The argument in one line.
Outbound lead generation doesn't need more sophisticated tooling — it needs three simple, repeatable AI research habits that surface a handful of genuinely high-intent leads every day.
Read if. Skip if.
READ IF YOU ARE…
- A founder, sales leader, or one-person GTM team running cold outreach who wants qualified leads without hiring a research team.
- Someone comfortable wiring together Claude Code, Codex, or a Slack-based AI agent to run scheduled research tasks.
- A B2B seller targeting a specific buyer role who can build outreach off public hiring signals.
SKIP IF…
- You're selling to consumers, not businesses — the job-posting and event-sponsor signals here are B2B-specific.
- You want copy-paste prompts rather than workflow logic — the video shows what to build, not exact scripts to steal verbatim.
The full version, fast.
Cold outreach doesn't need more sophisticated systems, it needs simpler, higher-intent ones. The video walks through three AI research workflows: first, running parallel.ai on a schedule to surface three new companies a day that match a specific hiring signal, then finding the decision-maker's validated email with a free Clay waterfall template. Second, running a Slack-based research agent to find upcoming industry trade shows and pull their full sponsor lists into a spreadsheet. Third, applying Chet Holmes's classic Dream 100 strategy at AI-assisted scale: reading a target company's own job description and using Codex to build a working demo of exactly what that role would have automated, then using the demo itself as the outreach hook. Research is now the easy part; writing the message is still the bottleneck.
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00:00 – 00:23
01 · Intro: sophistication isn't the answer
States the thesis up front: cold outreach needs simple, high-intent lead systems, not more sophisticated tooling. Previews the three workflows to come.
00:23 – 03:29
02 · Workflow 1: parallel.ai daily lead search
Sets up a recurring parallel.ai query, run via Slack or a Claude Code/Codex scheduled task, that finds three new high-intent leads a day off a hiring signal and never resuggests a company already flagged. Pairs it with a free Clay waterfall template to find and validate the decision-maker's email at each hit.
03:29 – 04:44
03 · Workflow 2: scraping trade-show sponsor lists
Tags a custom Slack research agent, "Dale," built on Hermes, to find a relevant upcoming industry event and pull its full sponsor list, demoed on Dreamforce, Unbound, and SaaStr Annual, into a Google Sheet as a ready-made target list.
04:44 – 09:02
04 · Workflow 3: the AI-scaled Dream 100
Revives Chet Holmes's Dream 100 strategy and uses Clay plus Codex to scale it: pulls a deduplicated list of companies hiring for a specific role, reads each job description, and has Codex build a working demo, an ABM target-account list, of exactly what that hire would have automated, turning the demo itself into the free-value outreach hook.
09:02 – 10:32
05 · How to apply it: research is the easy part now
Wraps with the operating principle: research is now cheap and automatable, the message is still the hard, high-value part to build. Recaps scaling Dream 100 to Dream 1,000 or Dream 10,000 with AI-generated free value, usable in either Codex or Claude Code.
Lines worth screenshotting.
- The bottleneck in cold outreach isn't finding leads anymore, it's writing the message once the lead list is built.
- A daily search that surfaces just three high-intent leads a day beats a high-volume list of loosely-qualified prospects.
- Job postings are a public, structured signal for exactly what pain a company is trying to solve and who they'll listen to about it.
- Trade-show sponsor lists are a ready-made target list: any company paying to sponsor an event has already announced its budget and its market.
- Chet Holmes's Dream 100 strategy still works decades after The Ultimate Sales Machine because the mechanism, concentrated attention on a short list, hasn't changed, only the tooling has.
- AI turns a Dream 100 list into a Dream 1,000 or Dream 10,000 by making the free-value-first step cheap to repeat at scale.
- Reading a prospect's own job description and building a working demo of what that hire would have automated is a stronger icebreaker than a generic cold email.
- Scheduled AI agents can run a lead-research workflow every day without a human re-running the prompt.
- Deduplicating a lead list against every previously-suggested company keeps a daily automated search from resurfacing the same accounts.
- Limiting a Clay enrichment pull to one contact per company forces a clean, deduplicated target list instead of dozens of overlapping rows.
Three research habits that scale outbound leads
LEAD GEN SYSTEM
A daily hiring-signal search, a trade-show sponsor scrape, and an AI-scaled Dream 100 replace generic list-buying with a small number of leads that are already primed to care.
- Narrow a daily search to one concrete hiring or intent signal, then let an AI agent surface just three matching companies a day instead of chasing volume.
- Keep a running list of every company an automated search has already suggested so it never resurfaces the same accounts and wastes a day's lead.
- A one-contact-per-company limit on enrichment tools forces a clean, deduplicated target list instead of dozens of overlapping rows for the same account.
- Trade-show sponsor and attendee lists are a public, ready-made target list: any company paying to sponsor an event has already declared its budget and its market.
- The Dream 100 strategy still works because concentrated attention on a short list of ideal accounts outperforms broad, low-effort outreach, AI just makes the free-value step cheap to repeat.
- Reading a target company's own job description and building a working demo of what that role would automate is a stronger opener than a generic cold email.
- Research is now the cheap, automatable part of outbound; writing the actual outreach message is still the highest-value, hardest-to-automate step.
Terms worth knowing.
- Parallel.ai
- An API that connects AI agents to web-based market intelligence, letting a script or agent search for companies and signals like hiring activity instead of a human doing it manually.
- Dream 100 strategy
- A sales method from Chet Holmes's book The Ultimate Sales Machine: pick 100 ideal target accounts and repeatedly earn their attention with free value and multi-threaded outreach rather than mass-blasting a large list.
- Clay waterfall
- A Clay enrichment feature that runs a contact through multiple data providers in sequence until one returns a validated work email, increasing match rate beyond any single source.
- ABM (account-based marketing)
- A B2B strategy that targets a specific, named list of accounts with tailored outreach and content instead of running broad campaigns aimed at a general audience.
- Multithreading (sales)
- Reaching out to several decision-makers inside the same target account at once, instead of relying on a single point of contact to move a deal forward.
Things they pointed at.
03:29toolCodex / Claude Code scheduled tasks
05:05bookThe Ultimate Sales Machine by Chet Holmes
06:26toolHermes agent (custom Slack research agent, "Dale")
Lines you could clip.
00:00
“Here are three boring AI workflows that you can use in order to get more sales from cold outreach.”
00:11
“You don't need more sophisticated systems. You need simple systems that bring you high quality leads.”
05:07
“You should make a list of your dream 100 customers and then do anything you need in order to get their attention.”
09:11
“The hardest part is writing the message, and that is gonna take the most time for you to do the investment in order to fully automate that. But until you get that built, the easy part is the research.”
Word for word.
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metaphor
00:00Here are three boring AI workflows that you can use in order to get more sales from cold outreach, whether you're leading your marketing team, a sales team, or you're the founder doing these outreach campaigns. You don't need more Claude skills. You don't need more sophisticated systems.
00:15You need simple systems that bring you high quality leads for you to be able to reach out to, and that's exactly what we're gonna go over in today's video. The first boring workflow that we're gonna go over, we're gonna use parallel.ai to literally just ask it to find three high intent leads for us every single day.
00:33Now what many people do when they are doing sales research or marketing research is they are looking for prime ideal customers and that means something different for everybody. They wanna find people who are hiring for certain roles.
00:47They wanna find people who just launched new product. They wanna find people that just got acquired. Whatever it might be, what we set up for a lot of our customers is a very low volume but very high intent outbound campaign where we literally use parallel.ai to just say, hey, every day just find three new leads and keep a list of all of the companies and the leads that you've ever suggested for me, And then don't suggest any of the other ones and just find me new ones that qualify for this.
01:15Right? And so this is what the website of parallel.ai just looks like.
01:19It's basically just an API that connects you to market intelligence. And so what we will do is we will connect this to a Slack channel and we will literally just say something as simple as and I'll zoom in for this.
01:32Something as simple as, can you help me find three companies per day that hired their first go to market engineer, are hiring for their first go to market engineer, have a go to market engineer at all. You can publicly look up people who have put it on their job posts on their website, on LinkedIn, or on Indeed, etcetera, and just all these other things.
01:51This is I'm just showing this to you as an example. Your request might be more complicated. You might wanna know roofers that are hire that just announced new jobs or you might might wanna find, uh, marketing teams that are growing, whatever it might be, and just say, just want three leads every single day.
02:06It's as simple as that. You can then use ClaudeCode or Codex with their scheduled tasks to be running this every day for you as well too.
02:14But just check this out, how immediately off of one prompt, it found me a that Toast is hiring for a senior go to market engineer. Revik is hiring for a senior, uh, a founding go to market engineer, and Stutt is hiring for a go to market engineer.
02:28Super boring, but we know that these are really high intent leads. And now we can use tools like Clay or Prospio or any other tools to literally then say, okay. Now find me the sales leader at Toast.
02:40Find me the marketing leader at Toast. Find me the CEO at Toast. And now we can reach out to them and say, hey.
02:45I saw that you're hiring for this go to market engineer role, and then pitch whatever product or service that you're looking for there. Real quick. That step where I found that sales leader at Toast, there's a free clay template that does all of that for you.
02:57You just drop in the company URLs and the job title that you're looking for, and it finds the decision maker at every company and pulls their validated work email with the . Super boring, but it works every single time. It's free.
03:09The link's in the description, and grabbing through that link will make sure you get some extra clay credits as well. Now let's get back to the video. You can just set up a schedule inside of Claude Code or Codex and use parallel.ai, specifically their task, uh, research agent to be able to get this done.
03:24And it's so simple to get started and then you have three really great companies every single day to be able to reach out to. The second thing is another list building strategy that I put the screenshot into a Google Doc so I didn't have to edit the Slack messages for you. But another suggestion I would have is using a Hermes agent or parallel.ai as well to find industry trade shows or niche trade shows, and then you can use those tools to find all of the sponsors and the attendees if they're available as well too.
03:52So here, if you see, I just used I tagged my Hermes agent in my Slack channel. I named him Dale. And I just said, can you find an event coming up in the near future that we can use to get sponsors?
04:01I would love to find a go to market engineering event, a marketing event, a sales event. And, basically, I said the bigger the event, the better. And then it just did a little bit of thinking and then it outputted this, uh, Google Sheet for me of all the sponsors at Dreamforce.
04:14And so this is the sheet that it gave me. And look, it even included the sponsors of Unbound. So we have Dreamforce over here, and then we have Unbound over here, and then we have Saster Annual as well.
04:26I didn't do anything. I literally just said, hey, Hermes. Just find this event and then go find the people who are sponsoring so I can reach out to those people, and I'll find contacts using Clay, etcetera.
04:36And now we're gonna talk about something that requires a little bit of practice with Claude, but I think is actually where more sales teams need to be going. Now if there's no events for you and it's not really great to publicly be looking up these people, we can try our third boring AI workflow.
04:54And the reason I call this a boring AI workflow is because this strategy has been around for years. It's called the dream 100 strategy. The dream 100 strategy is a classic strategy by someone named Chet Holmes in the ultimate sales machine.
05:07And what Chet basically said is you should make a list of your dream 100 customers and then do anything you need in order to get their attention. Create free value, constantly reach out to multiple decision makers and , whatever it might be.
05:23What I started thinking about though is this is an insanely boring workflow that with AI, you can take it from the Dream 100 to a Dream 1,000 or a Dream 10,000.
05:34We can use AI to make phenomenal lead magnets and show people the work that we've already done and use that to be able to get their attention. And then we can combine it with a clay workflow to make it even more powerful. I use clay over here to find a list of companies that are hiring for go to market engineers.
05:51I basically just wanted to see, okay, what companies are hiring for go to market engineers and the way you set up this is we are looking for GTM engineers and then we're looking for go to market engineer. And then you wanna put the limit per company at one. That way when you pull the list, you're only gonna get a a deduplicated list of all these companies.
06:09You're not gonna get multiple duplicate rows or or anything like that. We just limit it to one and we say, okay. These are all these companies that are hiring for go to market engineers.
06:18Then all I did was I just moved it over and I just enriched it so that we could get the job description. Then what I did is I basically said, hey, the the free value that I would give to Dream one hundred company is whatever the job description says for the go to market engineer, there's usually a lot of data that's required for that.
06:36They want us to build clay work workflows. They want us to build codex workflows. They want us to enrich their CRM.
06:41Whatever it might be, let's read the job description of what this person is going to be responsible for and let's do a little bit of that with the APIs and the skills that are already available and made on my computer. So that's exactly what we did. We took the hog right here.
06:56They said that they're a single unified API based in San Francisco, and it is supposed to be the web intelligence layer for AI agents. And this person is gonna be responsible for early stage growth and they wanted them to use modern strategies for their ABM motion.
07:16So what do we do? Because all of my skills are very list building related, it created an ABM demo for The Hog.
07:25And so as you can see, it already pulled companies. I actually don't even know how Codex did this. This was ridiculously smart.
07:32It already pulled companies that are basically sales intelligence companies that would need to use something like The Hog if they were given, you know, a better web intelligence layer. And it also gave what they would even use them for, what would be the use case.
07:46So you see can see clay.com is at the top of the list, which is awesome. Maybe we should we can use this video to get them introduced to them. Then we had Common Room, Common Competitor, Unifi, Nooks is a dialer, Eleven x is an AI sales agent.
07:57Great. And then we just keep going down. All of these companies absolutely have a use case to integrate with the Hog or any web intelligence layer that is.
08:06And then after they integrate, can make that a part of their product suite or they can use that as just generally a part of their sales team as well too. So I would say it did a great job of making this list. Even said why they fit the hog, the likely use case, and then the trigger trigger signals to be looking out for and the recommended personas that we should be reaching out for as well.
08:26And then it gave us briefs on each of them in a very ABM style. And then we have our workflow architecture, a one page write up, validation notes, and etcetera, etcetera. And so, again, now this is a little bit more complicated of an approach, but I still call it a boring workflow because this has been around forever.
08:43But all I would just told Codex was this is what we're specialized at. Dig into our data and let's go use these job descriptions. See what these job descriptions are saying that these people will be responsible for, and then let's just go do that.
08:57And so that's our third boring AI workflow. I think these are workflows that anybody could use. They're not necessarily high volume workflows.
09:05The Dream 100, like I said, can scale to Dream 1,000 or Dream 10,000. This is if you're just getting started with outbound and you need just really high intent leads, take all the research off your plate. The hardest part is writing the message and that is gonna take the most time for you to do the investment in order to fully automate that.
09:24But until you get that built, the easy part is the research. Use these AI tools to surface really great leads for you based on the fact that they just meet some crazy criteria that only three leads a day are gonna be able to reach. The fact that they're attending or sponsoring an event and that it has something to do with your industry or you know that they're a good fit because you use something like they're hiring for a job description and then accomplish the work of that job description using Codex or Claude code and use this Dream 100 strategy.
09:53But instead of manually do everything, scale that to a Dream 1,000 or Dream 10,000 strategy because you can use Codex to scale the the output of the free value that you're gonna be giving all these companies.
10:05And now you could just reach out to them with this Dream 100 strategy and say, hey, I saw you're hiring for this person. You might not need to hire for them because I could do it for you or or I'm the perfect person or we have a service for that or we have a product for it. This is what the output would look like that if you were to work with somebody like us.
10:19I saw that you needed an ABM list or something. Right? And so, uh, I hope this is useful.
10:23If you're a Codex fan, just do all of them in Codex. If you're a Cloud Code fan, do them all there. Do them wherever you want.
10:29I hope you get use out of them. Thanks so much for watching.
The Hook
The bait, then the rug-pull.
Cold outreach doesn't need more sophisticated tooling, it needs simpler, higher-intent research, and three unglamorous AI workflows can generate that research on autopilot every single day.
Named ideas worth stealing.
05:05concept
Dream 100 (AI-scaled)
Chet Holmes's classic strategy of building a list of 100 dream customers and doing whatever it takes to earn their attention, updated with AI: instead of manually researching and creating free value for 100 accounts, use Codex or Claude to generate personalized free value for 1,000 or 10,000.
Steal forany outbound campaign targeting a defined ICP where personalized free value would outperform a generic cold email
00:27list
Daily high-intent lead search (parallel.ai)
- Define one hiring or intent signal (e.g. 'first GTM engineer hire')
- Query parallel.ai daily via Slack or a scheduled Claude Code/Codex task
- Maintain a running dedupe list so it never resuggests a company
- Enrich each hit with Clay/Prospeo to find the decision-maker's validated email
A recurring, narrowly-scoped AI search that trades lead volume for lead intent.
Steal forany B2B outbound motion built around a specific buying signal
How they asked for the click.
VERBAL ASK
03:06link
“There's a free Clay template that does all of that for you... The link's in the description, and grabbing through that link will make sure you get some extra clay credits as well.”
Soft mid-roll plug woven into the workflow explanation itself, the template does the exact enrichment step just described, not a separate ask. The video closes with 'thanks so much for watching' and no hard CTA.
MENTIONED ON CAMERA
FROM THE DESCRIPTION
PRIMARY CTAWhere the creator wants you to go next.
AFFILIATECommission earned if you click.
OTHER LINKSAlso linked in the description.
Visual structure at a glance.
