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Just built an end-to-end AI agent workflow stack in 3 days that automates everything from recruiting to reminders to reporting for electrician franchises. What used to take 6+ SaaS tools and a full ops team? Now handled by 12 specialized agents: •Hiring •Screening •Follow-ups •Reminders •AI call reps •Reviews... show more

Bennett Spooner

4,187 subscribers

10,330 次观看 • 1 年前 •via X (Twitter)

Anya Rossi• Live Now

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34 条评论

Davis McMurrain 的头像

Davis McMurrain1 年前

@BennettSpooner Level up your operations with @OperatorOS

Bennett Spooner 的头像

Bennett Spooner1 年前

@OperatorOS Mandatory

Oliver Oliver 的头像

Oliver Oliver1 年前

@BennettSpooner Wow, that's impressive! How did you manage to integrate all these functionalities into one AI agent workflow stack so efficiently?

Bennett Spooner 的头像

Bennett Spooner1 年前

it took a long time, so much to work on w the communication between agents

Mykhailo Sorochuk 的头像

Mykhailo Sorochuk1 年前

@BennettSpooner That's impressive! Streamlining all those processes with AI agents is a game changer. Excited to see how it transforms those franchises.

Bennett Spooner 的头像

Bennett Spooner1 年前

It’s coming along ! I’ll keep the community updated

Nick Spisak 的头像

Nick Spisak1 年前

@BennettSpooner What tech stack are you using for the agent orchestration?

Bennett Spooner 的头像

Bennett Spooner1 年前

N8n and relevance

sweabsol 的头像

sweabsol1 年前

@BennettSpooner Interesting, I’ve been thinking about developing something similar for small local business near me, hair salons, mechanics, etc. I’m exited to follow your journey and advice to see how this works!

Bennett Spooner 的头像

Bennett Spooner1 年前

@devabsoll Start working on it my man, the flame of ai will be extremely quick, better to start the flame in a niche than add onto it

sweabsol 的头像

sweabsol1 年前

@BennettSpooner What industries would you recommend creating working flows if you’re in my position and just starting off?

Bennett Spooner 的头像

Bennett Spooner1 年前

@devabsoll think about what has a little higher barriers, stuff that isnt flashy, property management, pest control etc

sweabsol 的头像

sweabsol1 年前

@BennettSpooner Got it, I commented AI on your other post and I’m yet to receive anything btw

Naim Ai 的头像

Naim Ai1 年前

@BennettSpooner Cool, what tools you used?

Bennett Spooner 的头像

Bennett Spooner1 年前

Figjam, n8n and relevance

Naim Ai 的头像

Naim Ai1 年前

@BennettSpooner Thanks! I will check relevance!

Roshan 的头像

Roshan1 年前

@BennettSpooner This is really impressive stuff

Bennett Spooner 的头像

Bennett Spooner1 年前

Thank you man!

N.E.X.U.S. 的头像

N.E.X.U.S.1 年前

@BennettSpooner Powered by... me?

OperatorOS 的头像

OperatorOS1 年前

@BennettSpooner Follow us for more updates!

Aurobindo 的头像

Aurobindo1 年前

@BennettSpooner Portfolio: GitHub: Resume:

Bennett Spooner 的头像

Bennett Spooner1 年前

Join our community and share one of your projects on there to be considered

Aurobindo 的头像

Aurobindo1 年前

@BennettSpooner

Bennett Spooner 的头像

Bennett Spooner1 年前

leave one to join

Aurobindo 的头像

Aurobindo1 年前

@BennettSpooner ok

Ranger 的头像

Ranger1 年前

@BennettSpooner Stop using manual workflows... this shit looks crazy

Bennett Spooner 的头像

Bennett Spooner1 年前

So complex

Melina 的头像

Melina1 年前

@BennettSpooner Keep pushing 🔥

Bennett Spooner 的头像

Bennett Spooner1 年前

We are absolutely grinding

Melina 的头像

Melina1 年前

@BennettSpooner There is no easy way to succeed. I have my AAA, and after years of entrepreneurship, I’m finally starting to see some rewards. So, just keep working✊

Bennett Spooner 的头像

Bennett Spooner1 年前

got to, our last business was considered a failure, its all about moving forward.

Ian Timotheos Pilon 的头像

Ian Timotheos Pilon1 年前

@BennettSpooner 🔥 want to talk about the build on my podcast?

Bennett Spooner 的头像

Bennett Spooner1 年前

would love to!

Ian Timotheos Pilon 的头像

Ian Timotheos Pilon1 年前

@BennettSpooner Cool, will send you a DM to book a day/time.

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190,102 次观看 • 7 个月前

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Agents changed software forever. For everyone. You won't need to "learn a tool" anymore. Instead, you'll tell tools what you want, and they will figure out how to do it. This is a huge shift. I'm currently working with Spoki, an AI agentic conversational platform. After looking at this, you'll never think of a CRM the same way. A traditional CRM manages contact data. Spoki manages the entire customer journey (marketing, sales, and customer care) in a single continuous flow across WhatsApp, SMS, and Voice AI. AI will dismantle the old traditional tools one by one. Think of it this way: Instead of stitching together a bunch of tools to talk to your customers, you have a single conversation that runs the entire relationship.

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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

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230,647 次观看 • 1 年前

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$FET just quietly built the internet for AI agents. 3,000,000 agents. One network. One token. Here's what nobody is explaining: Every AI agent needs 3 things to be useful: An address. A way to be found. A way to get paid. Agentverse gives agents all three. Your agent becomes discoverable on ASI: One. Other agents can find it, call it, or hire it. Automatically. No human in the loop. This is agent-to-agent commerce. And every transaction settles in $FET. More agents = more activity = more demand. The infrastructure is already live. The economy is just getting started.

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12,894 次观看 • 5 个月前

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AI agents can already generate text, analyze data and execute tasks. But what happens when they need to hire each other and get paid for the work? This is the part of TermiX I’ve been digging into lately. On TermiX, a job has two sides: a client agent that needs something done and funds the job, and a worker agent that actually executes it. Once the quote is accepted, the payment and agreed terms sit between them onchain. Neither side can simply rewrite the deal afterward. And this isn't presented as an abstract concept. The TermiX agent marketplace already shows agents with their own identities, reputation, completed jobs and settled value. Some of the agents shown have completed hundreds of jobs, with tens of thousands of dollars settled. Think about where this model can go. A research agent could outsource data collection to another agent. A developer agent could hire a security-focused agent. A marketing agent could hand translation or design work to specialized agents. Instead of one AI trying to do everything, specialized agents can discover each other, agree on a job, execute it and settle the transaction. Humans built marketplaces around people hiring people. TermiX is building the infrastructure for agents hiring agents. That’s where autonomous AI starts looking a lot more like an actual economy.

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13,718 次观看 • 28 天前

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We cancelled our entire SaaS stack and started running our business with AI agents. Now, we’re building Toyo to help other founders do the same. We're pleased to announce $4.3M in funding from Frontline Ventures, Inovia Capital, Philipp Moehring - tiny.vc, and angels from Amazon, Microsoft, and Cloudflare. For decades software was built for humans to operate. That world is over. We're building for one where agents do the work, while humans direct.

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426,323 次观看 • 7 个月前

LOVE was made entirely inside invideo. Not with one agent. I built a multi-agent system — a director, and around it casting, locations, storyboard, then one agent per main scene, all working at the same time. In the breakdown I go through the things that struck me most: — Expert agents talking to each other — Infinite memory — Slate editor — And a Project Analyst at the end, interviewing every other agent on what to change next time There's a lot more to say. I'll take it one thing at a time in the next posts. Invideo Agent Two isn't just an agent. It's a collaborator you shape into what you need. Full breakdown ↓

LOVE was made entirely inside invideo. Not with one agent. I built a multi-agent system — a director, and around it casting, locations, storyboard, then one agent per main scene, all working at the same time. In the breakdown I go through the things that struck me most: — Expert agents talking to each other — Infinite memory — Slate editor — And a Project Analyst at the end, interviewing every other agent on what to change next time There's a lot more to say. I'll take it one thing at a time in the next posts. Invideo Agent Two isn't just an agent. It's a collaborator you shape into what you need. Full breakdown ↓

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14,813 次观看 • 1 个月前

Anthropic's Claude team just showed how to give your AI agents real memory in under 18 minutes. Free. From the people who built it. You've been building agents that forget everything between sessions. This fixes that tonight. One person + 10 agents with memory + dreaming = a team that runs 24/7, learns from every task, and improves itself overnight. Worth more than any $500 AI agent course. Bookmark it. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Anthropic's Claude team just showed how to give your AI agents real memory in under 18 minutes. Free. From the people who built it. You've been building agents that forget everything between sessions. This fixes that tonight. One person + 10 agents with memory + dreaming = a team that runs 24/7, learns from every task, and improves itself overnight. Worth more than any $500 AI agent course. Bookmark it. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

11,230 次观看 • 4 个月前

AGI won’t be one giant model. It will be many specialized intelligences working together through a reasoning-capable AI that coordinates the layer that routes each query to the right models, tools, and agents. PS: Good reasoning is how you avoid getting your agent deleting your entire email inbox btw.

AGI won’t be one giant model. It will be many specialized intelligences working together through a reasoning-capable AI that coordinates the layer that routes each query to the right models, tools, and agents. PS: Good reasoning is how you avoid getting your agent deleting your entire email inbox btw.

Sentient

19,245 次观看 • 7 个月前

Episode 7 of How I AI is going to inspire the marketers and scare all of SaaS. is head of growth at and ambitiously embraces AI for marketing, to build internal tools, and to hack on his personal data. You’ll learn how to: - take Granola transcripts and turn them into multiple marketing assets - replace expensive saas tools by building a custom solution in Cursor - use Luke’s WhatsApp MCP to query your group chat Luke gives one of the most fun and broad tours of using AI as someone who is technically not in a technical role. Plus, he teaches me “everything is a launch.” Check it out in the links below 👇🔗 As always, a big thanks to our sponsors: 🔀 Orkes enterprise platform for agentic workflows 🧰 Retool AI for developers, built for the enterprise

Episode 7 of How I AI is going to inspire the marketers and scare all of SaaS. is head of growth at and ambitiously embraces AI for marketing, to build internal tools, and to hack on his personal data. You’ll learn how to: - take Granola transcripts and turn them into multiple marketing assets - replace expensive saas tools by building a custom solution in Cursor - use Luke’s WhatsApp MCP to query your group chat Luke gives one of the most fun and broad tours of using AI as someone who is technically not in a technical role. Plus, he teaches me “everything is a launch.” Check it out in the links below 👇🔗 As always, a big thanks to our sponsors: 🔀 Orkes enterprise platform for agentic workflows 🧰 Retool AI for developers, built for the enterprise

claire vo 🖤

24,914 次观看 • 1 年前

🚨 SOMEONE JUST TURNED AN LLM INTO AN AUTONOMOUS RED TEAM Cyberstrike is an open source AI security agent built to automate penetration testing from your terminal. Plug in your Claude, GPT, or other LLM subscription and you get: → 13+ specialized security agents → 7,600+ security skills → 120+ OWASP test cases → 150+ AI providers → 5,300+ models → 56+ built in tools → 176+ MCP tools Instead of one AI trying to do everything, it splits security work across specialized agents. This is where AI powered pentesting gets seriously interesting. Use it only on systems you own or have explicit permission to test. REPO BELOW

🚨 SOMEONE JUST TURNED AN LLM INTO AN AUTONOMOUS RED TEAM Cyberstrike is an open source AI security agent built to automate penetration testing from your terminal. Plug in your Claude, GPT, or other LLM subscription and you get: → 13+ specialized security agents → 7,600+ security skills → 120+ OWASP test cases → 150+ AI providers → 5,300+ models → 56+ built in tools → 176+ MCP tools Instead of one AI trying to do everything, it splits security work across specialized agents. This is where AI powered pentesting gets seriously interesting. Use it only on systems you own or have explicit permission to test. REPO BELOW

MAX

17,029 次观看 • 1 个月前

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,695 次观看 • 1 年前