanks to the Postman team for partnering on today's post!

Avi Chawla

22,830 次观看 • 1 年前

Every new thing launched at ZapConnect: First up: Unified Copilot. Type what you want, and it builds across Zaps, Tables, Interfaces, and Agents: - Workflows in minutes (not days) - Context flows everywhere (no rework) - AI does the wiring so you focus on strategy (Try it here: We also shipped: 1. Human-in-the-loop 2. Over 30 new AI apps: Perplexity, Mistral, Cursor, DeepSeek + more 3. Agent Sharing: Build once, deploy to your whole org 4. Enterprise controls your IT team will actually like Oh and Tables + Interfaces are now included in every Zapier plan. Missed the event? Replay’s up now.

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Wade Foster

21,348 次观看 • 10 个月前

most people open Claude every morning and re-explain their entire life. every. single. time. then I built 7 layers that remember everything: Layer 1: tell Claude who I am, once Layer 2: build separate brains for separate work Layer 3: turn on memory so it learns me Layer 4: upload 5 writing samples so it sounds like me Layer 5: dump my world into project files Layer 6: connect Gmail, Calendar, Drive, Slack Layer 7: schedule tasks that run while I sleep 60 minutes to set up. spread across one week. now Claude finishes my sentences. knows which client I mean from one word. catches mistakes I'd miss. it's not a chatbot anymore. it's a personal AI that knows me better than most coworkers do. your AI doesn't know you yet. this article fixes that.

most people open Claude every morning and re-explain their entire life. every. single. time. then I built 7 layers that remember everything: Layer 1: tell Claude who I am, once Layer 2: build separate brains for separate work Layer 3: turn on memory so it learns me Layer 4: upload 5 writing samples so it sounds like me Layer 5: dump my world into project files Layer 6: connect Gmail, Calendar, Drive, Slack Layer 7: schedule tasks that run while I sleep 60 minutes to set up. spread across one week. now Claude finishes my sentences. knows which client I mean from one word. catches mistakes I'd miss. it's not a chatbot anymore. it's a personal AI that knows me better than most coworkers do. your AI doesn't know you yet. this article fixes that.

Nav Toor

62,350 次观看 • 2 个月前

just unlocked the deepest vault of n8n automations on the internet - and you can get them for free. I had my VA scrape and sort every useful n8n repo on the internet by hand.. and I'm now sitting on a clean, categorized directory of 1500+ workflows inside the vault you'll find: – RAG analysis & AI research flows – lead scoring and CRM updates, fully automated – inventory management flows – content repurposing schedulers – Airtable/Notion/GPT mega-integrations all plug-and-play want access to the repo + organized vault? Like + comment “REPO” + repost (must be following so I can DM you)

just unlocked the deepest vault of n8n automations on the internet - and you can get them for free. I had my VA scrape and sort every useful n8n repo on the internet by hand.. and I'm now sitting on a clean, categorized directory of 1500+ workflows inside the vault you'll find: – RAG analysis & AI research flows – lead scoring and CRM updates, fully automated – inventory management flows – content repurposing schedulers – Airtable/Notion/GPT mega-integrations all plug-and-play want access to the repo + organized vault? Like + comment “REPO” + repost (must be following so I can DM you)

J.B.

174,073 次观看 • 1 年前

Still using AI tools that can’t turn your ideas into real apps? Most tools can write bits of code but fail when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I just asked Replit: “can you redesign this website in professional way.." In minutes, it built the entire website— clean design, full logic, animations, and dark/light mode included. No setup. No debugging. Just pure vibe coding. Here’s why Replit stands out 👇 ✅ Build with plain English – Describe what you want, Replit builds it. ✅ All-in-one platform – Code, AI help, hosting, database, and auth in one place. ✅ Create anywhere – Use the Replit mobile app on iOS or Android. ✅ Instant integrations – Connect to Notion, Slack, Google Drive, Dropbox, and more. ✅ From design to live app – Import from Figma and launch in minutes. No chaos. No micromanaging. Just you, your idea, and Replit doing the hard work. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my link: #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore

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Fakhr

24,152 次观看 • 8 个月前

Most keyboard apps are built just to help you type faster. Acti is the world’s first agentic keyboard. It can actually do things for you. I have been using it for a while, and I literally love this one. Let’s say you are chatting with someone and they say: “Let’s meet at XYZ Place” Normally you would open Maps, search the location, copy the link, come back to app, and send it. With Acti, you just stay inside app, copy the text + hold the spacebar, and it adds the location + map link directly in the chat. This works inside WhatsApp, Telegram, Discord, Slack, or basically any chat interface. More use cases 👇 1/5

Most keyboard apps are built just to help you type faster. Acti is the world’s first agentic keyboard. It can actually do things for you. I have been using it for a while, and I literally love this one. Let’s say you are chatting with someone and they say: “Let’s meet at XYZ Place” Normally you would open Maps, search the location, copy the link, come back to app, and send it. With Acti, you just stay inside app, copy the text + hold the spacebar, and it adds the location + map link directly in the chat. This works inside WhatsApp, Telegram, Discord, Slack, or basically any chat interface. More use cases 👇 1/5

AshutoshShrivastava

15,873 次观看 • 1 个月前

Helmor has been out as an open-source coding agent orchestrator for less than a week, and we’re already close to 1,000 GitHub stars!!! As a little gift, we shipped a new feature you’re going to love. 👇 Stop copy-pasting GitHub links, Linear tickets, Slack threads, and random notes into prompts. We're tired of rebuilding context every time I ask an agent to do work. Contexts in Helmor is another step toward a local dev loop: browse, preview, inject context, and dispatch tasks without leaving the app. Before you start a task, Helmor should help you gather the right context first. Try the open-source Helmor — link in the comments. #Helmor

Helmor has been out as an open-source coding agent orchestrator for less than a week, and we’re already close to 1,000 GitHub stars!!! As a little gift, we shipped a new feature you’re going to love. 👇 Stop copy-pasting GitHub links, Linear tickets, Slack threads, and random notes into prompts. We're tired of rebuilding context every time I ask an agent to do work. Contexts in Helmor is another step toward a local dev loop: browse, preview, inject context, and dispatch tasks without leaving the app. Before you start a task, Helmor should help you gather the right context first. Try the open-source Helmor — link in the comments. #Helmor

Caspian 東澔

10,805 次观看 • 2 个月前

GOODBYE TO CYBERSECURITY! Someone just open-sourced an arsenal of AI hacking tools. Not one. Not ten. Hundreds. Inside the repository: • Jailbreak frameworks for LLMs • Prompt injection testing tools • AI red team agents • Model extraction utilities • Supply chain attack demos • Automated AI pentesting frameworks These are the same categories of tools security researchers use to find vulnerabilities before attackers do. Now anyone can study them. That's both exciting... and terrifying. The biggest threat to AI isn't smarter models. It's insecure ones. If you're building with LLMs and you're not actively testing your prompts, agents, and infrastructure— You're probably shipping vulnerabilities you don't even know exist. Open source is accelerating AI. It's also accelerating AI attacks. Repository link in the comments ↓

GOODBYE TO CYBERSECURITY! Someone just open-sourced an arsenal of AI hacking tools. Not one. Not ten. Hundreds. Inside the repository: • Jailbreak frameworks for LLMs • Prompt injection testing tools • AI red team agents • Model extraction utilities • Supply chain attack demos • Automated AI pentesting frameworks These are the same categories of tools security researchers use to find vulnerabilities before attackers do. Now anyone can study them. That's both exciting... and terrifying. The biggest threat to AI isn't smarter models. It's insecure ones. If you're building with LLMs and you're not actively testing your prompts, agents, and infrastructure— You're probably shipping vulnerabilities you don't even know exist. Open source is accelerating AI. It's also accelerating AI attacks. Repository link in the comments ↓

Shruti Codes

119,763 次观看 • 8 天前

Today we're shipping the governance layer enterprise AI was missing. Every organization running AI at scale faces the same choice: turn off AI connections to tools entirely, or let agents have full access to everything. Today we're launching a better path: precise control over connections, actions, and models across every surface. The goal is simple: IT gets visibility and control, teams keep building, no approval queue in between. 6 new capabilities in Zapier today: 1. Action restrictions at the endpoint level 2. Managed app connections with domain control 3. Bring your own model through AWS Bedrock 4. A queryable audit trail 5. Agents GA with MCP governed across every surface 6. Workspaces (GA later this quarter) One set of rules for your entire AI stack. Try it now. If you've had early access, let me know what you think.

Today we're shipping the governance layer enterprise AI was missing. Every organization running AI at scale faces the same choice: turn off AI connections to tools entirely, or let agents have full access to everything. Today we're launching a better path: precise control over connections, actions, and models across every surface. The goal is simple: IT gets visibility and control, teams keep building, no approval queue in between. 6 new capabilities in Zapier today: 1. Action restrictions at the endpoint level 2. Managed app connections with domain control 3. Bring your own model through AWS Bedrock 4. A queryable audit trail 5. Agents GA with MCP governed across every surface 6. Workspaces (GA later this quarter) One set of rules for your entire AI stack. Try it now. If you've had early access, let me know what you think.

Wade Foster

32,542 次观看 • 3 个月前

I've been personally burning through billions of tokens a week for the past few months as a builder. Today I'm excited to announce Hyperagent, by Airtable. An agents platform where every session gets its own isolated, full computing environment in the cloud — no Mac Mini required. Real browser, code execution, image/video generation, data warehouse access, hundreds of integrations, and the ability to learn any new API as a skill. Deep domain expertise through skill learning. Teach the agent how your firm evaluates startups or how your team runs due diligence — now anyone on the team gets output that reflects your actual methodology, not a generic template. One-click deployment into Slack as intelligent coworkers. These aren't bots that wait to be Mentioned — they follow conversations, understand context, and act when relevant. And a command center to oversee and continuously improve your entire fleet of agents at scale. We're onboarding early users now.

I've been personally burning through billions of tokens a week for the past few months as a builder. Today I'm excited to announce Hyperagent, by Airtable. An agents platform where every session gets its own isolated, full computing environment in the cloud — no Mac Mini required. Real browser, code execution, image/video generation, data warehouse access, hundreds of integrations, and the ability to learn any new API as a skill. Deep domain expertise through skill learning. Teach the agent how your firm evaluates startups or how your team runs due diligence — now anyone on the team gets output that reflects your actual methodology, not a generic template. One-click deployment into Slack as intelligent coworkers. These aren't bots that wait to be Mentioned — they follow conversations, understand context, and act when relevant. And a command center to oversee and continuously improve your entire fleet of agents at scale. We're onboarding early users now.

Howie Liu

13,805,163 次观看 • 5 个月前

Increasingly, HTML Artifacts are becoming a core part of how I work with AI agents. Long-horizon agent sessions need a better way to surface insights about what work it has done. This may not be obvious right now, but as you start to let your agent work on dynamic workflows, large codebases, long-running loops (e.g., using /goal), and deep research tasks, you need a good way to present results. Chat window is not it. You also don't want to just trust everything the agents do. Artifacts help provide an important verification layer, which in turn enables important decision-making. I like HTML artifacts because I can just ask the agent to produce as many of them (and in whatever form) as I need to verify the work and make sense out of everything. I even built a nice tab system for my artifacts. They are great for continual learning and research. I use HTML artifacts for logging, tracking experiments, brainstorming, managing my inbox, code reviews, agent session management, deep research, writing, reading, and so much more. I believe Andrej Karpathy wrote about this somewhere: As we move on to more advanced applications of AI agents and outputs get more complex, we will start to find the need for even more advanced forms of interactions with AI, including interactive neural videos/simulations.

Increasingly, HTML Artifacts are becoming a core part of how I work with AI agents. Long-horizon agent sessions need a better way to surface insights about what work it has done. This may not be obvious right now, but as you start to let your agent work on dynamic workflows, large codebases, long-running loops (e.g., using /goal), and deep research tasks, you need a good way to present results. Chat window is not it. You also don't want to just trust everything the agents do. Artifacts help provide an important verification layer, which in turn enables important decision-making. I like HTML artifacts because I can just ask the agent to produce as many of them (and in whatever form) as I need to verify the work and make sense out of everything. I even built a nice tab system for my artifacts. They are great for continual learning and research. I use HTML artifacts for logging, tracking experiments, brainstorming, managing my inbox, code reviews, agent session management, deep research, writing, reading, and so much more. I believe Andrej Karpathy wrote about this somewhere: As we move on to more advanced applications of AI agents and outputs get more complex, we will start to find the need for even more advanced forms of interactions with AI, including interactive neural videos/simulations.

elvis

36,881 次观看 • 2 个月前

Hermes Agent + Higgsfield Marketing Studio = AI UGC Content Factory I built a fully automated system inside Higgsfield that repurposes, localizes, and launches winning TikTok Shop content across hundreds of creator-style accounts. It's so effective it feels like running Facebook ads in 2008. No actors. No products in hand. No ghost creators. Just viral TikTok Shop sales - 24/7. The results speak louder than any pitch: • CPMs as low as $0.10 • 550+ cinematic, product-ready ads per day from a single prompt • 100 hooks tested in the time it used to take to test 10 • $100/mo replacing a $50k+ creative budget Here's the full pipeline - all native inside Higgsfield Marketing Studio: > Hermes Agent analyzes your product, scrapes Meta Ads + TikTok Ads, identifies winning content, and localizes every angle to your brand. > Seedance 2.0 turns data into AI UGC ads - captions, pacing, hooks, your website showcase, all auto-edited inside Higgsfield Marketing Studio. > AI UGC personas are spun up with realistic faces, voices, and personalities - cloned voiceovers in seconds. > Our phone farm pushes every finished video straight to TikTok Shop, daily, on autopilot. >No setup. No switching between five tools. Everything lives inside Higgsfield Marketing Studio. Here's how it actually runs: Hermes Agent researches the niche, scrapes winning TikTok Shop videos, and rebuilds them with fresh hooks, angles, and UGC visuals tailored to your brand. Agents create and post daily to affiliate accounts - fully automated. Then we activate the MPS (Multi-Platform Swarm): once a concept wins on TikTok Shop, Higgsfield deploys hundreds of AI Agents to flood the niche with variations that all drive back to our shot. Most brands are still paying $300–$500 per video. Testing 10 hooks costs $5,000 and takes three weeks. With this system, we test 100 hooks in the same timeframe - and the winners scale automatically. TikTok doesn't reward the best video. It rewards the brand that shows up the most - with content that converts. The brands automating content at scale will be the biggest winners of 2026.

Noah Frydberg | Tiktok Shop For Brands

27,037 次观看 • 3 个月前

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)

Tyler

24,994 次观看 • 1 年前

We were tracking 50+ campaigns manually. Viktor turned it into one report in minutes. We skipped a project coordinator hire. We're a 12-person team managing 140+ AI and tech creators. For months, campaign tracking meant someone on the team manually checking spreadsheets, chasing creators over DM, and pulling together a status update before every client call. It worked, but it was the kind of work that quietly ate hours nobody had to spare. We tried solving it by splitting the work across the team. That just meant more people spending time on the same repetitive problem instead of one. Then we gave Viktor one job: own the campaign tracker. Pull status across all active campaigns, flag what's overdue, what's pending approval, what needs a payment follow-up, and what's coming up next. Post it directly into our Slack workspace before the week starts. Inside Slack, Viktor flagged overdue tasks, pending approvals, payment follow-ups, and upcoming deadlines. All from one report, posted directly into our workspace. Everything stayed read-only. Nothing was edited or sent without approval. The team stopped spending the first hour of every Monday piecing together what was happening across 50+ campaigns. That time went back to the work that actually moves clients forward. The teams still tracking this in spreadsheets are one missed deadline away from a client conversation they don't want to have. 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 #CreatorMarketing #CampaignOps Paid Partnership

We were tracking 50+ campaigns manually. Viktor turned it into one report in minutes. We skipped a project coordinator hire. We're a 12-person team managing 140+ AI and tech creators. For months, campaign tracking meant someone on the team manually checking spreadsheets, chasing creators over DM, and pulling together a status update before every client call. It worked, but it was the kind of work that quietly ate hours nobody had to spare. We tried solving it by splitting the work across the team. That just meant more people spending time on the same repetitive problem instead of one. Then we gave Viktor one job: own the campaign tracker. Pull status across all active campaigns, flag what's overdue, what's pending approval, what needs a payment follow-up, and what's coming up next. Post it directly into our Slack workspace before the week starts. Inside Slack, Viktor flagged overdue tasks, pending approvals, payment follow-ups, and upcoming deadlines. All from one report, posted directly into our workspace. Everything stayed read-only. Nothing was edited or sent without approval. The team stopped spending the first hour of every Monday piecing together what was happening across 50+ campaigns. That time went back to the work that actually moves clients forward. The teams still tracking this in spreadsheets are one missed deadline away from a client conversation they don't want to have. 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 #CreatorMarketing #CampaignOps Paid Partnership

Nova Reid

103,707 次观看 • 10 天前

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Mike Futia

50,112 次观看 • 5 个月前

We just dropped a game-changer to slash your Gemini API costs 🤯 Yesterday we launched Gemini Context Caching, saving you up to 70% on your bill 💸💸 Here's how it works. Gemini let’s you add powerful AI models to create apps like: 📧 Email apps that summarize entire threads for you 💃 Storytelling apps that write the next chapter 💼 HR chatbots that actually understand your company's policies To make these apps, you need to repeatedly send Gemini instructions, which can be pricy. But through the integration of research, software and chips came a breakthrough; 🤖 Context Caching Just tell Google what you want to save money on and we'll take care of the rest. It’s an industry first and it’s going to be a big deal. I'm so proud of the team for always putting developers first 🙌 Cost is always a huge part of the equation and we keep making it better. Try Gemini Context Caching now and tell us what you think! Docs link is below. #AI #LLM #Gemini

We just dropped a game-changer to slash your Gemini API costs 🤯 Yesterday we launched Gemini Context Caching, saving you up to 70% on your bill 💸💸 Here's how it works. Gemini let’s you add powerful AI models to create apps like: 📧 Email apps that summarize entire threads for you 💃 Storytelling apps that write the next chapter 💼 HR chatbots that actually understand your company's policies To make these apps, you need to repeatedly send Gemini instructions, which can be pricy. But through the integration of research, software and chips came a breakthrough; 🤖 Context Caching Just tell Google what you want to save money on and we'll take care of the rest. It’s an industry first and it’s going to be a big deal. I'm so proud of the team for always putting developers first 🙌 Cost is always a huge part of the equation and we keep making it better. Try Gemini Context Caching now and tell us what you think! Docs link is below. #AI #LLM #Gemini

Liam Bolling

124,644 次观看 • 2 年前