How I Book 160+ Sales Calls a Month With AI Agents

0:00I'm currently generating over 160

0:02meetings per week for my company. And

0:04we're doing it without a single SDR

0:06picking up the phone without a massive

0:08ad budget and without blasting thousands

0:10of generic cold emails. Instead, I use

0:12AI to build what I call an allbound

0:15system where inbound and outbound aren't

0:17separate channels anymore. They feed

0:19into each other through AI agents,

0:21social signals, and automated workflows

0:23that run around the clock. And the best

0:25part is you don't need a big team or

0:28expensive enterprise tools to do this.

0:29In this video, I'm going to walk through

0:31this exact system and how I use it step

0:33by step and show you how to copy it.

0:35Let's dive in. I want to explain why we

0:38moved away from the traditional approach

0:40because it sets up everything else in

0:42this video. And if you're pulling static

0:43lists based on job title, location,

0:45revenue from tools like Apollo or Zoom

0:47Info, you're using the same data as

0:49everyone else. Your prospects are

0:51getting hammered by dozens of companies

0:52running the same playbook. And now email

0:55providers are using AI to filter out

0:57anything that reads like a sales pitch

0:59before it even hits the inbox. So

1:02instead of reaching out to people

1:03because they match a filter, we reach

1:05out because they just did something that

1:08shows they might actually care. That

1:10could be engaging with competitors

1:11content, talking about a problem we

1:13solve, or hiring for a role that signals

1:15they need what we offer. One signal like

1:18that is worth more than a,000 emails to

1:21people who have no reason to talk to

1:22you. That shift is what allowed us to

1:24build a system where three people

1:26generate over 160 meetings a week. So

1:28let me show you how exactly I built the

1:30allbound framework. Now before I dive

1:32into these layers, here's a quick look

1:34at how the whole system connects. We

1:36have three core functions running this.

1:38First is the master list builder. This

1:40is your growth or revenue operations

1:42person responsible for building

1:43evergreen lists. That's key, evergreen

1:45lists using mainly social listening.

1:47They're not doing manual prospecting.

1:49They're setting up automated

1:50signal-based searches that run

1:52continuously. Second, the account

1:54executive or AE, which in this case is

1:56me. I'm closing deals and self-sourcing

1:58warm leads that the system feeds to me.

2:00Third is an SDR I built using NA10. It

2:03handles replying to inbound traffic,

2:05nurturing leads, and booking in warmer

2:07prospects coming into our site. Then we

2:09have a content generator who acts as a

2:11ghostriter for the entire team, taking

2:13real themes from our sales calls and

2:15turning them into posts. I'll explain

2:18exactly how that content loop works

2:19later in the video. So, let's get

2:21started and walk through each layer,

2:23starting with the one that makes

2:24everything else possible, and that is

2:26the signalbased prospecting. Everything

2:28starts with how you build your list. And

2:31this is where Triggery, which is my own

2:33tool that I developed, sits at the

2:35center of this entire operation. So,

2:37let's dive in. Inside Triggery, we have

2:39two main features powering this. Social

2:41listening and social engagement via our

2:43workflow feature. I'm going to walk you

2:45through how we can set up a boolean

2:47search to monitor anyone talking about a

2:49specific topic across something like

2:52LinkedIn for example, but we have

2:53multiple other social sites like Reddit,

2:55YouTube, podcasts, threads, Instagram

2:58and so on. So for example, with my use

3:00case here, what I'm searching for is I

3:02want to search for anyone who is talking

3:03about something that has high level of

3:06intent for me on LinkedIn. So I'm going

3:08to search for something where it's

3:09related to signals. And then inside of

3:12here, I'm going to have social or sales

3:15or marketing, right? And so what this is

3:18now going to search for is it's

3:19searching for anyone who is talking

3:21about signals and social or sales or

3:23marketing basically. And we can start to

3:25use it to find very specific people

3:27talking about very specific things. Now,

3:30if you feel like it's a little bit

3:31generic, I could get rid of certain

3:33keywords, for example, or I can make it

3:35a little bit more specific. So if

3:37signals is maybe coming back and being a

3:39relevant content, I can narrow all of

3:42that down. So now whenever someone posts

3:44about these topics or engages with

3:46content around them, they flow into a

3:48system automatically where I then go

3:50ahead and capture that engagement. So

3:53one of the popular one that I do is I

3:55track for any intent subjects. I also

3:58monitor specific profiles that I upload

4:00and tier. So these are competitors,

4:02these are thought leaders that are

4:03tracking specific things and they are

4:06obviously my own brand. Now once they

4:08post, they basically filter through into

4:12what I have as this workflow set up

4:14which is capturing all of that

4:16engagement. So here I'm monitoring for

4:18three different competitors and the

4:20intentbased search that I obviously just

4:21set up and my own brand. When one of

4:23these posts comes in, I go ahead and I

4:26grab all of the engagement that these

4:28individuals are getting. I enrich that

4:30information. I verify that they're ICP

4:33before I can go ahead and do things like

4:34send it through to Clay or I could send

4:36it through to tools like Hey Reach or

4:38Instantly or Smart Lead or whatever pill

4:40is your poison there when it comes to

4:41your outreach. Now, I tend to group

4:43these people that I'm tracking into what

4:45we call like groups. So, for example,

4:46like one is for competitors, one is for

4:49my own brand, and one is for thought

4:50leaders. And then each different group

4:52will have a different strategy, a

4:54different campaign associated with it.

4:56every like, every comment, every person

4:58touching this content that I'm searching

5:00for gets captured. Now, if they match

5:02our ICP criteria, which you can see that

5:04we have inside of this node, we find

5:06their email addresses and then, as I

5:07say, we automatically add them to a

5:10outreach system. This is so much more

5:12effective than a static list. For

5:14example, if someone has been liking

5:15content about cold email infrastructure

5:1710 times in the last month and I email

5:19them saying, "Hey, I can help you land

5:20in the inbox." They're far more likely

5:22to respond. That's not personalization

5:25for the sake of personalization. It's

5:27person level relevance based on what

5:29they actually care about. Right now, my

5:32campaigns using social signals typically

5:34get a one in4 positive reply rate, which

5:36is dramatically higher than anything

5:38that I've done personally and anything

5:39that I've seen from a cold static list.

5:42On top of this, I use a strategy called

5:44social warming, which makes this even

5:46more powerful. So, what is social

5:48warming? Well, the idea is simple. you

5:51monitor key thought leaders in your ICP.

5:54So, for example, in this social

5:56listening that we're looking at here, um

5:58you'll notice that I've got a load of

5:59different profiles that I'm basically

6:01set up and monitoring within here. You

6:03can see people like KL Coleman, Sam

6:05Jacobs. These are all influential

6:07marketing individuals. Now, anytime that

6:09they post about something relevant, I

6:12have a workflow set up. It uses an agent

6:14inside of our workflow system that

6:16classifies whether that post is relevant

6:18to what my business does. If it is, then

6:20I'm going to go ahead and collect all of

6:22that engagement. Now, at the same time,

6:24I'm going to go and get notified via

6:26Slack the moment they post. And the

6:29reason that I'm going to do this is I'm

6:30going to drop some value into that

6:32comment. Now, my prospects that I want

6:34to reach out to, they're obviously going

6:36to start engaging with this content.

6:38They're going to see my post within that

6:41comment section typically because I'll

6:43be the first to comment there. So that

6:44means once I collect all of this

6:46engagement, all the likes and comments,

6:47the chances are they would have seen my

6:49name in some shape or form, either

6:51through the notification system or just

6:53as they go on to that post and they like

6:54it. So when it comes to me reaching out

6:56via the inbox, whether that is through

6:58email or even potentially LinkedIn, my

7:01name is a little bit more familiar to

7:03them, right? They understand, they know

7:05who I am because they probably seen them

7:07and they've seen my name maybe five to

7:0910 times before I reach out. So, your

7:12DMs stop being cold and your emails stop

7:14being ignored. Now, before I explain how

7:17I actually reach out to these people, if

7:18you want to start building signalbased

7:20lists and running social warming just

7:22like I showed you, head over to the

7:23triggery site and sign up. Link is in

7:25the description. It's totally free to do

7:28so. Now, back to the video. Cold email

7:30infrastructure. So, now you have high

7:32intent leads flowing in. The next

7:34question is how you actually reach them

7:36without landing in spam. We mainly rely

7:39on cold email and for that we use

7:41instantly um but we're also actually

7:43experimenting with a new tool called

7:45plus vibes. So here's an example of a

7:47campaign we're running. Okay. So in this

7:50campaign we have a two-step process. I

7:53typically only ever do two steps and we

7:56always lead with value. So in this case

8:00you'll see on LinkedIn and Twitter and

8:02all these other places lead magnets are

8:03incredibly popular. We actually take

8:05that philosophy and dial it through into

8:08our cold email campaigns. So in this

8:10case, we have a system set up where

8:12people are engaging with content around

8:15LinkedIn um content building. They're

8:17engaging with content around like

8:19LinkedIn automation tools. So again,

8:20it's really really relevant because

8:22these people will have a direct interest

8:25in understanding how they could get a

8:2730% reply rate through their LinkedIn

8:29campaigns and engagement data, right?

8:30And so we turn this interest into a lead

8:33magnet and say, "Hey, do you want me to

8:35send across this lead magnet that I have

8:36which has a bunch of CTAs like wrapped

8:38inside of that lead magnet itself, which

8:40will start to act as a lead gen driver."

8:43So we go quite soft with this approach

8:45and this is what gets us a really really

8:48good success as a result. Now when it

8:51comes to infrastructure, we tend to use

8:54uh multiple different tools. Um, one of

8:56the popular ones that we've recently

8:57started using is Mail Doso to spin up

8:59inboxes across Google Workspace and

9:01custom SMTP. Now, the reason I chose

9:03Mail Doso is they have an official

9:05partnership with Google, so they aren't

9:07shady accounts. At any time we're

9:08running 50 to 100 inboxes. The sending

9:11rules are conservative by design and

9:14that's exactly why, in my opinion, they

9:17work. So, first things first with

9:19emails, we only send as plain text. No

9:22HTML at all. We remove all links

9:25associated in at least that first email

9:28as well. And personalization, I'm

9:30actually anti-personalization a lot of

9:32the time because as long as you're

9:33reaching out with relevance, that is

9:35enough personalization for what you need

9:37from a limitation on the amount of

9:39emails that we're sending per day. We

9:41limit it down to 20 per inbox per

9:44domain. Again, that's really, really

9:47aggressive with the limitation, but it

9:48works by design. We don't have to rotate

9:51the inboxes all the time and it keeps

9:53our cost on email infrastructure down.

9:55Now, you'll also notice that we've

9:56disabled open tracking. It uses pixels

9:59that hurt deliverability. So, we've

10:00turned it off entirely. I know this

10:02sounds boring and that's the point. If

10:05you get it right, if you get the basics

10:06right, you don't need hacks and every

10:09email gets validated before it goes out.

10:12This step is nonnegotiable. We actually

10:15use lead magic for enrichment and

10:17validation. Let me actually show you the

10:19clay table uh that we have running on

10:21one of these campaigns. Okay, so here we

10:23have a clay table. This is all of my

10:25engagement. You can see there's about uh

10:27just over 8,000 records coming in here.

10:29Everything comes in through uh from a

10:31lead magic perspective. We validate it

10:33through lead magic as well. We always

10:36use um bounce banan as well as a an

10:38additional verification um process. Um

10:41we don't run massive waterfall

10:43approaches or anything like that.

10:44Typically we keep it uh predominantly to

10:46lead magnet and prosp as you can or

10:48prosper as you can see there. Bad emails

10:50equals burn domains and if you can't run

10:53successful campa well you literally

10:54can't run a successful campaign with

10:55burn domain. So got to get the email

10:57infrastructure right otherwise

10:58everything else that you're doing is

11:00kind of mute. Now onto layer three. This

11:03is the content loop and I think probably

11:05one of the coolest parts. Now here is

11:07where the system starts feeding itself

11:09and this is where it turns a one-time

11:11campaign into an evergreen machine. For

11:14people who don't know, evergreen

11:15basically just means it's continuously

11:17running. Once you set it up, away it

11:19goes. Most people treat content and

11:21sales as completely separate. We connect

11:23them into a loop where each one feeds

11:26the other. And it starts to make

11:28everything better. The more sales calls

11:30we do, the better our content strategy

11:32gets, the better our outbound gets, and

11:34so on and so on. So for us, it all

11:36starts with the demos. Here we actually

11:39use a tool called Fireflies. Every demo

11:42the team makes is automatically

11:44transcribed through Fireflies and then

11:47hooked up to G sheets which in turn that

11:49Gsheets is then hooked up to anything

11:51that we use claudes anthropic whatever

11:53it is. So as you can see once a meeting

11:56takes place we go ahead we grab the

11:59transcript and then we add it into uh a

12:02G sheets. Now we're automatically

12:03storing all this information for you

12:06know knowledge repositories and so on

12:07and so on. You can use an MCP and

12:10connect straight into Fireflies as well.

12:11I just like having all of this data

12:13stored in a local spot basically for me.

12:17So for each call, we pull every single

12:19question that's being asked and we store

12:21them obviously inside of the G sheet. AI

12:24then analyzes these questions and

12:25converts them into content themes based

12:28on the FAQs our prospects are typically

12:31asking. Now, this solves the biggest

12:33problem every founder and sales team has

12:35with content, which is not knowing what

12:38to post and that kind of fear of just

12:40sitting there working out what will do

12:43well. Instead of staring at a blank page

12:44or posting corporate nonsense, which is

12:47just garage that nobody ever engages

12:49with, every post is based on a real

12:51question a real prospect has actually

12:53asked in a real conversation. Our

12:55content generator then takes these

12:57themes and turns them into four posts a

12:59week, which gets spreads evenly across

13:01the team. Everyone at Triggery is tasked

13:03with posting two to three times per

13:05week. And here's where the loop closes.

13:07All of the engagement from these

13:09individuals that are posting in my team

13:11is then tracked through Triggery. The

13:13engagement is then collected. If we head

13:16back to here and have a look, our

13:17engagement is then collected through

13:20this system that we basically built

13:22inside of Triggerfy. Yeah. All the

13:23engagements from this content from my

13:25team gets tracked right back through

13:27triggery. So every like, every comment

13:30that they get from the content which we

13:32got from the calls that they were doing

13:34then gets enriched, then gets qualified

13:36and if they match our ICP, they're added

13:39automatically to our CRM which we use as

13:41these leads then get turned into demos.

13:45Those demos generate more content themes

13:48and the cycle keeps going. On top of

13:50that, this content gets syndicated into

13:53blog posts through another agent I built

13:55inside of NA10. So, this then runs, it

13:57basically researches all of the FAQs, as

14:00you can see here. It looks all of this

14:02information up inside of the the G

14:03sheets. It then works out what blog

14:06content it should be doing, newsletter

14:07content it should basically be doing. It

14:09then feeds it through to this research

14:10agent which runs research on the

14:12questions that were asked. It obviously

14:14has access to the triggery knowledge

14:16repository and then it turns it into an

14:18actual blog and a newsletter which I

14:20post on my Substack. Uh and then

14:23obviously the newsletter the blogs go

14:24onto our website. This process has meant

14:26that we've been started to be mentioned

14:28in things like Claude in OpenAI when

14:29people are searching for it. It's

14:31massively helped our SEO as a result as

14:34well. Every single thing that we're

14:36doing has an impact on everything else

14:38that we're doing. One demo conversation

14:41can fuel a full week's worth of content

14:43across multiple channels. So, on to the

14:46last layer. Layer four, capturing and

14:48recirculating leads. The last piece is

14:51making sure that you're not leaking

14:52leads anywhere in the system. All of our

14:54outbound content is driving people to

14:57our socials and website. And if you're

14:59not capturing that traffic, it's wasted

15:01on the website. You can use tools like

15:04RB2B or Vector to identify visitors at a

15:08person level. On LinkedIn, we use

15:10Triggerify to capture things like

15:11profile views, obviously engagements,

15:14which I've talen a lot about. So, if

15:15someone checks out my LinkedIn or checks

15:17out my website after seeing one of my

15:19posts or receiving an email, we know

15:22about it. Both of these signals are then

15:24fed back to instantly via a subsequence.

15:28these leads then gets added to our

15:30triggerly flow and can be cooled by our

15:33team and the loop keeps going. So

15:35someone who visited our website after

15:37seeing a cold email now gets a follow-up

15:39that feels warm because it is they've

15:41already shown interest. This

15:42recirculation is what gives us more

15:44meetings than we can handle with only

15:46three people. Every channel reinforces

15:49the next channel. Outbound drives

15:50attention. Content builds trust.

15:52Engagement creates signals. And the

15:54signals feedback into an outbound. the

15:56AI agents tying it all together running

15:58these systems you need a team of 10 to

16:0115 people the reason we do it with three

16:04is because of AI agents I built using

16:06NA10 claw code open claw and so on first

16:10is the AI SDR so when someone comes onto

16:13our site or responds to an email the AI

16:15SDR handles the initial conversation and

16:18it books warm leads directly into our

16:20calendar and as you can see here it's

16:22doing a lot of different things through

16:25the different inputs that it comes in

16:26via the web hooks, right? And that's

16:28coming in from the website and so on. It

16:30handles all of the crossorrelation with

16:32communication. It updates everything.

16:34And yeah, really the idea of this is

16:36basically to get meetings just landing

16:37in our inbox. So the next is what we

16:40have I call like my master chief. This

16:43is my AI sales call prep agent. So let

16:45me show you this here. Master Chief call

16:47research. inside of here. This basically

16:51anytime I have a calendar or a meeting

16:54which is booked through that AISDR, they

16:56then basically go and look up the

16:58individual, they analyze, they're like a

17:00business analyst, they're a website

17:02analyst and they also generate a

17:03triggery uh use case to then add it to

17:06my ATIO and obviously a Slack

17:08notification. I effectively get this

17:10full brief on how and why they should be

17:13using triggery, who they are, and why

17:15that they probably have generated

17:17interest. uh with us. So every 15

17:19minutes, this workflow pulls my calendar

17:20for upcoming meetings and then Master

17:22Chief deploys these sub agents to run.

17:25Now the key thing with this is you'll

17:27notice that I'm updating systems of

17:29record throughout the journey with all

17:31of these different workflows and agents

17:33that I've built. Typically like my

17:34systems of records are either local repo

17:36files that I have or a CRM or maybe

17:39something like Superbase or whatever it

17:40is. In this instance, it's atio. So

17:43we're adding notes to these records. The

17:45reason that we're doing that is we don't

17:47want research to run twice. I only ever

17:49want it to run once. No wasted API

17:52calls, no wasted token spend um that I'm

17:56basically doing. Before this, I was

17:59showing up to 50K deals completely

18:01unprepared because my calendar looks

18:03like Tetris. Now I walk into every call

18:06knowing exactly more about the business

18:08than maybe even they do as well. Third

18:10is an AI content generation agent. As we

18:13can see here inside of the Triggery

18:15platform, I have a completely built

18:17workflow system that is using social

18:19data to generate ideas for me. I set up

18:22a Triggery to monitor social listening

18:24keywords, and whenever something trends

18:26in our industry, the system picks it up

18:28every morning at 9:00 a.m. I then get a

18:31Slack notification with three content

18:33ideas ready to go. This keeps us

18:35consistently up to date without spending

18:38hours thinking of content ideas. on top

18:40of the fact that we're generating

18:42content with our sales calls as well.

18:45So, there's no excuse for my team not to

18:47be generating content. And obviously, as

18:49I've explained, the more content we

18:51generated, the more this whole flywheel

18:53begins. So, if you want to start

18:55building like this kind of system for

18:56yourself, the first step is getting

18:58across to the social signal data that

19:01makes it all work. To do that, click the

19:03first link in the description, head over

19:05to Triggery, and sign up. You can start

19:07tracking engagement, monitoring Thor

19:09leaders, and building signalbased lists

19:12right away. Again, the link is in the

19:14description, so go click on that. And if

19:15you want to learn more about how to use

19:17AI for marketing, then watch this video

19:20next.