Podcast Summary: Startup Stories - Mixergy

Episode #2286: Pepper: AI + people = > $10 million
Host: Andrew Warner
Guest: Anirudh Singla, Founder of Pepper Content
Date: November 17, 2025

Overview

In this episode, Andrew Warner interviews Anirudh Singla, founder of Pepper Content, which leverages AI and a human talent network to create high-scale, high-quality content for enterprises. Anirudh shares Pepper’s evolution from a content-writing marketplace into an AI-powered content growth engine with over $10 million in annual recurring revenue (ARR). The discussion covers business strategy, the practical blend of AI and human creativity, actionable tips for content optimization, and the future of content generation in an LLM-driven world.

Key Topics & Insights

Pepper's Business Journey and Scale

• Starting Out (Upwork/Freelancing Origins)

  • Anirudh began by trying to earn $2,500 for college on Upwork, Fiverr, and Chegg, discovering the fragmented global writing market and its potential for aggregation.
    • "I slogged about 17, 18 hours on Upwork, Fiverr, all these other tutoring platforms and made that happen." [00:53]

• Pepper's Marketplace Model & Growth

  • Initially, Pepper matched clients with Indian writers for lower costs, but the model evolved into a global, multimodal talent network (writing, design, video, etc) with 150,000 freelancers—working only with the top 3%.
    • "Our value proposition ... we have subject matter experts in retail, cybersecurity, crypto who are US native experts ... Pepper also produces content in 45 languages." [02:31]

• Revenue Milestone

  • Pepper recently crossed $10M ARR and now serves major enterprises like Atlassian, Sprinklr, Instacart, and ClickUp.
    • "We just crossed 10 million in ARR and we're now in the 10 to 25 to 50 journey." [00:32]

AI + Human Content Creation

• Evolution from Manual to AI-powered Workflows

  • Early adopter of foundational AI models—got early access to GPT-3 by directly emailing OpenAI founders. Built PepperType AI, attracting half a million users.
    • "We were the first 50 users to get access to this. I had cold emailed Sam Altman and Greg Brockman to get access." [03:56]

• Human & AI Roles in Content Generation

  • AI generates a first draft; humans review and edit, with sophisticated feedback/reinforcement loops built into Pepper’s workflow engine (Nimbus).
    • "So it's still a human engine, but it's heavily propelled by AI." [05:57]
    • "We have what we call a reinforcement loop ... We chain multiple prompts ... scrape all those top 10 URLs and see what all have they covered. ... All of that is already being done as jobs to be done by the AI just in part of the research." [06:13]

• Continuous Optimization and Refresh

  • AI-driven processes monitor results via Google Search Console and auto-refresh underperforming content, ensuring clients' sites remain competitive in search and LLM responses.
    • "...can re-optimize that content six months down the line if it's not performing. That's something that customers are loving..." [08:19]

Content Optimization for LLM and AI Search

Case Study: Humana Article Analysis

Segment: [09:01–13:32]

• Key Tactics for Ranking in AI-First Search:
  • Always include 'publish' and 'updated' dates: Freshness signals are crucial for LLMs.
    • "LLMs love freshness. So that's one way, small insight." [09:24]
  • Add TLDR/key point summaries at the top.
    • "LLMs want to summarize this in a microsecond ... If you can already summarize your existing content in a TLDR summary, that is huge advantage." [10:31]
  • Use comparison tables for clear, machine-readable data.
    • LLMs are "great at whipping up tables ... companies starting to do that is super interesting. ... They want to give a user a holistic sense and try to appear unbiased." [11:21]
  • Structure headings as interrogative questions for FAQ/schema optimization.
    • "If you convert the subheadings into interrogative questions ... suddenly now your website's already FAQ optimized..." [12:58]

Expanding Beyond Written Content: Video and Image Automation

• AI-generated Videos

  • Using Sora, Synthesia, and proprietary AI avatars to turn scripts into short-form videos (for platforms like Instagram/YouTube).
    • "We're helping them create hundreds of videos ... which can be then run as a performance ad with colorful creatives." [18:28]
    • "You're then having a talking head using Synthesia or some other tools ... plus an audio, an AI generated voice, all creating a video that's going on Instagram and YouTube." [23:36]

• Voice & Avatar Tools

  • 11 Labs for synthetic voice; Synthesia and custom AI avatars for talking-head presentations.
    • "We use tools like 11 labs, which help us with voice ... we can have a human be generated completely from AI." [21:09]
    • Discussion on future ability to have fully AI-generated podcast guests. [22:14]

• Automated Creative Assets for Enterprise

  • AI tools like Runway (video), MidJourney (images), create banners, push notifications, and ad creatives at massive scale (e.g., 30,000+ creatives in 6 months for DoorDash/Instacart).
    • "We've created these custom engines ... at scales like 30,000 creatives over last six months. ... We're A/B testing this with data to see which creatives work..." [25:39]

Authority and Distribution: Practical Advice for Small Content Creators

• If You Can't Afford Pepper:

  • Don’t just rely on ChatGPT output—add authentic, expert-driven content.
    • "Don't go in for the staple, put it on ChatGPT, get whatever it's throwing out and put it out. You need to make content more intuitive." [27:27]
  • Build domain authority by putting videos/posts on LinkedIn Pulse; reference yourself to build trust signals.
    • "I'd create a lot of content on LinkedIn Pulse ... you'll see LinkedIn gets cited almost on 12% of ChatGPT citations." [27:57]

• Own Your Niche

  • "It's a lot about owning a niche and building that authority very strongly." [29:24]

Maximizing LLM Presence — Reddit, Wikipedia, and Beyond

• LLMs Source from a Broad Internet Pool

  • Pepper analyzes not just SEO but “Geo” (Generative Engine Optimization): optimizing content for LLMs citing across platforms like Reddit, Quora, Wikipedia, etc.
    • "It's not about SEO being dead, it's now SEO plus geo. ... You need to think about platforms like Reddit, Quora, having the Wikipedia page." [13:42]

• Reddit Playbook

  • Advise clients to organically build communities and share expertise on Reddit, not just create promotional posts (which leads to bans).

    • "Reddit is a highly strongly moderating platform ... treat Reddit as a social media channel ... get people from their product teams ... start posting out on queries..." [30:42]

  • Automation: Pepper scans Reddit for relevant threads for clients to authentically engage with.

    • "We have an automated way to pull up threads which you should be answering..." [32:21]

Notable Quotes & Memorable Moments

• On AI's Expanding Ability
  "If you put content on a number line of 1 to 10 ... one to four, which is high volume, low value content will get automated and everything above that 5 to 10 will need experts enabled by AI." [03:56]

• On Freshness for AI Search "There's a 25% probability your content will get surfaced up better if you map out freshness ... LLMs love freshness.” [09:24]

• On Reddit and LLM Training
  "ChatGPT is a search engine that gives you answers based on what someone said on Reddit five years ago." (paraphrased by Andrew, referencing Sean Pory) [30:33]

• On Human vs. AI Video Creation "At least in short form video it is AI slop ... but it's still doing well ... One has to eventually create that workflow with scriptwriters and ... people have to use these tools." [20:56–21:09]

• On Bootstrapping with AI “Engineer these growth loops into content. So just be smarter about it. Don’t just, you know, copy paste from ChatGPT...” [28:04]

• On Cold Emailing OpenAI
  "I cold emailed Greg Brockman, ... and I got a reply from Greg in less than an hour from sending an email when they probably had less than 50 users, GPT3." [32:58]

Practical Takeaways & Actionable Tips

• Content Refresh is Critical: Use AI to continually update and republish content, signaling freshness to search engines and LLMs.
• Summarize for Machines: Always include TLDRs/key point sections at the top; use tables for comparisons.
• Format for Questions: Turn headings and subheadings into questions to optimize for LLMs and FAQ schemas.
• Diversify Content: Create text, videos, and images using AI tools, but layer human creativity and authority for quality/impact.
• Distribute Across LLM-friendly Platforms: Publish content on LinkedIn Pulse, Wikipedia, Reddit, and Quora—where LLMs look for authority.
• Engage Authentically on Reddit: Treat it like a real community; don’t spam.
• Automate Where Possible, Review Always: Combine workflow automation with expert human review for scalable, high-quality outcomes.

Important Segments & Timestamps

• [00:32] — Pepper crosses $10 million ARR
• [03:56] — Early adoption of GPT-3 and integrating AI into Pepper’s workflow
• [06:13] — The technical breakdown of Pepper's AI+human content generation
• [09:01–13:32] — Deep dive into optimizing content for LLM/AI search with real examples
• [15:41] — Automating content updates and client results tracking
• [18:13] — Video content via AI; tools and workflow
• [25:39] — Generating creative images and banners using AI at scale
• [27:27] — Advice for small creators on competing using free/cheap AI tools
• [30:42] — How brands should use Reddit for long-term authority with LLMs
• [32:58] — The OpenAI cold email story
• [34:29] — Anirudh’s personal use of AI for time management and productivity hacks

Tone of the Episode:
Engaging, practical, rapid-fire, and technical yet accessible. Andrew asks sharp, clarifying questions and Anirudh delivers both high-level strategy and nitty-gritty operational wisdom, always focusing on how founders, marketers, and creators can use AI not just as a tool, but as a force multiplier.

This episode is packed with immediately useful tactics for anyone involved in content, marketing, or building tech-driven businesses.