Your “source of truth” for customer acquisition isn’t GA4. It’s what people tell you when they sign up — and right now, that story is changing fast.

In this episode, we unpack a simple but brutally effective tactic: adding a required “How did you hear about us?” field to your signup form — and using that data to understand where real discovery is happening. The surprise? More and more B2B customers are saying social media, even when analytics tools claim otherwise.

But here’s the deeper shift: organic social is hard to measure… unless you track the right trailing indicator. That indicator is branded search.

You’ll learn how to use Google Search Console to track brand-name impressions over time, why it’s becoming the only KPI that matters for modern founder-led marketing, and how branded search creates a defensible moat competitors can’t easily steal.

If you’re planning your marketing strategy for 2026, this is the measurement system you need.

What You’ll Learn

• Why signup form attribution is often more reliable than your analytics dashboards
• The biggest B2B acquisition shift happening right now: from search → social
• Why organic social is nearly impossible to ROI… and how to measure it anyway
• The “branded search” metric that acts as a trailing indicator for social discovery
• Why branded search is a marketing moat your competitors can’t take from you
• How to build a branded-search chart using Google Search Console in minutes
• The exact prompt to pull branded impressions by query and track them over time

Timestamps

• 00:00:00 - Customer Discovery Starts at Signup
• 00:00:10 - The Shift: Search → Social
• 00:00:31 - Why Organic Social Now Matters Most
• 00:00:52 - The Measurement Problem (and the Fix)
• 00:01:12 - Branded Search = Your Trailing Indicator
• 00:01:33 - Why Branded Search Is a Moat
• 00:01:54 - Where to Invest Time, Money, and Energy
• 00:02:04 - The 2026 Strategy: Grow Brand Searches
• 00:02:15 - How to Track Branded Search in GSC
• 00:02:25 - Building the Branded Impressions Chart
• 00:02:46 - Live Demo: Google Search Console Setup
• 00:03:07 - Final Thoughts

Key Topics & Insights

1. Signup Attribution Beats Analytics (Almost Every Time)

One of the fastest ways to understand how customers actually found you is simple: add a required “How did you hear about us?” field in your signup form.
Why it works:

• It captures customer intent in their words
• It reveals channels analytics often misattributes
• It shows the real discovery story (not the last-click story)

And the punchline: it often contradicts what GA4 says.

2. The B2B Discovery Shift: Search → Social

If you’ve been paying attention to the data, something big is happening:

People aren’t discovering new software products through search anymore. They’re discovering them on social — then Googling them afterward.

This shift has accelerated over the past 12–18 months. Even in B2B, where trends typically lag behind DTC.

What this means:

• SEO is no longer the first touchpoint
• Social is becoming the top-of-funnel discovery engine
• Search is evolving into a validation channel

3. Organic Social Has a Measurement Problem

The hardest part about investing in organic social is that it’s difficult to tie to ROI.

Whether you’re doing:

• Founder-led content
• Creator sponsorships
• Community distribution
• Organic growth loops

…it doesn’t fit neatly into traditional attribution.

So instead of forcing bad ROI models, track the trailing indicator that proves social discovery is working.

4. Branded Search Is the Trailing Indicator That Matters

Here’s the key idea:

When someone discovers your product on social, they don’t click your link. They Google your name.

That branded search becomes the measurable proof:

• A discovery event happened
• People care enough to look you up
• Your brand is entering the market’s memory

This is why branded search growth is one of the strongest indicators of momentum.

If branded search is increasing month-over-month, your brand is winning.

5. Branded Search Creates a Defensible Moat

This is where it becomes more than measurement — it becomes strategy.

Branded search is difficult for competitors to steal. Once people are searching your name, you own that demand.

The only way competitors can interfere:

• They bid on your brand in Google Ads
• They try to outspend you
• Or they attempt to confuse the market

But that’s expensive, obvious, and usually temporary.

So branded search is not only a KPI — it’s defensibility.

6. How to Track Branded Search in Google Search Console

This is the tactical part.

To track branded search over time, you want a chart that shows:

• Impressions over time
• For queries containing your brand name
• Captured in every format your audience might type it

And this is surprisingly easy to pull from Google Search Console.

7. The Exact Chart & Prompt to Build It

The goal is to extract Search Console impressions where queries include your brand name.

Example prompt:

Then your job becomes simple:

Increase branded impressions month-over-month through:

• social content
• distribution
• creator partnerships
• podcast mentions
• repeated brand exposure
• consistent visibility

This becomes the clearest signal that marketing is compounding.

Action Steps (Do This Today)

1. Add a required “How did you hear about us?” field on signup
2. Review responses weekly (and compare against analytics)
3. Use Google Search Console to track branded query impressions
4. Create a monthly KPI: branded impressions growth
5. Use branded search growth as the scoreboard for your organic social efforts

Sponsor
Today’s episode is brought to you by Graphed – an AI data analyst & BI platform.

With Graphed you can:
Connect data like GA4, Facebook Ads, HubSpot, Google Ads, Search Console, Amplitude
Build interactive dashboards just by chatting (no Looker Studio/Tableau learning curve)
Use it as your ETL + data warehouse + BI layer in one place

Ask:
“Build me a stacked bar chart of new users vs. all users over time from GA4”
…and Graphed just builds it for you.

👉 Get a 14-day free trial with 10 seats for your team: https://graphed.com/

If you’re not getting cited by ChatGPT, your “AI SEO” strategy isn’t working, no matter what your dashboards say. Most of it is observability theater: dashboards, charts, synthetic prompts — and zero actual placement.

In this episode, we chat with Shawn Schneider, founder of Eldil AI, about what actually determines whether your company shows up in ChatGPT answers. The short answer: LLMs don’t reward more content, clever prompts, or prettier dashboards. They reward a small set of trusted third-party sources — and most brands aren’t mentioned in any of them.

Shawn breaks down why observability alone creates a false sense of progress, how to identify the specific citations that dominate your category, and how to turn that insight into real placements through outreach and negotiation. We also unpack why Google Search Console is still the best signal we have for AI-driven queries, how to prioritize the one citation that actually matters, and what the first 30–90 days can look like when you do this correctly.

Guest

Shawn Schneider — founder of Eldil AI, a GEO / AI SEO platform focused on identifying and securing the citations LLMs rely on most; helps brands and agencies win visibility in ChatGPT by targeting the power-law sources that shape AI answers.

Guest Links
LinkedIn: https://www.linkedin.com/in/shawn-schneider-61b2b5207/
Company Website: https://www.eldil.ai/

What You’ll Learn

• Why most GEO / AI SEO observability tools are meaningless without actual placements 
• The only thing that reliably improves AI search visibility: citation placements
• How to use Google Search Console to surface AI fan-out queries
• Why synthetic prompt data is still unreliable (and what to trust instead)
• The power law of citations: why only 1–3 sources actually matter
• How Eldil turns citation discovery into outreach and negotiated placements
• What 30–90 days can look like when you secure the right citation
• Which industries should invest heavily — and which should ignore this for now
• Why ChatGPT dominates referral traffic compared to other LLMs
• What happens when ads arrive inside AI search results

Timestamps

• 00:00 — GEO, AI SEO, AEO: noise vs. reality
• 00:21 — Why observability tools don’t move the needle
• 03:55 — Where GEO tools get their data (and why it’s messy)
• 07:16 — Using Google Search Console as a prompt proxy
• 09:40 — The three pillars: technical, content, authority
• 12:07 — Citations as the dominant ranking lever
• 13:07 — The power law: thousands of citations, one winner
• 19:07 — How fast results actually show up
• 20:39 — When building your own citation content makes sense
• 30:41 — Which business models win with GEO
• 37:11 — ChatGPT ads and the future of AI search
• 41:32 — Where to find Shawn and closing thoughts 

Key Topics & Ideas

1. Why dashboards feel good but don’t create outcomes.

• Most tools are essentially “Google Analytics for LLMs”
• ChatGPT referrals rise naturally as usage increases
• Charts go up even if you do nothing
• Without placements, observability is just vanity

2. The three common approaches in the market today:

• Guessing prompts with LLMs
• Clickstream data sourced from Chrome extensions and brokers
• Synthetic prompts without transparency

Eldil uses Google Search Console + Analytics as the best available proxy for real intent.

3. How to spot AI-generated fan-out queries:

• 50+ character queries
• High impressions
• Low or zero clicks

These often represent LLMs expanding short prompts into long-form searches.

4. The three pillars: Technical, Content, Authority

• Technical — can an LLM crawl and understand your site?
• Content — does useful information exist?
• Authority — does anyone credible back it up?

Authority is the multiplier most teams ignore.

5. What actually shapes AI answers:

• Citations are not backlinks, they are semantic explanations
• LLMs repeatedly return to the same trusted sources
• Third-party listicles and niche blogs dominate citation share

6. The Power Law of Citations

• 10k–15k citations may exist
• 200–300 matter
• 1–3 actually move the needle

If you’re not in those, content volume won’t save you.

7. The real workflow:

• Identify high-value customer questions
• Extract dominant citations
• Rank them by weight
• Contact site owners
• Negotiate placement
• Monitor AI visibility and referral traffic

This is where most tools stop — and where Eldil focuses.

8. How many placements do you need?

Surprisingly few.

• You don’t need 100 placements
• You need the right one
• Then expand into adjacent verticals

This is concentrated betting, not spray-and-pray SEO.

9. Why GEO feels different from traditional SEO:

• You are inserting into sources that already rank
• Changes can show up in weeks, not years
• Meaningful referral growth often appears within ~60–90 days

10. Who Should (and Shouldn’t) Do This

Best fit:

• High-ACV B2B SaaS
• Long buying cycles
• High-LTV e-commerce (supplements, skincare)
• ICPs that already live in ChatGPT

If your customers do not use LLMs yet, start elsewhere.

11. Why ChatGPT is the main event

Based on Eldil’s data:

• ChatGPT referrals dwarf Perplexity and others
• For most companies, this is where focus belongs
• Smaller channels still matter for high-ticket sales

12. What’s coming next

• Paid placements inside LLMs
• Organic plus paid becoming a one-two punch
• Citation inventory getting expensive fast

The window for cheap dominance will not last.

Sponsor
Today’s episode is brought to you by Graphed – an AI data analyst & BI platform.

With Graphed you can:
Connect data like GA4, Facebook Ads, HubSpot, Google Ads, Search Console, Amplitude
Build interactive dashboards just by chatting (no Looker Studio/Tableau learning curve)
Use it as your ETL + data warehouse + BI layer in one place

Ask:
“Build me a stacked bar chart of new users vs. all users over time from GA4”
…and Graphed just builds it for you.

👉 Get a free trial worth $500 plus a personal discovery call to set up your first dashboard: https://graphed.com/

Your brand doesn’t exist until it ranks on page one—and most founders have no idea how to make that happen.

In this episode, we break down the exact playbook for getting a brand-new domain to show up in Google for your company name. After going through this process firsthand with Graphed.com, you’ll learn how to choose a rankable name, build the right backlinks, trigger branded search behavior, and use Google Ads to accelerate the whole process.

If you're launching anything new, this is the tactical blueprint you wish you had earlier.

What You’ll Learn

• Why ranking for your brand name is the first real trust signal for any startup
• How to pick a name and domain you can actually rank for
• The “first 100 links” strategy that trains Google to recognize your brand
• Simple ways to generate branded search behavior across social and content
• How Google quietly tests your domain—and how to know when it’s happening
• How to use Google Search Ads to accelerate ranking and protect your brand
• Why .com still matters more than any other TLD

Timestamps

• 00:00 — Why your new domain must rank for your own brand name
• 00:31 — Why ranking for your brand name is a critical early trust signal
• 01:03 — The rookie mistake founders make when picking a brand name
• 01:13 — What ideal, non-competitive SERPs should look like
• 01:35 — Graphed.com’s journey to finally ranking in position one
• 01:45 — Overview of the process to teach Google your brand
• 01:55 — Step 1: Build backlinks to your homepage
• 03:29 — Step 2: Drive branded search with social posts & content
• 04:21 — Step 3: Run Google Search Ads on your exact brand name
• 05:45 — Why you should always buy the .com for your brand
• 06:16 — Final thoughts + Graphed free trial

Key Topics & Insights

1. Ranking for Your Brand Name = Early-Stage Trust

If someone Googles your company and doesn’t find you, credibility collapses. Ranking for your brand name is one of the first—and easiest—trust signals to secure. Graphed.com took ~2 months to rank, but with this framework, it can happen in as little as 24–48 hours.

2. How to Choose a Rankable Name

• Avoid names already used by active companies
• Look for search results filled with noise, not competitors
• Ideal: two words, few syllables, easy to spell
• And always, always buy the .com

3. Build the First 100 Backlinks (Brand-Name Anchors Only)

Your #1 job early is to teach Google what your company is.
Do this by:

• Building backlinks to your homepage
• Using your brand name as the anchor text (not keywords)

These are foundational “identity” links that help Google map brand → domain.

How to build them:

• Submit to software directories
• Use link submission services
• Cold email companies for guest post swaps
• Layer PR on top later

4. Trigger Branded Search Behavior

Once Google sees your backlinks, you need humans to reinforce the signal:

1. Search your brand name
2. Click your domain
3. Spend time on the page

Google then learns:

You create this behavior through:

• Social posts
• Newsletters
• Podcast mentions
• Repeated use of the brand everywhere

5. How Google Tests Your Domain

Google will quietly experiment by showing your domain for branded queries.
You’ll see this in Search Console via:

• Rising impressions
• Increasing CTR
• Sudden jumps in average position

This is the moment Google “decides” you belong on page one.

6. Accelerate Everything With Google Search Ads

Run a brand campaign:

• Exact-match brand keyword
• Minimum bid: around $5
• Send traffic to homepage

This forces the association between brand name → your site, and accelerates your rise in organic search.

Brand protection tips:

• Raise bids to block competitors
• Add sitelinks to take more SERP real estate
• Optional: multiple ad accounts (with caution)

7. Why .com Still Beats Every Other Domain

Consumers inherently trust .com more than .io, .co, .xyz, etc.
It drives higher CTR and reduces friction in word-of-mouth.
If the .com isn’t available, pick a new name—don’t settle.

Sponsor
Today’s episode is brought to you by Graphed – an AI data analyst & BI platform.

With Graphed you can:
Connect data like GA4, Facebook Ads, HubSpot, Google Ads, Search Console, Amplitude
Build interactive dashboards just by chatting (no Looker Studio/Tableau learning curve)
Use it as your ETL + data warehouse + BI layer in one place

Ask:
“Build me a stacked bar chart of new users vs. all users over time from GA4”
…and Graphed just builds it for you.

👉 Get a 14-day free trial with 10 seats for your team: https://graphed.com/

There’s a whole narrative right now that “vibe coding is a bubble” and all the MRR from AI-built apps isn’t real.

In this episode, we chat with Jacob Klug, founder of the agency Creme, which specializes in building lovable MVPs on top of tools like Lovable and AI coding assistants. Jacob makes the case that most of the “AI apps are trash” discourse is really a skill issue, not a tool issue—and he breaks down the exact process his team uses to ship full platform-level apps in two-week sprints.

We dig into how to scope and design software that doesn’t look AI-generated, how to think about personal operating systems vs. SaaS, why ideas are getting worse even as tools get better, and how creators and agencies can turn niche domain expertise into real products.

If you’re an operator, marketer, or founder trying to figure out how to actually use AI coding tools (instead of just tweeting about them), this one’s for you.

Guest

Jacob Klug — founder of Creme, an agency building “lovable MVPs” and full-stack products with Lovable + AI tools; helps founders, startups & enterprises ship production apps in weeks without sacrificing UX.

Guest Links

Website: https://www.creme.digital/
LinkedIn: https://www.linkedin.com/in/jacob-klug-37b254156/
X (Twitter): https://x.com/Jacobsklug

What You’ll Learn

• Why the “vibe coding is a bubble” take is mostly a skill and discipline problem
• How Jacob’s agency ships full startup-grade products using Lovable and AI
• The PRD-first formula they use before ever opening a builder
• How to decide when to build vs. when to buy software in 2025
• Why we’re entering a wave of personal OSes and custom internal tools
• How to avoid shipping janky AI UI and make your app look intentionally designed
• The mindset shift from “I could build anything” → “I will build this one specific thing”
• Why specializing in one AI tool (Lovable, Cursor, n8n, etc.) beats being “the AI guy”
• Tactical content and lead-gen plays for agencies on LinkedIn and YouTube
• How to learn AI tooling without getting paralyzed by the infinite possibilities

Timestamps

• 00:00 — Vibe coding: bubble or breakthrough?
• 02:23 — Effective use of no-code tools
• 05:23 — Stack and scoping for MVP development
• 07:08 — Trends in personal software development
• 10:33 — Personal projects: blood work analysis tool
• 13:00 — Steps to start building custom software
• 17:49 — Successful and unsuccessful product categories
• 21:01 — Learning and adopting AI tools
• 27:45 — Creator collaboration in software development
• 32:14 — Lead generation strategies for AI-powered agencies

Key Topics & Ideas

1. Bubble or Skill Issue?

• Why early no-code/AI apps looked janky
• How tools like Lovable increased automation from ~50% → ~85%
• The remaining 10–15% where real engineering still matters
• Many failures come from non-devs skipping fundamentals

2. How Creme Builds Lovable MVPs

• Every project starts with a clear PRD (often drafted with ChatGPT)
• AI is used to tighten scope before building
• When Creme stays fully in Lovable vs. moving code to Cursor
• Using Lovable Cloud for hosting, database, and analytics

3. Personal Operating Systems & Internal Tools

• People replacing SaaS subscriptions with their own custom tools
• In a 20-person cohort, nearly everyone built workflow apps
• Rise of the Personal OS: one system for life + work
• Example builds:
  • Bloodwork tracker from PDF uploads
  • Unified messaging CRM (WhatsApp, Telegram, SMS, email)
  • Automated 30-second sales briefings

4. How to Learn AI Coding Tools

• Half the cohort hadn’t built anything before starting
• Main blocker: overwhelm, not skill
• Learn core concepts: frontend vs. backend, auth, roles, security
• Build daily reps, focus on the next thing you need—not “all of AI”

5. Designing Apps That Don’t Look AI-Generated

• Good design is still the hardest and biggest edge
• Creme process: build a /components library, define buttons/cards/inputs, assign stable IDs
• Tools: Mobbin, Figma Community kits, 21st.dev
• Best prompt: “Here’s a screenshot → copy this.”

6. What Works in Product Ideas

• Most of Creme’s builds are full startup platforms, not micro-tools
• AI makes shipping easier, but ideas are getting worse without depth
• Real advantage = domain expertise + niche problem + AI speed

7. Creators x Software

• Creators can now ship products without capital
• Jacob prefers retainers over equity
• Analogy: Like creator brands—most fail, a few go huge

8. Career Strategy: Specialize

• Future = verticalized expertise, not “AI generalists”
• Specialist lanes: Lovable, Cursor, n8n, automation
• Be the person for one tool + one market

9. Content & Lead Gen

• Jacob's two rules for content: people are selfish and people are bored
• Build content that teaches, sparks emotion, and creates curiosity
• Post ~5x/week, prioritize visual posts
• Long-term: YouTube deep dives for high-intent inbound

Sponsor
Today’s episode is brought to you by Graphed – an AI data analyst & BI platform.

With Graphed you can:
Connect data like GA4, Facebook Ads, HubSpot, Google Ads, Search Console, Amplitude
Build interactive dashboards just by chatting (no Looker Studio/Tableau learning curve)
Use it as your ETL + data warehouse + BI layer in one place

Ask:
“Build me a stacked bar chart of new users vs. all users over time from GA4”
…and Graphed just builds it for you.

👉 Get a 14-day free trial with 10 seats for your team: https://graphed.com/

Think of page one as real estate—and claim as much of it as possible. Jesper Nissen breaks down modern parasite SEO: leveraging high-authority platforms (YouTube, Instagram, X/Twitter Articles, Perplexity/Qwen pages, etc.) to rank quickly for branded, local, and long-tail keywords. We cover indexing workflows, daisy-chain linking, exact-match domain plays, and the content + link velocity patterns that are working now.

Guest
Jesper Nissen — SEO educator, link-building practitioner, founder of SchemaWriter.ai and the cloud-stacking platform YACSS; speaker at POFU Live / SEO Rockstars; MSc in Physics (U. of Copenhagen). 

Guest Links
Website: https://jespernissen.com/
YouTube: https://www.youtube.com/@JesperNissenSEO
X (Twitter): https://x.com/jespernissenseo?lang=en

What You’ll Learn

• Parasite SEO, 2025 edition: Why page-one results increasingly favor social UGC, news, and authority domains—and how to ride that DA for fast wins. 
• Platforms that still rank: Jesper’s current leaderboard (e.g., Qwen, Perplexity) and what changed for Claude Artifacts.
• Local + long-tail focus: How to use Facebook/Instagram posts, YouTube videos & community posts, and X Articles to own branded and geo-keywords.
• Indexing workflow: Indexing services + social “daisy-chain” links to accelerate discovery.
• EMD plays: Exact-match domains (service+city and SaaS feature terms) and smart, steady link velocity patterns.
• Social → Search shift: Why Instagram and Facebook posts have started surfacing in Google (July 2025 change) and how to write posts to rank. 

Timestamps

• 00:00 — Owning page one like “real estate”
• 02:16 — Parasite SEO vs. traditional guest posts
• 08:45 — Reddit’s link-out limits & why Jesper moved on
• 14:58 — Claude Artifacts surge (and why it cooled)
• 18:02 — What’s working now: Quen & Perplexity pages
• 21:35 — Indexing flow: drip pings + social link bursts
• 26:40 — Meta shift: FB/IG posts in Google (local SEO gold) 
• 31:55 — Exact-match domains + link velocity math
• 46:55 — Shorts as TOF magnets; long-form as sales letter
• 51:40 — Priming YouTube with low-CPC X ads (global)

Jesper’s Parasite SEO Playbook (Step-by-Step)

1. Pick a target query (branded, local, or long-tail).
2. Publish across high-DA surfaces:
   • YouTube (video + Community post), X/Twitter (Articles), Instagram, Facebook Page, plus AI page builders (e.g., Quen, Perplexity).
3. Front-load keywords in social posts (especially the first words of FB/IG captions for cleaner URLs/titles).
4. Daisy-chain internal links: point your X Article to the IG/FB/YouTube/AI pages to aid indexing.
5. Kick indexing via reputable ping/index services, then add lightweight social links to nudge crawl.
6. Measure and iterate: keep winners, replace laggards, expand with adjacent long tails.

Exact-Match Domain (EMD) Mini-Framework

• When to use: service+city rank-and-rent, or narrowly defined SaaS use-cases.
• Build: one-page lander, fast crawl path, 5–10 quality links/month early, layer socials & citations; avoid unnatural velocity spikes.
• Why it works: high topical alignment + clean intent matching.
  (Jesper’s background in cloud stacking/YACSS and SchemaWriter.ai complements this with structured data & internal “powerstack” patterns.) 

Sponsor

This episode is brought to you by Graphed — the AI-native analytics platform that builds dashboards from plain English. Connect GA4, ads, CRM, GSC, and Sheets to get KPI boards in minutes. Learn more: https://graphed.com/

Billboards at $0.75 CPM. Streaming TV you can actually measure. Tim Rowe breaks down how to blend OOH + CTV to drop blended CAC, spark geo-lift, and build “living-room” brand equity—without massive budgets.

Streaming has turned TV into a performance channel you can buy, cap, and measure like digital—often at CPMs rivaling or beating social. Tim explains how their ad server + pixel connect living-room exposure to down-funnel actions, with many brands seeing $3–$4 cost per visit and 3–4× higher conversion vs other traffic sources. On OOH, the overlooked arbitrage is static or digital boards priced like real estate: win by buying the biggest formats in the largest markets at the lowest biddable entry price, then engineer earned media (social virality) and geo-lift. Start with ~$5k for a real CTV test (smaller tests can still work as an add-on), measure blended CAC, branded search, and market-level lift, and let creative—not hyper-granular targeting—do the heavy lifting.

Guest

• Website: https://cognitionads.com/
• LinkedIn: https://www.linkedin.com/in/troweactual
• X (Twitter): https://x.com/oohinsider
• Tim’s newsletter/resource hub: https://stateofstreaming.com/

What You’ll Learn

• Why streaming made TV relevant again—and cheap ($1–$2 CPMs in some geos).
• How to attribute TV exposure → search → site visit → purchase within a 48-hour view-through window.
• The out-of-home (OOH) arbitrage: buying big signs in big markets for sub-$1 CPMs.
• How OOH + CTV lower blended CAC and lift branded search in target geographies.
• Practical first tests: budgets, pixels, frequency caps, creative, and geo measurement.
• Event playbooks: digital billboard trucks, rideshare screens, street teams, and QR flows.
• Targeting reality: on CTV, less targeting often wins—use creative as the filter.
• Retargeting on TV (yes): pixel site traffic and follow with CTV/audio/display.

Timestamps & Chapters

• 00:00 — Why TV is “back”: streaming CPMs and geo-targeted buys
• 01:30 — Direct attribution: 48-hour view-through from TV → search → site → purchase
• 03:45 — OOH primer: static vs digital, programmatic buys, and PMP tips
• 06:05 — The arbitrage: big boards, big markets, tiny CPMs (often <$1)
• 09:15 — Measuring lift: branded search, Search Console, geo-heatmaps, blended CAC
• 12:10 — Earned media by design: turning boards into social fuel
• 15:20 — Event playbook: mobile LED trucks, rideshare TV, coffee-cart sponsorships
• 18:05 — CTV mechanics: ad server + pixel, frequency caps, “hands on keyboard” setup
• 21:10 — Budgeting your first test (~$5k) and what “good” looks like
• 23:00 — Targeting truth: broad wins; use creative, use your 1P data for segments/lookalikes
• 26:10 — Retargeting on TV and building a full streaming funnel
• 28:00 — Who this works best for (DTC, local services, ABM/SaaS, events)
• 30:00 — Getting started and where to reach Tim

Playbooks & How-Tos

1) Fast OOH Test (2–4 weeks)

• Pick 1–2 large markets your sales team targets.
• Buy largest formats you can afford (static or digital) at the lowest CPM; test via https://www.blipbillboards.com/
  (entry-level) or via PMPs/direct with operators.
• Creative: one bold claim + large logo + simple URL/QR. Design for 0–3 second read.
• Measure: branded search & direct/organic sessions from those geos; compare pre/post.

2) Streaming TV (CTV) Starter

• Pixel your site (for attribution + retargeting).
• Launch a broad geo campaign; cap frequency; rotate 1–2 :15–:30 creatives.
• Budget: aim for $5k to reach statistical signal; smaller ($1.5–$2k) still useful as a display-like add-on.
• KPI: cost per visit ($3–$4 is common in Tim’s data), conversion rate lift vs other traffic, branded search lift, blended CAC shift.

3) Event Swarm Tactics

• Digital billboard truck looping near venue entrances all day.
• Rideshare TV for the event radius; add a QR to capture emails or drive an offer.
• Street team + product samples or demo cards; sponsor a coffee cart beside the venue.

Key Takeaways (Skimmable)

• CPMs: OOH can hit ~$0.75; CTV often $1–$2 in the right geos.
• Attribution: Use a 48-hour view-through window from TV exposure to on-site actions.
• Blended CAC: Expect downstream CAC reductions across channels from brand lift.
• Targeting: On CTV, broader = cheaper CPMs and often better performance; let creative and 1P audiences do the work.
• Budget: $5k is a solid first test; smaller tests still demonstrate directionality.
• Creative: Be bold; engineer shareable moments to multiply paid with earned.

Links & Resources Mentioned

• Cognition Ads (Tim’s company): https://cognitionads.com/

• State of Streaming (news & insights): https://stateofstreaming.com/

• Blip (entry-level digital billboards): https://www.blipbillboards.com/

• The Trade Desk: https://www.thetradedesk.com/

• DV360: https://marketingplatform.google.com/about/display-video-360/

• Google Search Console (measure geo-lift): https://search.google.com/search-console/about

Sponsor

This episode is brought to you by Graphed — an AI-native analytics platform that builds dashboards from plain English. Connect GA4, ads, CRM and get KPI boards in minutes. Learn more: https://graphed.com/

Founders are ditching pure outbound for “community → product” funnels. Jacky Chou (Indexsy) breaks down a modern SaaS GTM: build audience, educate in a community, sell the tool that powers the play. We go deep on local SEO (map pack), YouTube as the highest-intent acquisition channel, Reddit/parasite SEO mechanics, and how LocalRank grows by educating & productizing services.

Guest

Jacky Chou — Indexsy
Website: https://jackychou.com/
YouTube: https://www.youtube.com/@indexsy
X (Twitter): https://x.com/indexsy

Brought to you by

Graphed — AI data analytics you can chat with. Connect your data, build live dashboards in minutes: https://graphed.com

What You’ll Learn

• The community-led SaaS funnel (audience → community → teach → tool)
• Local SEO 80/20: reviews, citations (NAP consistency), and CTR signals
• Why YouTube drives the most buyer-ready traffic for niche software
• Parasite SEO & Reddit tactics to earn visibility and brand mentions
• How “education first” communities expand TAM and reduce CAC
• Cold outreach that feeds branded search and category creation

Chapters

00:00 Intro — Why the SaaS funnel is shifting to community-led
 01:45 Local SEO 101: map pack vs. organic results
 03:40 The 80/20: reviews, citations/NAP, CTR signals
 06:10 Tactics for generating reviews & citations (pros/cons, risks)
 09:55 Indexing citations faster; NAP consistency checklist
 12:40 Community-led growth & seeding new agencies on LocalRank
 15:05 Why local SEO is “stupid easy” right now (and where it’s competitive)
 17:30 Prospecting & pricing: pick high-CPC verticals, value-based fees
 20:15 Packaging offers: guarantees, radius games, productized services
 22:40 The funnel behind LocalRank Academy → software upsell
 25:20 Paid vs. organic: X threads, remarketing, long email drips
 27:15 Launch data: YouTube > X for paid conversions at launch
 29:10 Reddit distribution, parasite SEO, and gaming brand mentions
 32:20 Cold email that drives site visits (naked domains, link timing)
 35:05 Manufacturing branded search & CTR spikes (digital PR ideas)
 38:10 AI Search (AISCO): what (might) influence LLM surfaces today
 43:05 Building moats: being the practitioner, faster iteration loops
 46:10 Experiments, ethics & sustainability of “gray-hat” tactics
 49:10 Where to find Jackie & final CTAs

Key Takeaways

• Community beats cold: educate first, then sell the tool that powers the play.
• Map pack wins local: Reviews + consistent NAP citations + real-world engagement drive outsized results.
• YouTube converts: Long-form demos/education create buyer-ready traffic for niche SaaS.
• Branded search compounds: Cold email, content, PR, and job posts can stimulate searches for your name/category.
• TAM expansion via education: A paid community can breakeven ad spend and prime higher-ticket software deals.

Today we break down why “influencer marketing” (renting audience) is losing to creator-based marketing (renting skill at making viral content) — and how to run it like a system. Guest Robert Lukoszko, founder of Stormy AI, shows how their agent finds creators, pulls contacts, sends DMs/emails, follows up, and even negotiates packages before you step in. We get tactical on budgets, pricing, UGC hiring, TikTok vs YouTube strategy, measurement, and building a compounding “surface-area” of content across the web.

Brought to you by Graphed.com — connect your data, ask in plain English, ship shareable dashboards.

Guest

• Website: stormy.ai 
• Robert Lukoszko — LinkedIn: linkedin.com/in/karmedge 
• X (Twitter): @Karmedge 

What you’ll learn

• Creator vs Influencer marketing: Why FYP-driven platforms reward great content over big followings — and how to “rent” creators’ skill instead of their audience.
• The scalable workflow: Brief → research → outreach (DM/email) → qualify → negotiate packages → handoff to human for final approval.
• TikTok UGC machine: Hire 1–3 full-time UGC creators posting 2–3 shorts per day; test cheaply, then double down on breakout templates.
• YouTube packages that work: Three-video bundles over ~6 weeks build trust & lift; use retainers for your top performers.
• Negotiation scripts that convert: Lead with “Paid collaboration” in subject/first line, anchor on value, and offer volume/retainer discounts.
• Pricing reality check: Typical UGC test pieces land in the ~$20–$100/video range (many sweet-spot wins at $20–$50) for micro/nano creators; salaried UGC in EU markets often $1–2k/mo part-time depending on output and quality.
• Compounding effects: Viral videos spawn follower videos; repeated sightings increase creator reply-rates and lower CPAs.
• Agents as team members: Why modern stacks look like small pods of engineers orchestrating many narrow agents (research, outreach, follow-ups, CRM status, stop-conditions).

Chapters & Timestamps

• 00:00:00 — Cold open: “Stop influencer marketing. Start creator marketing.”
• 00:01:17 — Sponsor: Graph.com (AI dashboards from plain English)
• 00:02:26 — Guest intro: Robert (Founder, Stormy AI) + why YouTube/TikTok matter
• 00:03:49 — The pain of manual outreach and why Stormy exists
• 00:05:55 — How Stormy’s research agent finds/qualifies creators (views, recency, fit)
• 00:08:15 — TikTok/UGC playbook: daily shorts, test → double down
• 00:10:04 — It’s a numbers game: post volume & breakout templates
• 00:12:00 — “Surface area” strategy: AI pulls from the open web; brand search as moat
• 00:15:03 — Validating features with viral demos before shipping
• 00:17:02 — Building in public: rapid iteration with creator feedback
• 00:18:00 — Outreach mechanics: DMs, scraping bios/Linktree, multi-source emails
• 00:20:06 — Copy that converts: lead with “Paid collaboration” + template tips
• 00:21:46 — Scale metrics: ~200 messages/day across rotated inboxes; reply-rate ranges
• 00:23:29 — Brand effects: recognition boosts replies; upfront vs affiliate by stage
• 00:26:01 — Compounding virality: trend templates, creator social proof
• 00:29:03 — Pricing: $20–$100 UGC tests; sweet spot $20–$50; EU part-time $1–2k/mo
• 00:29:53 — Agentic negotiations: packages, volume, follow-ups, human handoff
• 00:31:04 — Guardrails: budget anchoring, stop-conditions, funny “PayPal link” story
• 00:35:05 — Toolbelt of agents: research, outreach, CRM updates, payments, bulk sends
• 00:36:01 — Architecture: many narrow agents > one monolith
• 00:37:51 — Future: fewer humans in the loop; AI influencers; approvals as human role
• 00:39:16 — Can businesses run themselves? Media = growth flywheel
• 00:41:11 — Hiring philosophy: engineer-heavy teams (Gary Tan advice)
• 00:43:46 — Wrap + where to find Robert & Stormy

Playbooks & templates (steal these)

Outreach subject lines (email/DM first line):

• “Paid collaboration: {Brand} x {CreatorName} — 3-video package”
• “Paid promo + affiliate: {Brand} (fast approvals, simple brief)”

First message (short DM/email):
“Hey {Name} — we’re {Brand}, a {1-line what you do}. Paid collaboration: 1 test short this week (${offer}) + option to extend to 3-video bundle over 6 weeks. You keep creative control; we provide brief + examples. Interested? If yes, quick details + rate card?”

Negotiation levers: volume (3-pack → 6-pack), multi-month cadence (1/mo), affiliate top-ups on performance, first-video discount, creative templates proven to hit.

UGC hiring filter: Look for micro/nano creators (10k–50k) with at least one breakout (e.g., 500k+ views) in your niche; they have the “spark” but are still rationally priced. (Stormy highlights this pattern in search/fit scoring.) 

Key quotes (pull-ready)

• “Creator marketing rents skill at making viral content — not just an audience.”
• “It’s a numbers game twice: mass outreach, then mass posting — let the winners emerge.”
• “Lead with ‘Paid collaboration’ so creators instantly know there’s budget.”
• “Templates win. When a format pops, clone it and scale with more creators.”

Sponsor

Graphed.com — Connect your SaaS/GA4/Shopify/data warehouse → ask in plain English → get dashboards & ad-hoc analysis; share with clients or your team in one click. (Free 10-seat trial for listeners — link in description.)

AI “agents” have been hyped to death—but very few are truly delivering real-world impact. In this episode, we cut through the vaporware with Christian Wiens, co-founder of Loman, an AI voice agent platform transforming how restaurants handle customer calls, orders, and reservations. Christian shares how Loman went from a two-person idea to serving hundreds of restaurants and hitting $1.5M ARR in record time. We dive into why voice is the most natural, context-rich way for humans to communicate—and how AI agents that do real work (not just answer questions) will change how we interact with businesses forever. You’ll hear how Loman’s restaurant agents integrate directly with POS systems to take orders end-to-end, the surprising reasons Gen Z prefers talking to AI over humans, and why the future of a brand’s “front door” may be an AI personality instead of a website. Christian also breaks down Loman’s explosive growth playbook—from ditching cold email for native social ads, to filming on-location customer stories that convert like crazy. We cover the realities of AI-generated ads, programmatic SEO, and why outcome-driven automation is the only AI worth paying for.

What You’ll Learn in This Episode

• What really defines an AI agent—and why most products don’t qualify
• How voice-based AI can capture richer customer context than any app or form
• The operational pain restaurants face with missed calls and how AI solves it
• Why customers don’t care if it’s AI or human—only that it gets the job done
• Gen Z’s surprising comfort with AI calls (and discomfort with human ones)
• The two make-or-break factors every AI agent needs to succeed
• How to create “native feel” ad creatives that crush on social
• Why hyper-specific vertical integration beats horizontal AI every time
• The massive untapped potential for outbound AI voice (and the legal gray areas)
• Christian’s vision for a future where AI agents replace websites as the primary customer touchpoint

Chapters

00:00 – Intro & The AI Agent Hype vs. Reality
 04:18 – What an AI Agent Really Is
09:02 – Why Voice Is the Ultimate Interface
13:47 – The Restaurant Industry’s Missed Call Problem
18:25 – Gen Z’s Comfort with AI Calls
22:58 – Vertical vs. Horizontal AI Strategies
27:41 – Loman’s Explosive Growth Playbook
32:16 – Ads That Feel Native & Convert
37:08 – Outbound AI Voice & Legal Considerations
42:55 – The Future: AI Agents as the New Websites
47:20 – Closing Thoughts & How to Connect with Christian

Connect with Christian Wiens:

• LinkedIn – https://www.linkedin.com/in/christianwiens/
• Website – https://www.loman.ai/

If your LinkedIn feed looks like a museum of giant n8n screenshots and “comment to get the guide” posts…good. That means the playbook works—when you do it right. Paolo breaks down the exact framework his agency uses to turn LinkedIn into a repeatable inbound lead engine for B2B—especially SaaS, agencies, and info businesses.

What You’ll Learn

• Lead magnet mechanics that still crush: how to pick the right asset (templates vs. guides), formats that perform (Notion docs, Miro boards, short scroll videos), and the “perceived value + curiosity + scarcity” combo.
• Hooks that make people click “See more”: trigger desire, fear, or curiosity in the first 3 lines.
• Pattern interrupts that boost reach: why oversized workflows, zoom-ins, and 10-second sped-up videos spike hover time and help the algo.
• Profile-as-landing-page: how to structure your headline, Featured section, and CTAs to funnel traffic without tanking post reach.
• Nurture after the comment: DM prompts that qualify intent, when to drop case studies, and how to avoid low-intent “free audit” traps.
• Where this shines: B2B SaaS, agencies, consultants/coaches—audiences that are active on LinkedIn and buy from content.

Paolo’s Playbook (Step-by-Step)

1. Pick the problem (one ICP pain your offer solves).
2. Choose the asset format based on buyer type:
   • Done-for-you buyers → plug-and-play templates.
   • Education/info buyers → guides/videos.
3. Design the preview media to signal value and create curiosity:
   • Notion table of contents screenshot, massive Miro flow, or a 10-sec scroll video.
4. Write the post like this:
   • 3-line hook (desire/fear/curiosity).
   • Promise + what’s inside.
   • CTA to comment (optionally “repost for priority”).
   • Light scarcity (e.g., 48-hour window).
5. Delivery & DMs:
   • Send the asset, ask an easy reply (“Are you posting on LinkedIn yet?”).
   • Qualify with 1–2 follow-ups, then make a clear offer with outcomes + timeline (+ guarantee if you have one).
6. Nurture cadence (next 2–3 days):
   • Day 1: Case study (story format: before → intervention → after; CTA to book).
   • Day 2: Technical value post (lower engagement is fine; it nurtures).
   • Add strongest case studies to Featured on your profile.
7. Links without nuking reach:
   • Push to profile/Featured or drop links in comments; edit the post later to add the link after it’s cooked.

Tactical Nuggets

• Comments > Likes (weightier signal + more hover time).
• Avoid bot pods; if you coordinate engagement, keep it real accounts and relationships.
• For SaaS without a free trial, push to a free setup/usage guide that inherently requires the product.
• Use storytelling in case studies; people remember transformations, not dashboards.
• If you’re running volume lead magnets, expect lower engagement on deep-dive posts—that’s normal and still effective.

Tools & Formats Mentioned

• Notion (TOC screenshot as lead magnet preview)
• Miro (big workflow screenshots)
• n8n (automation diagrams that stop the scroll)
• Short scroll videos (10–15s, autoplay pattern interrupt)
• AI voice agent (optional MOFU experiment to educate and qualify at scale before handing off to a human)

Who This Works Best For

• B2B SaaS (often top performer)
• Agencies
• Consultants/Coaches
• Any ICP that’s active on LinkedIn and buys based on content/authority

Sponsor

Talent Fiber — Hire world-class global talent (engineers with 7+ years’ experience, U.S. time zones, excellent English) at ~⅓ U.S. cost. They’re an outsourced HR partner, handling compliance, payroll, and employee happiness—with a free replacement if it doesn’t work out. Learn more: talentfiber.com

Connect with Paolo

• LinkedIn: https://www.linkedin.com/in/leadgenwiz/

AI-driven search (AISEO) is opening a new lane for brands in competitive categories. Joe Davies from FATJOE explains why branded mentions (not just links) are increasingly what LLMs use to decide recommendations—and how teams can systematically earn those mentions. We cover tactics like guest blogging at scale, context-seeding your USP across reviews/listicles, building deep product docs to feed LLMs, and using tier-two links to get your “influencer pages” ranking. Early data shows 2–3× higher conversion rates from AI-referred traffic because buyers arrive pre-educated and ready to act.

What You’ll Learn

• Why AISEO rewards brand mentions and clear USPs more than classic link metrics.
• How AI-referred traffic converts 2–3× higher than traditional search.
• A repeatable process to seed your brand in listicles, reviews, and comparisons.
• How to “context-seed” your USP so LLMs recommend you for the right reason.
• Why deep help docs / knowledge bases make LLMs more confident recommending you.
• How to choose targets (DR + real traffic), then lift them with tier-two links.
• The state of AISEO observability (what to track, what’s still immature).

Tactical Playbook (Step-by-Step)

1. Define your USP: the specific “best for ___” angle you want LLMs to repeat.
2. Keyword map long-tail, bottom-funnel queries (e.g., “best X for Y,” “X vs Y,” “X alternatives,” “[product] review”).
3. Prospect targets with credible traffic (DR is fine as a filter, but prioritize verified organic traffic).
4. Commission content: secure guest posts/listicles and full reviews on those sites. Mix formats to look natural.
5. Context-seed your USP in every placement (e.g., “Best for small teams,” “Most features,” “Best value”).
6. Include competitors in listicles/reviews so the page is useful (LLMs prefer balanced sources).
7. Boost with tier-two links (niche edits, syndication) to help these pages rank on pages 1–3.
8. Expand surface area: Reddit answers, YouTube/tutorial mentions, and social chatter to reinforce brand salience.
9. On-site foundation: build exhaustive docs—features, integrations, FAQs, facts sections—so LLMs can learn you deeply.
10. Measure pragmatically: track referral traffic from AI surfaces and downstream conversions; current “AI visibility” tools are early.

Resources & Mentions

• ChatGPT Path (shows the searches/sources ChatGPT runs under the hood):
  https://chromewebstore.google.com/detail/chatgpt-path/kiopibcjdnlpamdcdcnphaajccobkban
• FATJOE — Brand Mentions Service: http://fatjoe.com/brand-mentions
• FATJOE: https://fatjoe.com/

Key Takeaways

• AISEO is early but growing fast and already drives higher-intent traffic.
• Focus on being mentioned credibly across the open web; LLMs synthesize those signals.
• Listicles + reviews on high-trust, real-traffic sites are the current highest-leverage assets.
• Your docs are marketing now—LLMs read them and recommend accordingly.
• Don’t abandon SEO; it remains the foundation that AI systems lean on.

Chapters

• 00:00 Cold open: AISEO’s opportunity & why mentions matter
• 03:45 Data: AI referrals converting 2–3× vs. classic SEO
• 07:50 Who should prioritize AISEO (and who can wait)
• 10:30 Tactics: listicles, reviews, and “context-seeding” your USP
• 15:45 Tools & workflows; extension that reveals ChatGPT’s queries
• 19:45 Content ops: human vs. AI writing, plans, and clustering
• 22:30 Build deep product docs to feed LLM understanding
• 26:10 Ranking the influencer pages + tier-two links
• 33:00 Observability today: what’s useful, what isn’t yet
• 36:50 The next 5–10 years: AI + SEO, not AI vs. SEO

Guest

Joe Davies

• X: https://x.com/fatjoedavies
• LinkedIn: https://es.linkedin.com/in/joe-davies-seo
• Website: https://fatjoe.com/

This AI SEO deep‑dive gets tactical. I sit down with Ilias Ismanalijev (aka @illyism) to map the real discovery journey happening inside AI search—what users actually prompt from problem‑aware to buyer‑ready—and how to influence results across models (GPT, O3, Claude, Perplexity). You’ll learn how to surface the right phrases (not just keywords), make your pages AI‑readable, and win off‑page placements on the listicles and directories LLMs love to cite.

What you’ll learn

• The 4 levels of AI search (no‑search → deep research) and how strategy changes at each.
• Prompt‑level intent mapping: info, comparison, executive/delegation, problem‑solving.
• How to spot AI‑generated queries in Google Search Console and build your tracking sheet.
• On‑page for LLMs: crawlability, structured content/markdown, alt text, and avoiding blockers (robots.txt, Next.js assets).
• Off‑page that moves rankings: listicle outreach, affiliate offers, directories (G2, Product Hunt), and Reddit/“parasite” opportunities.
• Why AI traffic is often more buyer‑ready—and how to target bottom‑of‑funnel prompts (e.g., “X vs Y,” “best X for Y,” pricing specifics).

Chapters
0:00 Cold Open — What You’ll Learn
1:22 Sponsor: TalentFiber
2:25 Meet Ilias & Why AI SEO Now
3:02 Who Benefits Beyond SaaS?
4:58 Research vs. E‑com Use Cases
6:20 Comparison‑Style Prompts IRL
8:59 Brands Doing It Well (Examples)
10:46 Why AI Traffic Is Buyer‑Ready
13:42 Benchmarking AI Search Visibility
16:38 Frameworks for AI Keyword Research
20:58 On‑Page for LLMs (Crawlability)
23:30 Finding AI Queries in Search Console
27:30 Regex + Long‑Query Filters
28:25 The 4 Levels of AI Search
32:17 Bottom‑of‑Funnel Prompts That Convert
34:06 Off‑Page: Listicles, Affiliates, Outreach
37:00 Reddit/Parasite SEO & Page One Sources
38:59 Mapping Sources w/ LinkDR
41:02 Pricing Pages & AI Page Inspector
44:34 Directories, Reviews & Digital PR
47:41 Should You Create AI‑Optimized Resource Pages?
48:38 Wrap‑Up & Where to Find Ilias

Guest
Ilias Ismanalijev
X: https://x.com/illyism
LinkedIn: https://www.linkedin.com/in/illyism
Site: https://il.ly/

Host
Cody Schneider
X: https://twitter.com/codyschneiderxx
LinkedIn: https://www.linkedin.com/in/codyxschneider
Instagram: https://www.instagram.com/codyschneiderx
YouTube: https://www.youtube.com/@codyschneiderx

Sponsor
This episode is brought to you by TalentFiber — hiring top offshore software engineers as an extension of your team (technical interviews, compliance, replacements, fast turnarounds). Learn more at talentfiber.com

Unlock the practical side of vibe coding and AI‑powered marketing automations with host Cody Schneider and guest CJ Zafir (CodeGuide.dev). If you’ve been flooded with posts about no‑code app builders but still wonder how people actually ship working products (and use them to drive revenue), this conversation is your blueprint.

CJ breaks down:

• What “vibe coding” really means – from sophisticated AI‑assisted development in Cursor or Windsurf to chilled browser‑based tools like Replit, Bolt, V0, and Lovable.
• How to think like an AI‑native builder – using ChatGPT voice, Grok, and Perplexity to research, brainstorm, and up‑level your technical vocabulary.
• Writing a rock‑solid PRD that keeps LLMs from hallucinating and speeds up delivery.
• The best tool stack for different stages – quick MVPs, polished UIs, full‑stack production apps, and self‑hosted automations with N8N.
• Real‑world marketing automations – auto‑generating viral social content, indexing SEO pages, and replacing repetitive “social‑media‑manager” tasks.
• Idea‑validation playbook – from domain search to Google Trends, plus why you should build the “obvious” products competitors already prove people pay for.

You’ll leave with concrete tactics for:

1. Scoping and documenting an app idea in minutes.
2. Choosing the right AI coding tool for your skill level.
3. Automating content‑creation and distribution loops.
4. Turning small internal scripts into sellable SaaS.

Timestamps

(00:00) - Why vibe coding & AI‑marketing are everywhere  
(00:32) - Meet CJ Zafir & the origin of CodeGuide.dev  
(01:15) - Classic mistakes non‑technical builders make  
(01:27) - Sponsor break – Talent Fiber  
(03:00) - “Sophisticated” vs “chilled” vibe coding explained  
(04:00) - 2024: English becomes the biggest coding language  
(06:10) - Becoming AI‑native with ChatGPT voice, Grok & Perplexity  
(10:30) - How CodeGuide.dev was born from a 37‑prompt automation  
(14:00) - Tight PRDs: the antidote to LLM hallucinations  
(18:00) - Tool ratings: Cursor, Windsurf, Replit, Bolt, V0 & Lovable  
(23:30) - Real‑world marketing automations & agent workflows  
(25:50) - Why the “social‑media manager” role may disappear  
(28:00) - N8N, JSON & self‑hosting options (Render, Cloudflare, etc.)  
(35:50) - Idea‑validation playbook: domains, trends & data‑backed bets  
(42:20) - Final advice: build for today’s pain, not tomorrow’s hype 

Sponsor

This episode is brought to you by Talent Fiber – your outsourced HR partner for sourcing and retaining top offshore developers. Skip the endless interviews and hire pre‑vetted engineers with benefits, progress tracking, and culture support baked in. Visit TalentFiber.com to scale your dev team today.

Connect with Our Guest

• X (Twitter): https://x.com/cjzafir
• CodeGuide.dev: https://www.codeguide.dev/

Connect with Your Host

• X (Twitter): https://twitter.com/codyschneiderxx
• LinkedIn: https://www.linkedin.com/in/codyxschneider
• Instagram: https://www.instagram.com/codyschneiderx
• YouTube: https://www.youtube.com/@codyschneiderx

Join me as I chat with Yoann Pavy, the growth mastermind behind AI Apply and ex-Deliveroo & Depop head of growth.

Timeline
 00:00 – AI tooling’s golden age (and why it’s overwhelming)
 00:31 – Introducing Yo, the “most gangster” consumer marketer I know
 00:45 – What you’ll learn: short‑form content, paid ads, automations
 01:23 – Sponsor: Talent Fiber makes offshore hiring effortless
 02:12 – Yo’s creative AI spotlight: VO3 videos & gorilla vlogs
 04:46 – Humans vs. AI avatars in paid videos (spoiler: humans still shine)
 07:20 – Building your creator pyramid with Sideshift & Shortimize
 10:00 – Automating code changes via “Jarvis” in Slack
 14:38 – Scaling organic content: thousands of posts, not dozens
 18:00 – Product‑channel fit: build the media first, product second
 20:30 – Automating international growth: 20+ languages in weeks
 24:00 – Filtering AI noise: focus on what’s already working
 27:15 – The biggest gap: corporate brands vs. startup agility

Key Points
 • AI creatives are exploding—VO3 videos hit millions of likes fast.
 • Human spontaneity still outperforms AI‑only videos—for now.
 • Slack‑based AI agents (“Jarvis”) deploy code, update copy, spin up PRs.
 • Automate localization: add new languages weekly without human translators.
 • Scale organic distribution by multiplying creators and formats.
 • Product‑first mindset flips: media channel drives features.
 • Startups win by sprinting on AI while corporates stall in red tape.

Deep‑Dive Sections

1. Creative AI in Paid Ads
    Verdict: 🔥 Underrated
    • VO3‑generated TikTok vlogs racked up 4M likes in days
    • AI statics (before‑after sliders) crank out ad assets at scale
    • Humans still lead on nuance—mix both and test relentlessly
2. Automations & Internal AI Agent
    Verdict: 🚀 Game‑changer
    • “Jarvis” in Slack handles code tweaks, pull requests, image swaps
    • One‑line commands push new footer tabs and copy revisions
    • Frees marketers to iterate strategy, not deployments
3. Scaling Organic Content
    Verdict: 💡 Must‑do
    • Move from 10 posts/month to 1,000+ by cloning formats across creators
    • Use Shortimize to track views cooking days after publish
    • Volume on TikTok & LinkedIn is the new SEO—play the numbers game
4. Product‑Channel Fit Mindset
    Verdict: 🔄 Reversed logic
    • Prototype media hooks (e.g. resume‑kit demos) before building features
    • Validate with viral tests—first video hit 700K views in 24h
    • Bake winning social formats into product roadmap
5. Future of AI‑Powered Growth
    Verdict: ⏳ On the horizon
    • Multi‑agent customer personas could replace focus groups
    • Meta’s AI for one‑to‑one ad creatives will upend engagement
    • Corporates risk being left behind as startups sprint

Notable Quotes
 “It’s never existed like it has now. But it’s extremely overwhelming.”
 —HOST

“I call it Jarvis because it’s sexy—I just ask Slack to add a tab and it’s done.”
 —Yoann Pavy

“Once you have two or three of these formats, you can go viral any given day.”
 —Yoann Pavy

Sponsor Block
 This episode is brought to you by Talent Fiber. Hire offshore full‑stack devs with 7+ years’ experience, US‑time‑zone availability, perfect English, and a solid replacement guarantee. Learn more at talentfiber.com or click the link below.

FIND ME ON SOCIAL
LinkedIn: linkedin.com/in/codyxschneider
X: x.com/codyschneiderxx

FIND Yoann PAVY ON SOCIAL
 LinkedIn: linkedin.com/in/yoannpavy
 X: x.com/yoannpavy
 Website: aiapply.co

In this episode, Adam Silverman — co-founder & CEO of Agent Ops — dives deep into what “AI agents” actually are, why observability matters, and the very real marketing & growth automations companies are shipping today. From social-listening bots that draft Reddit replies to multi-agent pipelines that rebalance seven-figure ad budgets in real time, Adam lays out a practical playbook for founders, heads of growth, and non-technical operators who want to move from hype to hands-on results.

Guest socials
• LinkedIn: https://www.linkedin.com/in/adamsil
• 𝕏 / Twitter: https://x.com/AtomSilverman
• Company: https://agentops.ai

Timestamps

00:00 — Defining “agents”: reasoning-powered automations, not AGI
00:54 — Introducing Adam & the 50+ internal agents his team uses daily
03:32 — “Vibe marketing” and why every employee will soon have an AI assistant
05:18 — Live example: an inbound-lead-scoring agent that books calls automatically
08:11 — Metric shift: revenue / agent & revenue / token
10:45 — Three-point filter for agent ROI: expensive, repeatable, low-risk tasks
12:56 — Social-listening agents for Reddit, X & forums (human-in-the-loop posting)
16:14 — OrcaBase + TripleWhale: agentic ad-spend rebalancing for e-com
21:29 — WhisperFlow → Claude to generate entire email sequences in minutes
25:04 — Multi-agent systems & OpenAI Agents SDK (Crew AI, Llama-Index, etc.)
40:12 — Tech stack cheat-sheet: AgentQL, BrowserBase, Composio, Anthropic Claude 3, Gemini 1.5 Pro
48:07 — Internal hackathons & “minimum viable post” culture for continuous learning

Key Points

• Observability is table-stakes. Enterprises won’t deploy agents without 99.99 % reliability, so logging, evals & debugging are critical.
• Marketing automations that already work:
– Social-listening + auto-response (Reddit, X “Radar”)
– Lead-scoring & routing directly inside Superhuman
– Real-time ad-budget re-allocation with TripleWhale’s OrcaBase agents
– UGC ad generation at ¢-scale via HeyGen API
• Tooling matters: mix-and-match lower-cost LLMs (Gemini/Claude) for chain-of-thought tasks and premium models (GPT-4o) for reasoning or code.
• Multi-agent ≠ many prompts. Think specialized “teammates” passing JSON, each with its own LLM, tools & memory.
• Hire for AI-nativity, not job titles. A VA fluent in Cursor or WhisperFlow can 10× output overnight.
• Run micro-hackathons. One day a month of structured tinkering keeps teams ahead of vendor fluff.

Six Practical Plays You Can Steal

1. Expensive + Repeatable + Low-Risk Audit
   Map every workflow; circle anything that costs $$$, repeats weekly, and won’t tank the business if it fails. Start there.

2. Social-Listening Agent
   Radar (X) or manual Boolean search → Agent drafts replies → human approval → schedule via Buffer/Zapier.

3. Ad-Spend Rebalancer
   Pipe TripleWhale or GA4 ROAS data into an agent that shifts budget between Meta, Google & TikTok every 60 min.

4. Outbound “Industry Brief” Generator
   you.com’s Ari agent → 5-page PDF tailored to the prospect’s vertical → attach in first-touch email.

5. Auto-Follow-Up Composer
   Fathom meeting transcript + Superhuman “Ask AI” → ready-to-send recap with action items.

6. Internal Hackathon Framework
   • 15 min YouTube tutorial
   • 45 min build using Gumloop / Lutra AI (no-code)
   • Demo & share Loom — highest-impact sprint gets pushed to prod.

Notable Quotes

“We’ve got more agent headcount than human headcount.” — Adam Silverman
“Stop talking AGI. Look for tasks that are expensive, repeatable, and low-risk — that’s where agents print money.”
“Your revenue per employee metric just became revenue per token.”
“Build once, sell twice: every podcast, video or doc should spawn emails, tweets and a downloadable PDF.”

2025 Takeaway: The winners won’t be the teams with the biggest models; they’ll be the teams that turn everyday processes into measurable, observable agent workflows — and iterate on them faster than their competitors can finish a slide deck.

In this episode, Sandra Dajic, Head of Marketing at Chatbase, dives deep into the world of "vibe marketing"—a movement at the intersection of growth, automation, and AI tooling. She shares how she’s building AI-powered workflows to supercharge her marketing efforts, from automated ad competitor dashboards to visual content generation using GPT-4. With a background in both VC-backed and bootstrapped startups, Sandra outlines practical strategies for creating a marketing engine that feels like a team of 100—run by just one person.

Timestamps:
00:00 - Introduction: The 100x marketer and automation trend
01:40 - Sandra's AI-powered marketing workflows
04:45 - Automating ad analysis with Lovable, Make.com, and GPT
09:12 - Why “vibe marketing” matters now
13:20 - How to scale marketing without engineering resources
16:45 - Building "AI Ninja": Sandra's personalized marketing agent
21:05 - Using AI to streamline press, partnerships, and outreach
27:50 - How Sandra accelerated visual design workflows using GPT-4
31:00 - The power of personal brand and founder-driven marketing
34:15 - Sandra’s experiments with LinkedIn growth strategies
39:22 - Automating content and measuring marketing effectiveness

Key Points:

• Vibe marketing = combining growth strategy with AI automation
• Sandra built a custom dashboard to track and analyze ad creatives across platforms
• Tools used: Lovable for browser agents, Make.com for workflows, GPT-4 for automation
• AI agents streamline repetitive marketing tasks: outreach, content, visuals, competitor tracking
• Emphasis on storytelling, personal brand, and focusing on one validated channel at a time
• Sandra shares tactical tips for LinkedIn growth and content structuring
• AI enables solo marketers to match output of large teams, affordably and fast

Notable Quotes:

Guest Links:
• X: @takotreba
• LinkedIn: Sandra Dajic

In this episode, I chat with Niels Klement (Head of Growth, Perspective) about how “app-feel” mobile funnels—with quiz questions, instant personalization, and 1-second load times—are crushing the old landing-page model. We dig into paid-ads math, creative iteration, and why a single 90-second video can double your business. Perfect for agencies, SaaS founders, and anyone chasing dollar-in → five-dollars-out predictability.

Timestamps

• 00:00 – Intro & why most builders fail on mobile
• 01:00 – Perspective’s path to €10 M ARR / 6 000 customers
• 02:30 – From web-design agency to quiz-funnel SaaS
• 06:00 – Interactivity, sunk-cost bias & personalization
• 09:30 – Page-speed math: 5 s vs 1 s loads
• 12:30 – Designing funnels that feel like native apps
• 17:30 – Best-fit customers: agencies & B2B teams
• 22:00 – Paid ads vs organic: guaranteed distribution
• 27:00 – Creative ops: turning 1 ad into 100 variants
• 33:00 – Dog-fooding Perspective to grow Perspective
• 38:00 – AI, “vibe-marketing,” and small-team scale
• 42:00 – Free 14-day trial & closing remarks

Key Points (to skim fast)

• Mobile-first, one-page apps load ~1 s and behave like IG Stories.
• Quiz/configurator flows lift conversions and qualify leads.
• 1 s load time ≈ 2.5× conversion—that’s a $1 M → $2.5 M funnel without extra spend.
• Paid ads = best first lever for predictable, measurable growth.
• Creative flywheel: launch 100 assets, kill 98, scale the 2 that print money.
• Dog-food advantage: marketing uses Perspective daily, feeding product loops.

Notable Quotes

Quick Funnel Framework

1. Craft an irresistible offer (free trial, template, case study).
2. Map the funnel steps backward from that goal.
3. Add interactive questions to personalize and pre-qualify.
4. Obsess over load speed and mobile UX.
5. Measure, prune, scale—let data pick winners.

Guest Socials
LinkedIn – https://www.linkedin.com/in/nielsklement/
Perspective – https://www.perspective.co/

In this episode, we’re joined by Jordan Mix, partner at Late Checkout, for an in-depth discussion on how startups can build a million-dollar brand in today’s hyper-competitive landscape. Jordan introduces the concept of digital gravity—a framework for creating “mass” on the internet that draws customers into your brand’s orbit. The conversation explores how companies can move beyond linear funnels and embrace orbit-based growth, where repeated brand interactions across multiple channels drive purchasing decisions.

Together, we break down actionable strategies for generating traction, including the smart use of AI agents, automation, and vibe marketing. Jordan shares insights on balancing transactional marketing (like paid ads and cold outreach) with long-term brand-building investments, while emphasizing the role of creators, content flywheels, and the importance of being discoverable in AI-driven search results.

Timestamps:
 00:00 - Introduction: Building a million-dollar brand in 2025
 00:27 - Meet Jordan Mix and overview of Late Checkout
 01:10 - The idea of digital gravity and mass in the AI era
 03:00 - Funnels vs. orbits: How people really buy
 06:15 - Automation, AI agents, and vibe marketing explained
 10:45 - AI SEO, branded search, and surviving the law of shitty click-throughs
 15:20 - Building discovery flywheels and creator-driven growth
 20:30 - Strategies for leveraging YouTube, Reels, and creators at scale
 25:00 - Managing creator risk and internal content strategies
 28:00 - How to start creating digital gravity without overwhelm

Key Points:
 • Digital Gravity Framework — Customers enter your orbit through repeated brand interactions, not linear funnels. The goal is to create mass (content, tools, assets) that attracts and retains attention.
• AI Agents + Automation — Jordan highlights practical uses of AI agents, like automating outreach campaigns, creating dynamic ad workflows, or scraping competitive data to inform marketing.
• Transactional vs. Brand Marketing — Early traction often comes from transactional tactics (ads, cold outreach), but long-term success requires investment in brand and content that lowers acquisition costs over time.
• SEO in the Age of AI — With LLMs scraping Google’s top pages, brands need to dominate bottom-of-funnel keywords and question-based queries to appear in AI search results.
• Creator-Led Growth — Partnering with creators can trigger a viral cascade where hundreds of pieces of content are generated without direct cost, building digital gravity passively.

Key Takeaway:
 Startups should focus first on finding where their customers spend time, test 2-3 channels, and double down on what works. From there, build repeatable processes and automate intelligently. The goal: maximize digital mass where it matters most, so your brand becomes the natural choice when buyers are ready.

Notable Quotes:
 • “Funnels create linear growth. If you want exponential growth, you need digital gravity.” — Jordan Mix
 • “Where are your customers? Build as much mass as possible in that space.” — Jordan Mix
 • “Every ring you put out is like a mini-funnel — together they form the black hole of your brand.”

Guest Socials:
 X: @jrdnmix
LinkedIn: https://www.linkedin.com/in/jordan-mix1/

In this episode, I chat with Jonathan, a rapidly rising expert on Twitter known for building and scaling AI-driven marketing automations using tools like n8n and custom API integrations. We explore the practical realities of "vibe marketing" automation beyond hype, revealing how real-world workflows are being constructed today and why true expertise in marketing is essential for effective automation. Listeners will gain insights into automating audience research, creative production, and ad performance analysis at scale, as well as actionable tips for getting started and leveraging AI tools to 10x their output.

Timestamps

(00:00) – Introduction to Jonathan and Marketing Automation The host introduces Jonathan and sets the stage for a discussion on modern marketing automation tools and why they’re currently so powerful.

(02:45) – Jonathan’s Background and Automation Journey Jonathan shares how he got into marketing automation, his paid ads background, and the evolution from manual work to automation.

(07:30) – Key Tools and Stack for Automation The host and Jonathan discuss their tech stacks, highlighting n8n, railway.com, and custom front-end interfaces to streamline automation.

(12:15) – Top Marketing Automation Workflows Jonathan outlines his most effective workflows: audience research, creative generation, and scaling marketing insights.

(18:00) – Audience Research Automation: Reddit Scraping and Analysis A deep dive into using n8n to scrape Reddit, filter and analyze discussions, and extract actionable marketing insights and customer language.

(25:40) – Twitter Insights Automation How Jonathan automates scraping Twitter for popular posts, identifying top-performing content and structuring it for ongoing content creation.

(31:10) – Creative Production Automation Jonathan explains workflows for bulk generating ad variations using OpenAI’s Image Gen API, including reference image analysis and prompt engineering.

(38:20) – Custom Front-End Interfaces for Workflows The pair discuss integrating user-friendly front-end UIs (using Lovable or Bolt) with n8n backend automations for client and team use.

(44:50) – Automating Ad Performance Analysis Jonathan describes a flow for pulling and analyzing Facebook Ads data, using sub-agents for performance analysis, deep research, and new ad creation.

(51:10) – Video Ad Automation and Future Trends A look at how video ad automation is evolving and the current limitations and opportunities, including upcoming tools like Google Veo 3.

(56:40) – Speeding Up Workflow Creation with Perplexity and Claude The host and Jonathan discuss using AI (Perplexity, Claude 4) to generate n8n workflow JSON, streamlining the automation development process.

Key Points

• Expertise in Marketing is Essential for Automation: To automate marketing workflows effectively, you need a deep understanding of marketing processes themselves. Only then can you define, script, and automate successful campaigns[1].
• Automating Audience Research Drives Results: Bulk scraping and analyzing platforms like Reddit and Twitter allow marketers to extract pain points, trigger events, and customer language at scale, informing ad copy and creative direction.
• Creative Volume is Game-Changing: Automation tools like OpenAI’s Image Gen API enable the generation of hundreds of ad variations, feeding algorithms for higher performance and lower costs.
• Custom Front-Ends Improve Workflow Accessibility: Building user-friendly interfaces (using tools like Lovable or Bolt) for complex n8n automations makes them accessible to non-technical team members and clients.
• AI Accelerates Workflow Development: Using AI tools like Perplexity and Claude to generate n8n workflow JSON reduces the time and technical skill required to build sophisticated automations.
• Human-in-the-Loop Remains Critical: While automation handles the heavy lifting, human oversight is still needed for nuanced analysis, curation, and final ad selection.

Notable Quotes

• Jonathan: “You have to be an expert at that thing to be able to go and actually build out these automations. But when you do that, you can automate 80% of the work that you previously were doing.”
• Jonathan: “I literally just tell Claude what I want to build, and then it maps it out for me. And then you kind of have a canvas that is like 60, 70, 80% there depending on the complexity.”
• Cody: “Your customers are your best advertisers, so taking their exact wording and phrases is for sure going to be an effective marketing strategy a lot of the time.”

Actionable Takeaways for Founders, Marketers, and Podcasters

• Start with a Core Marketing Process: Identify a repeatable marketing workflow you fully understand before attempting to automate it.
• Invest in Audience Research Automation: Use tools to scrape and analyze discussions on Reddit, Twitter, and other platforms to extract customer pain points and language for your messaging[2].
• Bulk Generate and Test Creatives: Leverage AI to produce hundreds of ad variations, enabling rapid testing and optimization of creative assets.
• Automate Performance Analysis: Implement workflows to automatically pull and analyze campaign performance data, allowing you to focus on strategy and execution[8].
• Simplify Tool Accessibility: Build custom UIs for your automation tools to make them accessible for your entire team, not just engineers.
• Accelerate Workflow Development: Use AI-powered tools like Perplexity and Claude to generate automation scripts and reduce development time.

Brought to you by

• TalentFiber – Hire top offshore engineers with US experience at half the cost of US hires. - talentfiber.com

Where to the find Guest:

•  https://x.com/vibemarketer_
•  https://linktr.ee/vibemarketer

Resources Mentioned

• https://www.youtube.com/@nateherk
• https://www.youtube.com/@Mark_Kashef
• https://www.youtube.com/@AI-GPTWorkshop/videos
• RapidAPI – Access a wide range of third-party APIs for quick integrations. - rapidapi.com
• Apify – Scrape websites and extract data at scale. - apify.com
• TwitterAPI.io – Free and affordable Twitter data scraping tool. - twitterapi.io