Key Takeaways

• Agents work where data is unified. DevRev’s Airdrop ingests/syncs tools and builds a knowledge graph, enabling accurate enterprise search and agent actions across support, product, and revenue workflows. (DevRev)
• Tiny, mighty teams: Startups are reaching ~$10M ARR with ~10–20 people by deploying AI agents for SDR, AE, and Customer Support—automating repetitive tasks and keeping humans for high-context work. (Discussed in episode.)
• Enterprise vs. SMB: Small companies can hire one experienced “agent ops” owner and ship fast; enterprises stall on internal builds, compliance, and cross-team alignment before circling back to a vendor. (Discussed in episode.)
• Human story wins. As “AI slop” floods feeds, audiences will seek content with a verifiable human arc—authenticity, provenance, and outcomes. Detection tools (like AIorNot) help restore trust signals. (aiornot.com)
• DevRev momentum: Series A $100.8M; valuation ~$1.15B; mission: connect end users, support, sales, product, and devs on one AI-native platform. (Reuters, DevRev)

Chaptered Timeline

• 00:00 Cold open — “You can create AI SDR/AE/Support agents today”
• 00:55 Welcome + guest intro: Agus Vivas (DevRev) & why human stories still matter
• 02:06 Career arc: consulting → banking ops → tokenized real estate → AI GTM
• 05:25 Inside Argentine banking ops: CSAT, churn, and support as a revenue stream
• 07:35 DevRev origin: bridging customer-facing and backend teams; tool sprawl → single AI-native layer (DevRev)
• 09:58 Airdrop & migration: hours not months; privacy and coexistence with existing stacks (DevRev)
• 10:58 Enterprise Search (Turing): “ChatGPT for your company data” → faster decisions (DevRev)
• 12:11 Market noise & the unicorn bar: from hype to durable design principles (Reuters)
• 13:00 Playbook: SMB vs. Enterprise—how each should roll out agents
• 17:02 Where agents hit hardest: customer experience first; GTM second
• 18:18 Full-stack outbound: prospect discovery + signal detection + 1-click omni-channel sequences
• 20:06 The downside of AI content: sameness, distrust, and detection layers (AIorNot) (aiornot.com)
• 24:00 Education & kids: keeping the “thinking muscle” while using AI as leverage
• 30:30 Closing: “Human + AI to enhance, not replace” → where to find Agus

Quotes

• “We’ll chase the real story behind the content—that human imprint AI can’t fake.”
• “Startups are hitting $10M ARR with teams of twenty because agents remove the busywork.”
• “It’s not speed for speed’s sake; it’s speed that preserves value and trust.”

Guest

Agustín Vivas de Lorenzi — Founding Member, GTM @ DevRev
Guest socials: LinkedIn → https://www.linkedin.com/in/agusvivasdl
Context: Founding GTM at DevRev since 2023; background in banking ops (Galicia), tokenized real-estate (Bricks); MBA at Governors State University. (THE ORG)

Links & Resources

• DevRev – AI-native platform for support, product & revenue (Airdrop, Enterprise Search) → devrev.ai. (DevRev)
• DevRev Series A ($100.8M, $1.15B val.) → DevRev blog / Reuters coverage. (DevRev, Reuters)
• Airdrop (data ingestion/sync) → product page & docs. (DevRev)
• Enterprise Search / Turing → product explainer & demos. (DevRev)
• AIorNot (sponsor) – Free AI detector; enterprise tools. (aiornot.com)
• Agus on LinkedIn → https://www.linkedin.com/in/agusvivasdl (guest-provided)

Sponsor: 

AIorNot.com — Free AI checker for text, images, music & video; enterprise detection and moderation tools. (aiornot.com)

Cihan shares how AI, digital distribution, and pay-per-viewer streaming are transforming the film industry—from independent creators making Oscar-worthy content to major studios leveraging AI-generated actors. We dive into the future of content creation, why the theatrical window is ripe for disruption, and how filmmakers can monetize directly without Hollywood’s traditional gatekeepers.

If you’re curious about the AI-driven future of film, streaming, and live events, this episode is a must-listen.

🗝️ What You’ll Learn

• AI & Filmmaking: How AI is slashing production costs and boosting creative output.
• Digital Box Office 2.0: Why Venue+ is the future of per-person ticketing for movies and live events.
• AI Actors & Digital Assets: The coming wave of AI-generated stars and licensing opportunities.
• Advice for Filmmakers: How creators can use AI tools and platforms to reach global audiences.
• Industry Disruption: Why traditional theaters risk being left behind without digital innovation.

🕒 Episode Chapters

00:00 – The coming AI content explosion (30X growth forecast)
06:30 – How Venue+ reinvents ticketed streaming for live & theatrical events
14:50 – AI-generated actors, deepfakes & the future of digital characters
22:10 – The economics: lowering costs, increasing output, reaching global audiences
27:30 – Advice for aspiring filmmakers & independent creators
33:00 – How AI + streaming = a new era for movies & live events

👤 About the Guest

Cihan Fuat Atkin is the founder & CEO of xSynx and Venue+, a streaming platform pioneering pay-per-viewer technology to bring theatrical releases and live events directly to audiences worldwide.

• LinkedIn: Cihan Fuat Atkin

• Website: xcinex.com

• Try Venue+: venue.stream

🎥 Sponsor

This episode is brought to you by AIorNot.com
– detect whether content was created by humans or AI in seconds.

We discuss:

• How Alex’s first ventures (selling internet to neighbors and running an internet café) taught him entrepreneurial grit.
• Why consulting shaped his perspective on automation and pricing inefficiencies.
• The challenges of pitching AI-driven pricing inside a traditional consulting model.
• Bootstrapping Competera with his own money, surviving early burn rates, and closing enterprise deals with just 300 products.
• How AI is reshaping pricing strategy, junior roles, and the speed at which founders must now operate.
• The future of AI in education, automation, and vertical solutions.

Alex also shares candid insights about fundraising, navigating corporate politics, and why focus, speed, and honesty are the true superpowers for founders in the AI era.

Chapters:

• 00:00 – Big ideas start simple
• 03:00 – Early life in Ukraine & first businesses
• 08:00 – Consulting, automation, and discovering pricing inefficiencies
• 13:00 – Why big firms resisted subscriptions & Alex’s pivot
• 16:00 – Bootstrapping Competera and landing first enterprise clients
• 23:00 – Compute costs, margins, and survival under the radar
• 28:00 – AI adoption in retail and beyond
• 33:00 – The future of education in an AI-driven world
• 36:00 – Advice for new founders in the post-LLM era

Connect with Alex Halkin:
🔗 LinkedIn

Brought to you by:
👉 AIorNot.com – Detect if content was created by AI or a human.

What you’ll learn

• Why “AI‑sounding” emails are becoming a new professional faux pas.
• Native vs. non‑native users: who actually benefits from grammar tools (and why).
• The evolution from rules → LLMs → heuristics (and how to marry them).
• “Delivery > model”: placing help where users write (Gmail, Docs, chat UIs).
• Education vs. productivity: when AI should hint—not answer.
• Product lessons: simplify, surface proactively, reduce clicks.
• How to approach a custom model: open source options, data realities, and evals.

Chapters (YouTube)
00:00 – The problem with AI‑sounding writing
00:45 – Meet Aleksandr Lashkov & the early Linguix journey
02:30 – Who uses grammar tools (native vs. non‑native)
05:20 – From rules to LLMs: the 3‑layer stack
07:45 – Post‑ChatGPT: why grammar tools didn’t die
10:30 – Delivery beats model choice (extensions, in‑context help)
12:40 – Humanizer: removing AI tells & emerging etiquette
15:20 – AI in education: hints over answers, critical thinking
18:40 – Why “writing coach” flopped at work
21:30 – Simplifier vs. paraphraser: usage hockey stick
24:05 – Two educator camps & using analytics for support
26:50 – The future: AI everywhere, natural language as the new UI
29:30 – Build vs. buy: open source, data costs, and evals
33:10 – What Aleksandr would do differently today
36:20 – Open‑source parity & getting started
38:30 – Wrap

Links & mentions
• Sponsor: AIorNot.com — detect whether text is human or AI‑generated.
• Guest: Aleksandr Lashkov — co‑founder, Linguix (AI writing assistant).

In this conversation, we dive into how Aquibur took AMP-powered, interactive email technology and evolved it into a full-fledged AI-driven email marketing and automation platform (Mailmodo). We cover his founding story, the shift from static to interactive emails, his approach to product-market fit, how generative AI is reshaping marketing teams and functions, and practical advice for startups on choosing channels, building trust, and maximizing ROI from email.

Guest: Aquibur Rahman 

• Background: Started in growth roles (Facebook Ads → organic SEO, content, email) at startups and led marketing at ClearTax.
• Mailmodo: Co-founded in 2020 to make emails interactive (using Google’s AMP technology), joined Y Combinator, raised seed from Sequoia.
• Today: Leading an AI-native email marketing & automation platform, launching AI-powered template generation (June 2025) and full “prompt-to-campaign” automation (September 2025).
• Connect:
  • LinkedIn: https://www.linkedin.com/in/aquibur
  • Email: aqeeb@mailmodo.com

Key Topics & Timestamps

• 00:00 – Introduction & AQ’s background
  From Facebook Ads to leading marketing at ClearTax, and the inspiration behind Mailmodo.
• 00:54 – Why interactive email?
  The problem with static email → users click out to websites → low conversions → frustration for marketers.
• 01:30 – Building Mailmodo
  Launch in 2021, Y Combinator, Sequoia seed, global expansion, product roadmap evolution.
• 02:35 – AI in email marketing
  How generative AI will automate template creation, audience building, campaign setup—“just prompt your goal.”
• 03:45 – Technology → solution mindset
  Start with customer pain points, then apply new tech (AMP, then AI) to solve them.
• 05:10 – Marketing fundamentals vs. channels
  Core of understanding customer pain > attention > trust > value—regardless of Google Ads, TikTok, etc.
• 06:20 – Advice for startups today
  1. Identify customers & channels (incl. ChatGPT search).
  2. Craft concise, non-generic messaging.
  3. Leverage influencer marketing, LLM-SEO, retention focus.
• 07:50 – Team structure in the AI era
  From specialized PM/design/eng roles to multifunctional generalists empowered by AI tools.
• 09:20 – Email best practices
  Respect opt-in trust, add value, avoid countdown bombarding; engagement drives deliverability.
• 11:15 – Biggest disruptions in marketing
  SEO → LLM-driven search, cold outreach saturation → need for trust-first educational content, presence on AI platforms.
• 13:10 – Building brand & thought leadership
  For new startups: start with person-to-person sales → scale to content & brand building → become a niche influencer.

Memorable Quotes

Resources & Links

• Mailmodo (interactive & AI email marketing): https://www.mailmodo.com
• Y Combinator: https://www.ycombinator.com
• AMP for Email (Google): https://amp.dev/about/email/
• Aquibur on LinkedIn: https://www.linkedin.com/in/aquibur

You’ll learn:

• David Carson’s Journey
  From benchwarmer goalkeeper to award-winning photojournalist—how early newspaper gigs led him to the Providence Journal, the St. Louis Post-Dispatch, and a 2015 Pulitzer Prize for his Ferguson coverage.
• The Rise of AI in Photojournalism
  Why Carson sees AI image-generation as a threat: deepfakes, democratized disinformation, and an erosion of public trust.
• Real vs. Synthetic
  Exploring “truth-default theory,” the liar’s dividend, and why six-fingered hands and full glasses of wine expose AI’s telltale flaws.
• Case Study: Ferguson Icon
  How Carson’s colleague’s iconic tear-gas photo was nearly lifted wholesale by generative models in just six prompts—and what it reveals about copyright and training-data ethics.
• Tools for Trust
  An introduction to C2PA standards and potential verification workflows to reclaim authenticity online.
• Balancing Act
  Strategies for news outlets: media and AI literacy, responsible sourcing, rapid corrections, and sustainable licensing deals.
• Looking Ahead
  Will the Internet rebel against synthetic content? Predictions on AI hype cycles, the future of general intelligence, and why the real will matter more than ever.

Key Takeaways

• Trust Is Fragile: Even perfect photos can be doubted once AI-slop floods social feeds.
• Verification Matters: Simple labeling and provenance metadata (e.g., C2PA) can help audiences distinguish fact from fiction.
• Creators Are Crucial: Photojournalists supply the real-world data that powers billion-dollar AI models—and deserve fair compensation.
• Public Rebellion: As AI-generated noise grows, audiences will gravitate back to authentic, verified content.

Resources & Links

Guest Socials:
• LinkedIn: https://www.linkedin.com/in/david-carson-628a596a/
• Stanford JSK Fellowship: https://jskfellows.stanford.edu/theft-is-not-fair-use-474e11f0d063

Carson’s Article: “AI or Not” on the impacts of generative AI in photojournalism
C2PA Specification: Coalition for Content Provenance and Authenticity (https://c2pa.org/)

Timestamps:
(0:00) - Intro

(2:29) - Data Privacy and AI Concerns

(3:33) - Generative AI and User-Generated Content

(12:06) - AI in Art and Copyright Issues

(25:06) - Surprising Use Cases: Fake X-Rays and Art Scams

(28:28) - Future Concerns: Biometrics and Identity Theft

Host Links:
Aiornot.com
https://www.linkedin.com/in/tolyk/

In this episode, I had the pleasure of speaking with Julie, a clinical psychologist with a diverse background, including military service and wealth management. She shared her unique approach to psychology, emphasizing the importance of understanding our intrinsic motivations rather than focusing on mental illness. Julie believes that many people suffer from anxiety and depression because they feel inadequate in a fast-paced, capitalistic society, and she aims to help them find their way back to their values and passions.

We also discussed the impact of art on mental health and how it can serve as a healing tool. Julie's travels have led her to support local artists, which not only brings her joy but also helps communities in need. However, she also highlighted the challenges posed by art fraud and the rise of AI-generated art, which can undermine the authenticity of true artistic expression and create distrust among consumers.

timestamps:
(0:00) - Intro

(0:21) - Julie's Background and Career Journey

(2:50) - Approach to Psychology and Coaching

(3:51) - March Madness and Sports Allegiances

(5:37) - Working with Athletes and Entrepreneurs

(9:23) - The Impact of Travel on Art Appreciation

(12:39) - The Role of AI in Art and Personal Experiences with Fraud

Host Links:
Aiornot.com
https://www.linkedin.com/in/tolyk/