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Creating with AI is fun. Turning it into a growing business is even more fun.
Andrew Warner: [00:00:00] I read about a guy who uses AI and people to create over three quarters of a million pieces of content, so I asked him to do an interview about how he does it. [00:00:09] Let's watch. Annie Ru. SLA is the founder of pepper, which uses AI and humans to create content for enterprise clients. [00:00:18]
Intro: The next new thing,
Andrew Warner: sla, what's your revenue right now at Pepper?[00:00:27]
Anirudh Singla: So we just crush 10 million in a RR and we're now in the 10 to 25 to 50 journey. So yeah, being, uh, [00:00:36] it took us some time to get us here, but, uh, yeah, very excited to finally cross this.
Andrew Warner: When you were working on Upwork as a writer, how much money were you [00:00:45] making a year then?
Anirudh Singla: You know, it's, it's funny. Uh, so I just for reference, I, uh, I was trying to figure out a way to finance my education, and the [00:00:54] goal was to earn.
$2,500 in two months, and I've never earned a single penny, uh, in my life. Um, [00:01:03] and I slogged about 17, 18 hours on Upwork five or all these check and all these other tutoring platforms and, [00:01:12] uh, made that happen. And, you know, that actually gave me this one very unique insight that, you know, hey, I put in the hustle and the slot to get this done, [00:01:21] but there's a real need out there where.
There's like, like I discovered these Facebook groups, which are like hundreds and thousands of writers at that [00:01:30] time, and I figured someone needs to aggregate this market. There's huge value. And uh, if you just recently saw Mercer, which. Went crazily [00:01:39] to, I don't know, two 50. There is two 50, 300 million event, uh, like uh, two 53 million where they're getting freelancers to train on AI [00:01:48] data sets.
So just see how the journey moved from, you know, people going from content production to not train AI data sets.
Andrew Warner: And the story as I understand [00:01:57] it, is you said this is way too difficult to find another writing gig. Every time I have to look, I end up spending more time looking and dealing with the.
Business of getting writing work [00:02:06] than actually doing the writing, which is what people are paying me for. Yes. There's gotta be a better way, a better model. And you created it, you called it pepper content, and it was a marketplace where you [00:02:15] personally, at first were matching customers with writers. The writers were in India, so the price was lower than it might be where you are today, which is San [00:02:24] Francisco.
Right. That's the, that's the model that you had.
Anirudh Singla: Yeah. And you know, the model evolved quite heavily where we now have a global talent network. So we have [00:02:33] about, uh, close to one 50,000 freelancers
Andrew Warner: Okay.
Anirudh Singla: Who've applied to write for Packer. And this is not just now [00:02:42] writing as well. Uh, so, uh, just a minor correction.
We also do design video production, and so it's a multimodal in terms of what we [00:02:51] do. And the talent pool is now global. 50% of our user base on the talent marketplace side sits out of the US so, [00:03:00] okay. And we work only with the top 3%. So our value proposition to an enterprise today is we have subject matter experts in retail, [00:03:09] cybersecurity, crypto, uh, who are US native exports, and we're also working with global organizations who need regional [00:03:18] exports.
So pepper also. Produces Continent 45 languages. So we right now are working on. With customers where someone needs [00:03:27] Arabic strategy for search or someone needs, uh, a native Chinese transcription. So we have that [00:03:36] level of, you know, global imprint so far from, you know, where we started on
Andrew Warner: and also far from just humans.
AI is the next thing. [00:03:45] How did, uh, how, how does AI and humans, how do AI and humans work together with you?
Anirudh Singla: Yes. So I'll give you a quick evolution of how [00:03:54] Pepper also evolved. So we started off with this managed services marketplace for content production where we were matching customers and these writers.
And [00:04:03] then, um, we tumbled upon this thing called Chad called GPD three, and this is two years before Chad GPT. This is [00:04:12] 2019 we are talking about.
Andrew Warner: Mm-hmm.
Anirudh Singla: And we were the first 50 users to get access to this. I had cold emailed Sam Altman and Greg Brockman to get access. They were happy to give it [00:04:21] to us. And uh, we realized very soon that, you know, if you put content on a number line of one to 10.
Uh, there [00:04:30] is probably, and, and you know, this is my prediction that time and obviously the strengths changed. One to four, which is high volume, low value content will get automated [00:04:39] and, uh, everything above that five to 10 will need experts enabled by ai. I can say safe to say that with ai, now it's one to seven or one to eight, and [00:04:48] we keep getting better and better.
And that's when we realized that AI needs to be. Natively embedded in workflows, uh, to [00:04:57] produce content at scale and do it effectively. So we built a lot of tools. We built this tool called PEPPER type ai that was an AI [00:05:06] writing tool that scaled from zero to half a million users while we were running the marketplace.
And we realized that, hey, there, there needs to be this marriage, which embeds both. [00:05:15] So we started building in this agentic technology called limbus. Which combines how AI can enhance [00:05:24] humans to produce content at unparalleled scale, but while still having a human review layer or editorial layer in picture.
So [00:05:33] it's still a human engine, but it's heavily propelled by ai. And just for reference, we have now about 500 custom apps. [00:05:42] Which are powering, uh, you know, this human plus AI content engine for the world's largest enterprise brands, while ensuring there is human level [00:05:51] quality checks.
Andrew Warner: But the first layer is AI starts the work, creates the first draft always.
Then a human being takes over from there. Do you [00:06:00] then take what you've learned from how the human being adjusted the AI content and feed it back in for Yes. You do. Talk to me about that.
Anirudh Singla: Yes. So [00:06:09] we have, uh, what we call as a reinforcement loop. Where, um, and it's not just, uh, Andrew about AI engineering the first draft and the [00:06:18] human reviewing it later with, as part of the platform technology we have built called Nimbus and we're publishing a lot of blogs on our website now, which talk about [00:06:27] how Nimbus works.
We are able to, uh, create unique insights and fetch data from a lot of sources [00:06:36] and throw that into the LLM. And it's not like I'm gonna charge GBD and putting in a topic. Saying, Hey, help me create content on this and it gives me something. And I use [00:06:45] that. Uh, we chain multiple prompts and these are very complex prompts that we write for enterprise customers.
And we chain those [00:06:54] responses and each response is output goes as the input of the next response. So for example, I want to create an article on something. [00:07:03] I'll pick up that topic. Uh, um, my platform technology called Numbers. What I'll do is. Uh, we create workflows where we put the topic on erp. [00:07:12] We will see the top 10 URLs that come in.
Our platform will scrape all those top 10 URLs and see what, uh, what all have they covered, [00:07:21] what are the edge ones, edge twos, all of those things. We combine all of that intelligence into one flow and then identify what's the most optimized [00:07:30] SEO focused. Article, uh, and obviously now it's g Also we are also inculcating workflows.
You need to optimize for AI search as well.
Andrew Warner: [00:07:39] Okay.
Anirudh Singla: Into the brief when the article's getting produced. So it's not just about producing an article, it's about producing an article which can optimize and [00:07:48] rank. And we are taking insights from what's already ranking from competitors. And uh, what we also end up getting is a human who used [00:07:57] to end up doing comparisons across 10.
Competitors seeing, hey, they've added this, they've added this, all of that. It's already being done as jobs to be done by the [00:08:06] ai, just in part of the research. And then, uh, we get the human, uh, we get, get the draft generated. We have a human review it, uh, it [00:08:15] goes live. Then we do another two, three things. We also look at data from Google Search Console and also have figured out workflows which [00:08:24] can reoptimize that content six months down the line if it's not performing.
That's something that customers are loving Pepper's technology for, [00:08:33] where people have websites which are like thousands and 10 thousands of pages of content, which they produce sometime or the other, but it's probably not doing anything to the business [00:08:42] today. How can we reoptimize that content automatically to start driving more hates and traffic?
And that also helped in Pepper's [00:08:51] evolution as a company to now a content led growth company.
Andrew Warner: Okay. You and I were looking at a Humana article earlier today where you [00:09:00] said, this is an indication of how content can be written. Let, lemme bring it up right now. Tell me why this is good. What am I looking at [00:09:09] here that says that is leading it to perform?
Yes, especially well in results for AI searches. [00:09:18]
Anirudh Singla: Yeah, so I'll, I'll give you a quick, uh, you know, analysis on this. So if you start at the top, you'll see this one thing [00:09:27] called publish date and updated date.
Andrew Warner: Mm-hmm.
Anirudh Singla: Right now this is very powerful. You'll be surprised. So just for [00:09:36] reference, all L lamps, uh, give, there's a 25% probability that your content will get surfaced up better if you map [00:09:45] out freshness of content.
So this is actually a signal to the LLM that this content was recently updated.
Andrew Warner: I
Anirudh Singla: see. So LMS [00:09:54] love freshness. So that's one very small insight
Andrew Warner: by the way. You go down further small note, the published date was April 21st. The [00:10:03] update date is April 16th. So this seems like a bug or some kind, right? Yes. But okay.
Anirudh Singla: Yeah, that's, that's probably a bug. But, but [00:10:12] if you get, yeah, that's a bug right now, uh, on this. But just to get you a sense that. Notifying the LA when this was last updated is like the, [00:10:21] you know, one of the school hacks that is driving a lot of search. Okay,
Andrew Warner: so that's
Anirudh Singla: one. If you go down further,
Andrew Warner: keep going further.
Anirudh Singla: Okay. That's one. If you go down further, you'll see this key points, you [00:10:30] know, summarization, it's like A-T-L-D-R summary of the article. Now, if you normally have seen, we've all been, you know, brought up with this logic of. [00:10:39] Throw everything you have on that topic in that article and make this like a 3,500 word long form article.
Guess what? The user doesn't care. They want to get [00:10:48] their answers in a very simple manner. And the L LMS wanna summarize this, uh, in a microsecond split decision. So [00:10:57] if you can do the job for the LL, if you can already summarize your existing content in A-T-L-D-R summary. That is huge advantage.
Andrew Warner: I see that.
So I've [00:11:06] taken one more step away from the LLM. It doesn't have to, it doesn't have to summarize it to analyze whether it should provide it. Okay. So that's the next thing. I like that. Exactly. That's the key point [00:11:15] section.
Anirudh Singla: Now if you go down further, if you see there is compare Medicare supplement plan costs.
Mm-hmm. Now see how it's giving an [00:11:24] example. If you see how LMS respond, they're great at giving these example structures because people are going in and putting in comparison [00:11:33] queries. They wanna know differences between different plans. Mm-hmm. And you'll see LMS are very great at whipping up tables. So if [00:11:42] you go down further below, you'll see this table summary, which is almost like a comparison analysis, uh, which gives you a sharp [00:11:51] understanding of what's working, what's not.
Companies starting to do that is super interesting, so you'll start seeing that these are things that [00:12:00] drive a lot of LMS to suddenly start pushing out this data because they want to give a user a holistic sense [00:12:09] and try to appear unbiased. Okay,
Andrew Warner: I get it. I've heard that too, that this kind of data is what the user wants and so you might as well put it in a table [00:12:18] and make it easy for the LLM to give it to them.
Anything else I should see here?
Anirudh Singla: I have a few factors that they could, you know, use to even further optimize this better. [00:12:27] Uh, if you see the H ones and the H twos, the headings, right? The, or the subheadings. Mm-hmm. If you convert those subheadings into interrogative questions. [00:12:36] So instead of sentences, if you would've written, uh, how, how, what are the factors that affect your Medicare supplement plans?[00:12:45]
Instead of, of what's written here, which is
Andrew Warner: factors that may affect your Medicare plan cost.
Anirudh Singla: Yes.
Andrew Warner: That's the title you're saying turn it into a question would've been even better because [00:12:54]
Anirudh Singla: interrogative question, because FAQ schemas are, uh, and FAQs are driving a lot of this growth, uh, in terms of user [00:13:03] discovery.
Andrew Warner: Mm-hmm.
Anirudh Singla: So people are seeing, like we've worked with customers where they've. Seen massive traffic uptick just on converting the H ones and H twos into [00:13:12] interrogative questions.
Andrew Warner: Okay?
Anirudh Singla: And that's something that can be done across the website because suddenly now, uh, your website's already FAQ optimized, [00:13:21] uh, and it's, you know, being built, uh, and showing trends based on that.
Andrew Warner: Okay, I'm with you now. I see this and this is what you do [00:13:30] at scale. How many articles would you say that Pepper, uh, is responsible for creating a day?
Anirudh Singla: So, uh, just for reference, we've done about [00:13:39] seven 50,000 articles, uh, till date. Uh, there have been months where we've done 30,000 articles a month.
Andrew Warner: Mm-hmm.
Anirudh Singla: So we've [00:13:48] seen scale of all kinds. Um, right now what we are focused more on is not just, you know, huge volume content production, but [00:13:57] content which will actually drive meaningful outcomes. So Pepper's now evolved into a content like growth engine. Where we're helping companies show [00:14:06] up on AI search, uh, through our own platform.
And the interest, interesting part is we have workflows [00:14:15] built in. Uh, these are autonomous workflows, which can accelerate content velocity, which can accelerate things like content [00:14:24] refresh, which can give you a sense of what are low hanging suits that can help pick up traffic at scale. Because if you see.
[00:14:33] 80% of the websites in the world, traffic's been going down. People don't know how to respond. So we are working with CMOs. So we do a lot of these [00:14:42] CMO dinners. So we've done like 40 CMO dinners over the last one year, and you'd be surprised, everyone's still not able to get [00:14:51] that. You know, it's not about SEO being dead, it's now SEO plus GEO, we call it GEO, generative engine optimization, [00:15:00] which is.
Uh, it's creating new real estate in the internet and suddenly it's not just about optimizing your own website. You need to think about platforms like [00:15:09] Reddit, Cora, uh, haling, a Wikipedia page. You'd be surprised we've literally created 15 Wikipedia pages or helped create that [00:15:18] over the last few weeks. So there is this huge value in now starting to analyze what factors do lms, uh, spend [00:15:27] a lot of time giving weights to.
And, uh, that's how UF two now think innovatively about organic content and search. [00:15:36]
Andrew Warner: And what you're doing is automating a lot of it. And so, for example, if a page has been published and it's, it needs to be refreshed, your software will [00:15:45] automatically refresh it and add the new updated time to the top of the post.
If you're seeing that something's not ranking, you are looking at Google Search [00:15:54] Console, understanding what's going on and editing the page for your client in real time.
Anirudh Singla: Updating their pages and Andrew, it's also giving them visibility [00:16:03] on where they get shown up on lms. So we built this platform called Atlas, which is our own proprietary tool.
Which where [00:16:12] we define a universe of prompts that could potentially get you, uh, that probably users are using for. And we have these volumes attributed to those [00:16:21] prompts. Uh, and we throw those prompts on these five different lms like cloud publicity, charge, GBD, Gemini, and so, and all of that. [00:16:30] And we see where all is your brand getting mentioned?
Andrew Warner: Mm-hmm.
Anirudh Singla: Uh, and we start seeing is your brand getting mentioned? Do you have citations? [00:16:39] Are m picking up cotton from your website or not? And once we get that analysis and most companies are doing, uh, don't get a great [00:16:48] analysis because of them not being LLM ready, we then give them a comprehensive checklist of here are the 10 things you need to fix.
These are the low hanging [00:16:57] fruits. And then we have technology which can automate a lot of those jobs to be done that they would've probably needed like 10 people to do. [00:17:06] In a far effective manner, but like I said, our differentiation is we're a platform plus service. So it's a solution [00:17:15] versus it just being like a tool that a company can use and be happy about because, uh, fundamentally the lift needed to pick up things like this [00:17:24] is huge.
Like we work today with Atlassian Sprinkler Clickup. Uh, uh, Instacart. These are big enterprise companies [00:17:33] which care a lot about organic search, driving a big part of their business. And, uh, for them, impact is directly linked to [00:17:42] revenue. Uh, so we now think a lot about speed in terms of how can we get organic transformation in these enterprises.
And one big [00:17:51] learning and what I wanna share also is video search is going to be huge. We are helping companies show up and start [00:18:00] producing a lot of content on YouTube because soon L LMS will actually push up videos a lot more.
Andrew Warner: How? How are you doing this now? Traditional articles, it's not, you [00:18:09] and I talked before we got started about how it's not just human beings creating videos.
You are using SOA and other tools to create videos using ai. [00:18:18] When you're using soa, you're not using the SOA like social app, are you? No. What are you using?
Anirudh Singla: No. So what we have is obviously all of these models and their [00:18:27] API is integrated, and like I told you, we have built in agent technology, which allows us to create custom maps and custom workflows for customers.
So [00:18:36] imagine we're working with a travel tech company where we are helping them create. Hundreds of videos, which are performance marketing ads.
Andrew Warner: Mm-hmm.
Anirudh Singla: Uh, on [00:18:45] Instagram where, um, we're putting in the text almost converting a top 10 places to visit, uh, say in West [00:18:54] Coast into like almost a reel. Uh, which can be then run as a performance ad wait me user with colorful creative
Andrew Warner: now gimme [00:19:03] this whole workflow.
So you're using AI to create Yes. Videos that you know will perform. And they're doing, when they do well on search, you buy ads for them. So where do you find the [00:19:12] content? How do you know what content to turn into? Videos on Instagram and YouTube.
Anirudh Singla: Yes. Yeah. So if you see most of Instagram and TikTok, [00:19:21] uh, they've just become indexable on search Instagram specifically.
So, which means LMS can now actually go through your video.
Andrew Warner: Mm-hmm.
Anirudh Singla: And see all the text [00:19:30] you have on your video and then drop that video off specifically.
Andrew Warner: Okay.
Anirudh Singla: So it's become machine readable metadata. That's why what we do is we pick up [00:19:39] all these listicle kind of topics and queries, like top 10 places to visit in West Coast, or here are the five things, you're not doing all those article [00:19:48] content, which no one now reads.
But once you love seeing good videos and visuals about, we, you know, create summaries [00:19:57] through, you know, a, a normal article builder, we then convert it into a video script. And then video script is made punchier with respect to audience cohorts. [00:20:06] So we have like, we work with customers who define either 10 audience cohorts you might wanna build on.
We create 10 scripts. We base each [00:20:15] script. We then add in the video elements and the brand elements that they care about. Get a video popped out. Um, play those videos organically, see which [00:20:24] ones perform, do AB testing and then run ads on the ones which perform the best. This is like agentic workflows and, and, and telling you [00:20:33] these videos very soon are going to start popping up on search instead of that article you were reading from, you know?
Right. Maybe booking.com.
Andrew Warner: Okay. And [00:20:42] who's doing the voice? What tool are you using for voice? What tool are you using to get the writing to not feel like AI slop or is it AI slap And that's okay right now? [00:20:51]
Anirudh Singla: Yeah. At least in short form video. It is AI slack, uh, and it is getting better. As you know, these models become more,
Andrew Warner: but you're saying it's [00:21:00] say I slop, but it that you're producing, but it's still doing well.
Anirudh Singla: It's still doing well, but I'll tell you, it's not sustainable long term. Mm-hmm. So one has to eventually [00:21:09] create that workflow with script writers and, you know, basically smarter people have to use these tools. It's not like, you know, a normal [00:21:18] person can just go in and write in this and get this out. You need person with creative input, creative output, understanding to get this workflow in place.
Andrew Warner: Okay. [00:21:27]
Anirudh Singla: Uh, we use tools like 11 Labs, which help us with voice.
Andrew Warner: Mm-hmm.
Anirudh Singla: And we're using, uh, we're also, uh, you know, building a lot of [00:21:36] synthetic AI models where we can have a human be generated completely from ai. So imagine, I, you are speaking and [00:21:45] we have a platform which understands how we are speaking, uh, on a live basis.
Then starts mimicking us and then starts the next [00:21:54] time I end. You don't need to get on a podcast. You can just speak to Eros ai avatar, who's going to make the same, you know, uh, hand moments, [00:22:03] hand gestures, facial expressions. And probably speak to you in a much better condensed manner than I am doing.
Andrew Warner: You know what?
I've, um, I've used 11 [00:22:12] labs for audio and it works so well that when I do it for people using their voice, they can't tell that they didn't talk. They think it's them, and that I captured a video of them somewhere. [00:22:21] Um, I understand also how to use AI to write in a certain voice. Like you can kind of write using my voice.
There's enough content out there. [00:22:30] What about video? Are you saying now that you can even have talking head or do you need to have images? Only? Can you do a talking head like me and move and gesture and everything You can. What are you using for [00:22:39] that? That works?
Anirudh Singla: Yes. So, so there are a lot of proprietary tools right now, so these are not like, you know, MAs tools at this point.[00:22:48]
Uh, we're experimenting with a lot of them. Nothing where I've seen huge success where I can tell you that, you know, hey, this definitely works. But I can tell [00:22:57] you this entire concept of Synthesia, I don't know if you've heard of them,
Andrew Warner: Uhhuh.
Anirudh Singla: They, they've now obviously expanded into a much larger company.
Uh, I [00:23:06] used to, uh, you know, I had a friend, uh, who should on this company called rephrase.ai. Which used to do this, which was basically, um, uh, [00:23:15] synthetic voice cloning. And, uh, they got acquired by Adobe eventually because Adobe wanted to introduce them in their gen, ei, [00:23:24] uh, you know, platform features. But there's hundreds and thousands of experiments being built and run on these things.
Andrew Warner: Are these good enough right [00:23:33] now that Pepper is using any in their videos? Are you using Synthesia? Are you, you are. You are using Synthesia. So here's, here's what I understand that you're doing. You are [00:23:42] finding articles that work already in a format that people just aren't going back to, which is text.
You're turning them into scripts. You now have a [00:23:51] script that works. You're asking for, um. Based on the, the user that this script needs to be customized for. You're customizing the script. You're then [00:24:00] having a talking head using Synthesia or some other tools. You're still playing around with what works best.
You have a human being plus some images that go on top plus [00:24:09] an audio. Uh, an AI generated voice. Yes. All creating a video that's going on Instagram and YouTube. We're not talking about stuff that's competing with Mr. Beast or Mark Rober, [00:24:18] but we're talking about stuff that com that competes with texts with people aren't reading anyway.
Got it. And you're saying we're going to keep iterating and improving it. I see what you're doing and the tools [00:24:27] that Right now that, I'm sorry. Go ahead.
Anirudh Singla: And you know, the vision with it is not just the perfecting workflow, it is to engineer growth. So [00:24:36] we're thinking about content led growth where we're saying, can I engineer growth where I create a hundred videos, which can get you potentially [00:24:45] this engagement rate or half a million views.
And it's imbued with data. So we know the search volumes are the keywords. There are a lot of tools like Red iq, [00:24:54] which tell you search volumes on YouTube. Uh, you can also have, there are a lot of tools. Mr. Beast also has one of his own tools around that, right? Um, [00:25:03] and once YouTube analytics is getting very good, uh, and similarly, all of these other platforms, analytics are getting better.
If you can first back those analytics [00:25:12] into the workflow process, you can re-engineer how you can do content better. And that's what we're about
Andrew Warner: driving. I have no idea you're doing all that. [00:25:21] Okay. Images too. You and I were talking before we got started about Cling and other tools that you're using because it's not just for text, it's [00:25:30] not just for video.
What are you doing with images and what AI tools are enabling you to do that?
Anirudh Singla: Yes. So we use, uh, a bunch of AI tools that we all, [00:25:39] all the, uh, standard ones including run, uh, you know, runway for video, uh, mid journey for creative. Uh, what we're seeing very interestingly [00:25:48] with this is we're doing a lot of always on creative content.
So imagine you go on DoorDash and Instacart app, you'll see these [00:25:57] banners floating around, which are off banners, or which are talking about deals and all of that. Yeah. Now imagine, and you'll be surprised, most large [00:26:06] enterprises still do it humanly in a manual manner, including the push notifications, including the traders and all of that.
We've created these custom [00:26:15] engines which can produce banner images, add creatives at scales, like 30,000 creatives over the last six months, [00:26:24] and we're eeb testing this with data to see which creatives work and then automatically that's skewing an engine to the LLM engine to refresh that creative. To [00:26:33] see how we can drive more CTRs up.
Okay. And with scale at say Instacart or DoorDash level, you'd be surprised that this translates [00:26:42] massively into revenue. So we are seeing CRM teams, or customer lifecycle marketing teams and all these big consumer apps heavily ITing [00:26:51] on, uh, AI usage in, um, no push notifications in anything customer comms, which could drive more revenue and acceleration off.[00:27:00]
Andrew Warner: If you were an individual owner of a content business and you couldn't hire pepper, because pepper is aimed for a higher [00:27:09] level of customer, right. Enterprise and middle market, I guess is the way that you've said it. Yeah. But if, if you are smaller and trying to create content using AI today, what [00:27:18] would you do?
What tools would you use? How would you think about it?
Anirudh Singla: Yeah, so I would recommend that don't go in for the [00:27:27] staple, put it on charge Bty, get whatever it's throwing out and put it out. You need to make content more intuitive. See, what's [00:27:36] happening is with this onslaught of AI slot being put out on the internet, uh, people need to be smarter about how they create content.
Uh, they have [00:27:45] to, and especially it's becoming harder with showing up on LMS as well. So you need to build in authority into whatever you're doing. So here's [00:27:54] what I would do. I would actually go and create videos and I'll start putting myself out on LinkedIn. I'll use those [00:28:03] videos and repurpose those videos into content and then create articles about me and then start referencing that he, uh, say [00:28:12] Inger spoke about this on A, B, C, and start building more trust signals around it.
I would create a lot of content on LinkedIn, pulse. Just [00:28:21] as a, uh, experiment, you'll see LinkedIn gets cited almost on 12% of charge GPT citations. So if I start, [00:28:30] I wanna build out a personal brand as a founder, um, you know, to drive leads for my business and eventually grow, I start putting out a lot of content on LinkedIn Pulse, [00:28:39] which starts to drive this narrative of a UGC growth lever, which NLM would want to promote.
And embed my video at [00:28:48] the top of the article and then have a summary of that down there. So you gotta become intelligent about the way you put out there [00:28:57] yourself. Like at Pepper, we have 320,000 followers on LinkedIn. I have 80,000 followers on LinkedIn, and we've seen that you need to [00:29:06] engineer these growth loops, uh, into content.
So just be smarter about it. Don't just. No copy paste from chat, c, b, d,
Andrew Warner: but post on my own [00:29:15] LinkedIn account about myself.
Anirudh Singla: Yeah. Like, uh, you can talk about, you know, hey, these are the things that you are, [00:29:24] uh, basically what you need to start building out on is authority. Yeah. And signaling, like, for example, look at you, you, you focus on [00:29:33] bootstrap giants.
That's, that's the theme, right? And today when I search about anything around bootstrapping, either you, Jesse, pick up, come up. So it's a lot about. Uh, [00:29:42] owning a niche and building that authority very strongly.
Andrew Warner: And I would do video you're saying, and post it on there. And you'd also do chat [00:29:51] GPT for scripts and for text.
But don't just take what comes outta there. Add the human element afterwards. Is that what you said? I.
Anirudh Singla: Yeah.
Andrew Warner: Okay. [00:30:00] Um, I like that by the way, I do see a lot of LinkedIn used in chat GPT and others, which frankly helps me. I looked you up on chat, GPT and I liked that it brought [00:30:09] up LinkedIn 'cause I would have to go and do it myself, if not, and there was a period there when they weren't and that was a pain in the neck.
You also mentioned earlier Reddit. Reddit is used all the time. [00:30:18] I, I, I don't think I'm gonna quote Sean, uh, URI properly, but he said something like, uh, chat, GPT is a search engine that gives you answers based on what [00:30:27] someone said on Reddit five years ago. And in many ways that is true. How do you as a company that works on mass, get Reddit post created?[00:30:36]
Anirudh Singla: Yeah, so, uh, our Reddit playbook to customers is about don't go out there and, you know, try to get. [00:30:45] A random, create a random posts about you, uh, getting created because Reddit will ban them. Mm-hmm. Reddit is a highly mo, uh, strongly moderating [00:30:54] platform. What we would say is pre-credit as a social media channel.
So what Reddit is now undergoing through, obviously they've obviously got a huge lot of [00:31:03] publicity. There's the 11th most visited website in the world. They've started creating and inviting brands to create brand pages on Reddit. And create [00:31:12] communities under it. So it's become like your social community platform.
Everyone's been thinking about, Hey, I wanna create my own community. Which platform should I list it on? I would say go to it [00:31:21] on it. Where engage with users, add value, do ammas, uh, and it's not just having, you know, marketing speak on Reddit, [00:31:30] because like I said, Reddit typically tends toban promotional posts.
You've gotta show value. Like some of the best companies I know are actually [00:31:39] getting people from the product teams and engineering teams on Reddit to start posting out on queries, which are helping them in deals. You'd [00:31:48] be surprised, and they're doing it authentically from their handle. It's not advocating, Hey, use us, it's advocating.
This is how you solve a problem. [00:31:57] So don't, you know, go the route of influencer marketing and all of that on Reddit. It's gray won't work. Build value, build it as a [00:32:06] social media channel and uh, do it credibly.
Andrew Warner: I see. And so at Pepper you don't have any automated AI driven way of doing it. You're just encouraging companies [00:32:15] to post on Reddit or are you.
Anirudh Singla: So we have, uh, an automated way to pull up threads.
Andrew Warner: Mm-hmm.
Anirudh Singla: Which you should be answering. [00:32:24] So what we've done is we have a Reddit module where we can scan through your website and the themes you want you care about, and pull out all subreddits and [00:32:33] all threads that need your attention in answering. So that at least gives you an intelligent way of how you can frame your content strategy on this chart.[00:32:42]
Andrew Warner: I see. Alright, I want, I'm keep coming back by the way. I don't wanna forget to ask you who had, uh, OpenAI, did you cold email, what did you write that got a [00:32:51] response from them?
Anirudh Singla: Yeah, so I primarily cold email Greg Brockman, who's a co-founder and president, and I ccd Sam Altman. [00:33:00] And I got a reply from Greg, uh, in less than an hour from sending an email, uh, when they probably are less than 50 users for GBD three.[00:33:09]
Andrew Warner: And what did you write that got a response? Was it just, I want to use this software that I've heard about?
Anirudh Singla: No, I think I, I think we, we kind of detailed out a use [00:33:18] case in terms of what we could do and so on. And I think, uh, you know, the good thing is the use case, ta stick sticks because we said, Hey, we have this marketplace of hundreds [00:33:27] and thousands of writers, which can be ai, turbocharged, and uh, aligned and we wanna build tools on.
These s which are [00:33:36] more personalized and customized for different platforms. So I think that that was probably the most, you know, sensible use case. That made sense. [00:33:45] Um, and yeah, I think they were, they gave us access. It took us 20 days to build out a platform called Pepper Type, which we launched on Product Hunt.
We were [00:33:54] number one product of the month and we got to a million, uh, uh, got to a half a million users in one year just for that tool. Uh, but we did realize that. [00:34:03] Just standalone tool won't help. You'll have to intricate this deeply into the workflows. So like, I've been giving examples this, that podcast about [00:34:12] naked IT workflow oriented, which can give value to the customer so that it can compound growth you don't solve for short term.
Andrew Warner: Alright, I wanna close it out with this. I wanna know how you [00:34:21] use AI personally.
Anirudh Singla: So what we're seeing, uh, so obviously run a very busy, tight studio, uh, managing multiple geographies, [00:34:30] customers. Um, I want to figure out how can I save more time for me? Uh, so I plugged in my calendar into charge GPT [00:34:39] and started audit and it, I told it to start auditing my calendar and starting to tell me which meetings are potentially time sinks or how can I [00:34:48] re-architect my calendar to make more sense.
Andrew Warner: Mm-hmm.
Anirudh Singla: Now, obviously it's trying to give me some good, interesting insights, which I'm starting to use and cut down meetings and [00:34:57] optimize them. What's gonna be gold for me is if I can marry my note taker with the calendar and Chad, GBD to [00:35:06] start actually seeing which meetings make sense or actually are driving high value outcome decision making for the business.
And if I can figure out that loop, I think that [00:35:15] this is gonna be pretty awesome.
Andrew Warner: I, I have an idea for how to do it. Um, and I know we're running outta town, but you tell me what you think of this. Go into your note taker and say, which meeting have I [00:35:24] talked less than 5% of the time? What, and then say, what is it about these meetings that is unique?
And frankly, you could even go back to chat GPT, which has access to your calendar and say, here are the [00:35:33] meetings that I didn't really talk. What is it about these meetings that they have in common? Now you have a new, uh, prompt that you can feed in and say, look at my upcoming meetings. Yeah, which ones [00:35:42] fit these criteria?
Does that make sense?
Anirudh Singla: But that makes a lot of sense and I think we can. Uh, and as you say, as you're saying, there's lot more workflows. We can keep [00:35:51] building on this, but I think, uh, I think what all of this has to lead towards insane productivity. Like, like we've been always talking about Connect Loan five of me.[00:36:00]
Uh, if that's possible, and hopefully we can make that happen. I think we're gonna skyrocket.
Andrew Warner: By the way, having interviewed the founder of Zapier about this, if you [00:36:09] do this in chat, GPT, I think you'd have to do it manually. If you use Zapier, it will every day be able to analyze, based on what we just said.
Alright. I would love to see, can I see the [00:36:18] email that you sent out to OpenAI? Can I share it with the audience?
Anirudh Singla: Can you see what street
Andrew Warner: it's coming up right now? Yes, I can. Yeah, here [00:36:27] it is. So
Anirudh Singla: this is to Greg, Greg Brockman, and this is first December, 2020. This is to years before charge GPT. [00:36:36] So we will manage marketplace of experts.
So we give them insights on what we can be doing, what, what could the benefits be, and we we could get access. This is me. [00:36:45] And yeah.
Andrew Warner: Responded so quickly.
Anirudh Singla: Yeah, this was, uh, in just a few, [00:36:54] yeah, one and a half hours.
Andrew Warner: Would you be able to forward that to me so that I can post it online? I won't, uh, I mean, their email addresses are super easy to find, but if I can post a, yeah, [00:37:03] an image of it, I think it'll help with the story.
Alright, killer. Thank you for extra time. Dude, you're so much better than I even hoped for. I knew that you were good, but. The way that you [00:37:12] were riffing on all these different AI techniques was just like, so both like
Anirudh Singla: possible and big, but at the same time, relatable. And today, anyway, I know
Andrew Warner: you gotta [00:37:21] run.
Thank you for doing this.