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AI for founders
ryanestes.info
95 episodes
2 days ago
Welcome to AI for Founders. I'm Ryan Estes. Here, you'll find tip-of-the-spear conversations with leaders in business, innovation, and health. Each episode will be packed with valuable insights as we learn how these remarkable individuals built moats around their companies to shield them from a future of uncertainty. You'll hear incredible stories of overcoming obstacles, learn about their daily routines that drive success, and discover the life-changing decisions that gave them the lift to reach new heights. Get ready to be informed, inspired, and uplifted.
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Entrepreneurship
Business
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All content for AI for founders is the property of ryanestes.info and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Welcome to AI for Founders. I'm Ryan Estes. Here, you'll find tip-of-the-spear conversations with leaders in business, innovation, and health. Each episode will be packed with valuable insights as we learn how these remarkable individuals built moats around their companies to shield them from a future of uncertainty. You'll hear incredible stories of overcoming obstacles, learn about their daily routines that drive success, and discover the life-changing decisions that gave them the lift to reach new heights. Get ready to be informed, inspired, and uplifted.
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Entrepreneurship
Business
Episodes (20/95)
AI for founders
AI Is Rewiring Pregnancy Care: Babyscripts CEO on RPM, Risk, and Real Outcomes

Guest: Anish Sebastian, CEO & Co-Founder, Babyscripts

Host: Ryan Estes

Episode Summary

Maternal mortality is rising in the U.S. while access to care lags. Anish Sebastian explains how Babyscripts uses AI, remote patient monitoring, and data-driven care plans to connect OB providers with patients between visits, cut unnecessary appointments, and surface high-risk events earlier. We dig into clinical validation, cultural and regulatory friction, value-based care incentives, and what an AI-assisted “team of experts” model means for the future of pregnancy care.

Who This Is For

  • Founders and product leaders in digital health
  • Clinicians exploring virtual care
  • Investors focused on outcomes and cost
  • Operators building AI into regulated workflows

Key Takeaways

  • Maternal health crisis in the U.S.: access and incentives drive outcomes
  • Pregnancy RPM: blood pressure, weight, glucose, symptoms, SDOH, mood screens
  • Two adoption waves: telemedicine/remote care → AI for documentation and prediction
  • B2B2C: sell to providers, prescribe to patients; workflow-first design
  • Validation before scale: studies, workflow fit, and minimizing liability signal fatigue
  • Value-based care rewards prevention and continuous monitoring
  • AI’s first impact: admin automation (notes, coding, billing), then predictive risk
  • Engagement model: task-oriented app—optimize for doing, not scrolling
  • Future: AI agents triage continuous data, escalate to humans, close the loop
  • North star: earlier risk detection, fewer adverse events, more patient agency

Frameworks

Adoption Waves

  1. Telemedicine + Remote Monitoring (COVID acceleration)
  2. AI/LLMs for documentation → predictive risk → agentic care

Care Delivery Loop

  1. Collect → Detect → Notify → Intervene

Engagement Design

  • Weekly education, specific tasks, quick biometrics
  • Short sessions, provider-connected feedback

Incentive Alignment

  • Fee-for-service vs. value-based care

Future Model

  • Team of experts on demand + AI triage agents

Resources

  • Babyscripts
  • Babyscripts — About
  • March of Dimes


Episode

  • ambient.us — Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co — A podcast featuring founders, tech leaders, CTO's, CEO's, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai — Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application — Let us schedule your podcast interviews on the world’s top podcasts.


More from us: aiforfounders.co | ryanestes.info

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2 days ago
59 minutes 22 seconds

AI for founders
AI storytelling for families

Guest: Ricardo Vice Santos, CEO and co-founder of DreamStories.ai

Topic: Agentic content studio, personalized children’s books, character-consistent AI imagery, subscriber-style publishing economics

Episode Overview

How DreamStories.ai turns kids into the hero of their own beautifully illustrated adventure. Ricardo explains the “agentic content studio” model, why he started with physical books, how he achieves character consistency at scale, and the unit economics behind paid acquisition and repeat purchase behavior.

Time-Saving Highlights

  • DreamStories.ai basics: Upload photos → AI creates a consistent main character → choose a template → get a printed book
  • Why books first: proven category, premium willingness to pay, repeatable nightly ritual, durable margins
  • “Intimacy at scale”: personalization that feels one-of-one, delivered with production reliability
  • Team and traction: lean engineering-heavy team, strong repeat purchase behavior, moving toward broader creative tools
  • Market approach: US-first, added non-Latin scripts to expand globally
  • Paid growth reality: Facebook as the steady workhorse, ROAS math, and the path from novelty to service

Key Takeaways (Founder-Focused)

  • Personalization moat: Character consistency is hard; solving it is a defensible advantage
  • Service over one-off product: Episodic books drive retention and higher LTV
  • Physical-first strategy: Consumers expect digital to be free; physical goods sustain CAC and margins
  • Distribution truth: Paid acquisition is an auction—win by superior LTV and repeat behavior
  • Taste matters: Make the creation flow enjoyable for parents, not just the final artifact for kids

Ricardo’s Playbooks and Frameworks

1) Agentic Content Studio Framework

  • Input: photos + light preferences
  • Orchestration: model mix (open-source + proprietary) for character consistency
  • Output: stylized, on-brand illustrations across pages
  • Feedback: human-in-the-loop edits and text control
  • Scale: “Infinite content” goal with guardrails

2) Intimacy-at-Scale Loop

  • Personal artifact → nightly family ritual → social proof at school and with relatives → referrals and repeat gifts → episodic upsell

3) Retention Through Episodes

  • Series structure rather than one-off novelty
  • Age-aware prompts and evolving language difficulty
  • Seasonal and milestone triggers (birthdays, holidays, grade changes)

4) Paid Media Unit Economics

  • Expect CAC ≈ AOV at the start
  • Unlock winning bids via higher LTV (repeat, bundles, subscriptions)
  • Use episodic content to justify continuous repurchase

5) Brand-Safe Personalization Guardrails

  • Restrict IP where necessary
  • Style and conduct policies for cameos and co-characters
  • Human review points for edge cases

Resources and Links

  • DreamStories.ai: https://dreamstories.ai
  • Ricardo Vice Santos on LinkedIn: search LinkedIn for “Ricardo Vice Santos”
  • The NeverEnding Story (reference)
  • Choose Your Own Adventure series (reference)
  • WILD Foundation: https://wild.org

Episode Sponsors

  • ambient.us — Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co — A podcast featuring founders, tech leaders, CTOs, CEOs, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai — Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application — Let us schedule your podcast interviews on the world’s top podcasts.

More from the Host

  • Newsletter: https://aiforfounders.co
  • Ryan: https://ryanestes.info
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4 days ago
59 minutes 2 seconds

AI for founders
Reddit SEO for AI Search: How to Win ChatGPT Recommendations

AI for Founders — Danny Kirk (ReddiReach) Show Notes

Episode summary

Reddit has become a prime source for AI training data and AI search results. Founder Danny Kirk explains how ReddiReach helps 7–10 figure brands win inside AI search by using Reddit the right way. We break down why comments beat posts, how AI search is changing SEO, and what brands should do now to capture demand from LLM recommendations.

Who this is for

Founders, CMOs, growth leaders, e-commerce operators, and SEO pros who want practical playbooks for AI search, Reddit marketing, and LLM-driven discovery.

What you’ll learn

  • How Reddit influences LLM answers and “AI search” visibility
  • Why comment-first strategies outperform posts and ads
  • Brand-safety and compliance on subreddit rules
  • Timelines and expectations for compounding results
  • Pricing and capacity realities for a lean, profitable agency
  • The bear case and risk controls for Reddit-dependence
  • How LLM Buy Now flows and Shopify could change conversion paths

Key takeaways

  • AI search is redefining classic SEO for many queries.
  • Comments are the signal LLMs rely on; quality compounds.
  • Play the long game; this era resembles early SEO.
  • Each subreddit’s rules determine removal or reach.
  • Organic first; posts and ads have different risk/return.
  • Small expert teams can outperform with tight systems.
  • Hedge platform risk; diversify discovery sources.

Frameworks discussed

  1. Reddit Marketing Buckets: Ads, AMAs, Posts, Comments
  2. Comment-First Operating Rules: genuine, helpful, accurate, truthful; help first, brand second; evergreen utility
  3. AI Search Strategy Stack: credible Reddit presence → identify LLM-cited queries → high-quality comments → monitor AI search intel
  4. Brand-Safety Protocol: platform + subreddit rules, native tone, account warm-up and karma
  5. Long-Term Compounding: durable comment assets over volume

Notable numbers

  • ~47 brands served by a ~5-person team
  • ~1 high-quality comment/day (~20 per month)
  • Starting around $1,500–$2,000/month
  • 500+ companies helped across the founder’s career

Resources and links

  • ReddiReach
  • AI Search Intel (Peekaboo)
  • Danny Kirk (LinkedIn)
  • Reddit
  • Ryan Estes
  • AI for Founders

Episode Sponsors

  • ambient.us — Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co — A podcast featuring founders, tech leaders, CTOs, CEOs, and software architects reflecting on their human story in creating world-changing, disruptive digital products.
  • warmstart.ai — Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application — Let us schedule your podcast interviews on the world’s top podcasts.

More from the host

  • AI for Founders
  • ryanestes.info
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5 days ago
52 minutes 51 seconds

AI for founders
Plugging AI Into Production: How MyOp Lets Non-Developers Ship UI Safely


Guest: Keren Fanan, Co-Founder & CEO, MyOp.dev
Topic: Plugging AI-generated UI into production without breaking your core app

Episode overview

AI can now generate front ends and UX logic in minutes, but most teams still cannot ship that code safely. Keren explains how MyOp’s pluggable layer lets non-developers ship UI in isolation while engineering protects the core, enabling faster experiments, A/B tests, and personalization in live apps.

What you will learn

  • How to connect AI-generated components to real products without redeploys
  • The separation-of-responsibilities model for product, design, and engineering
  • How to run safe experiments, staged rollouts, and A/B tests in production
  • Why front-end roles are changing and how non-developers can ship code
  • How to stand up design-partner programs and early customer workshops
  • Seed-stage tactics: pricing, usage metrics, and adoption inside mature orgs

Key takeaways

  • Pluggable isolation: MyOp keeps AI-generated UI and front-end logic isolated from core code so the product remains stable and secure while experiments move fast.
  • Non-dev empowerment: Product managers, designers, and growth teams can ship user-facing components safely; engineering owns core logic, data, and integrations.
  • Faster learning loops: Teams can ship, segment, and roll out UI changes to real users, then iterate based on measurable results.
  • Change management is the work: Success requires explicit ownership, QA gates, and trust building between product and engineering.
  • Pricing follows value: Usage-based subscription aligns cost to shipped components and measurable outcomes.
  • Career shift: A large portion of traditional front-end work moves to “citizen developers,” pushing engineers deeper into core systems or toward product.
  • Women in AI leadership: Action steps to widen participation and turn AI fluency into new leadership paths.

Frameworks and operating models

MyOp Architecture

  • Open source SDK inside the host app to define a safe “contract” to the core
  • Management hub for pasting AI-generated code, QA, segmentation, A/B tests, version history, and gradual rollouts

Separation of Responsibilities

  • Engineering: core domain logic, data models, integrations, stability, security
  • Product/Design/Growth: UI components, micro-interactions, experiments, and personalization via AI tools

Experiment-to-Production Pipeline

  1. Generate component with AI tool of choice
  2. Plug into MyOp management hub
  3. QA segment → beta segment → broader rollout
  4. Measure, iterate, and sync to Git as needed

Adoption Playbook

  • Lead with live demos built by non-developers
  • Run hands-on internal workshops to teach “vibe coding” for real app components
  • Use design partners to validate value and prove speed-to-impact

Pricing and Metrics

  • Usage-based subscription tied to shipped components and real outcomes

Fast stats

  • Founded: 2024
  • Team size: ~10
  • Capital raised: ~$2M seed
  • HQ: Tel Aviv, operating globally
  • Focus: UI/UX in production, experiments, segmentation, A/B testing, and rollouts

Resources mentioned

  • MyOp.dev: https://myop.dev
  • Keren on LinkedIn: https://www.linkedin.com
  • Women in Tech Israel: https://www.women-in-tech.org


Episode Sponsors

  • ambient.us - Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co - A podcast featuring founders, tech leaders, CTO's, CEO's, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai - Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application - Let us schedule your podcast interviews on the world’s top podcasts.

More from AI for Founders: https://aiforfounders.co
About Ryan: https://ryanestes.info

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6 days ago
57 minutes 55 seconds

AI for founders
Early warning for neurology and mental health with voice AI

Henry O’Connell, CEO of Canary Speech

— Voice Biomarkers, and Real-Time Clinical Support

Summary

Canary Speech turns everyday conversation into clinical-grade insight. Henry O’Connell explains how ambient listening analyzes 2,590 vocal biomarkers every 10 milliseconds to produce about 16 million data points per minute. The system returns real-time scores for anxiety, depression, cognitive health, Parkinson’s, multiple sclerosis, and more without interrupting the doctor–patient relationship. We cover continuous monitoring, aggression detection for nurse safety, patents and IP strategy, data security, deployment across devices, and how ambient AI moves healthcare beyond chat.


Key Takeaways

  • Voice is a rich biometric after DNA and can signal mental and neurological conditions through vocal biomarkers.
  • Ambient listening integrates into clinical workflows without test-taking or friction.
  • Canary analyzes 2,590 features every 10 milliseconds for roughly 16 million data elements per minute.
  • Real-time clinical decision support returns multi-condition scores to physician devices.
  • Device-agnostic capture works via phones, tablets, telehealth, call centers, and wearables.
  • New continuous monitoring flags risk in rooms and can measure aggression levels to protect nurses.
  • Canary reports 14 issued patents with 12 pending and approximately $26M raised.
  • Data security aligns with hospital-grade standards and ISO certifications.
  • Primary care becomes a force multiplier with earlier referrals and standardized objective metrics.
  • Longitudinal deltas compare a patient’s voice across visits to track change over time.


Who This Episode Is For

  • Founders in AI, digital health, and human–computer interaction
  • Clinical leaders evaluating ambient AI and decision support
  • Product and data teams shipping voice and real-time ML at scale
  • Investors tracking voice biomarkers and healthcare AI infrastructure


Frameworks Discussed


Ambient AI Pipeline

  1. Permissioned audio capture in natural conversation
  2. Speaker separation, sample quality checks, feature extraction
  3. ML models for condition-specific scoring in near real time
  4. Delivery into clinical workflows and notes platforms


Clinical Decision Support Loop

  1. Objective voice-based scores
  2. Physician interpretation and next best question
  3. Referral decision and follow-up
  4. Longitudinal tracking across visits


Longitudinal Delta Method


Compare patient voice features across time to quantify change and trend risk.


Safety and Operations Layer


Aggression detection with green yellow red indicators to reduce nurse assaults and burnout.


Compliance and Trust Stack


Hospital-level security posture, ISO certifications, integration with existing transcription and EHR workflows.


IP and Defensibility


Patents for voice biomarker detection, ambient AI methods, longitudinal comparison, and LLM fusion.


Notable Numbers

  • 2,590 vocal biomarkers analyzed every 10 milliseconds
  • About 15.5 to 16 million data elements per minute of speech
  • Real-time scores returned during normal clinical conversations
  • 14 issued patents and 12 pending reported in the conversation
  • Approximately $26M raised to date reported in the conversation


Resources

  • Canary Speech
  • Henry O’Connell on LinkedIn
  • Henry@canaryspeech.com


Episode Sponsors

  • ambient.us — Your AI Chief of Staff that preps you for every meeting, keeps your team accountable and aligned, and helps you stay on top of key initiatives.
  • codestory.co — A podcast featuring founders, tech leaders, CTOs, CEOs, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai — Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application — Let us schedule your podcast interviews on the world’s top podcasts.


More from Ryan

  • aiforfounders.co
  • ryanestes.info
Show more...
1 week ago
1 hour 2 minutes 42 seconds

AI for founders
Building a Gen Z Art Platform without the Algorithm Trap: Devika Sarin of Soal

AI for Founders

Guest: Devika Sarin, Founder of Soal (thisissoal.com)

Topic: AI-powered art discovery, taste mapping, and community-driven curation for Millennials and Gen Z

Episode Overview

Soal is building a daily ritual for art discovery that blends human curation with behavioral science and AI. Devika shares how the app helps users learn to see, name, and evolve their taste, why early community building beats early monetization, and how contemporary artists can thrive without chasing algorithms.

What You Will Learn

  • How AI recommendation engines and human curation work together for art discovery
  • Practical ways to map and refine user taste using behavioral signals
  • Community-first product strategy for consumer apps
  • How to monetize through prints and partnerships without ads
  • Why contextual education increases engagement and purchase intent

Key Takeaways

  • Start with human-led curation, then scale with algorithms for relevance
  • Build community and context before introducing transactions
  • Treat art discovery like music discovery to create daily habit loops
  • Prints create an accessible on-ramp to collecting and supporting artists
  • Ethical guardrails matter for recommendation systems that shape culture

Frameworks Discussed

1) Discover → Learn → Engage → Support

  • Discover: Daily set of artworks personalized to emerging taste
  • Learn: Lightweight education that meets users where they are
  • Engage: Conversations, context, and deeper rabbit holes
  • Support: Clear paths to shows, prints, and artist patronage

2) Human First → Algorithm Next

  • Phase 1: Curators define quality, tone, and standards
  • Phase 2: AI scales relevance and serendipity within those guardrails

3) Community Before Monetization

  • Audience building and taste education
  • Trust and retention metrics
  • Introduce revenue via prints and aligned partners

4) Taste Mapping Signals

  • Visual preferences over time
  • Session depth and dwell on context
  • Revisit behavior and save lists
  • Artist and genre adjacency graphs


Who This Episode Is For

Founders building consumer AI or marketplaces, product leaders designing recommendation engines, community builders, and creators exploring ethical and effective ways to scale human taste with technology.


Resources and Links

  • Soal: thisissoal.com
  • Join the Soal waitlist and newsletter on site


Episode Sponsors

  • ambient.us - Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co - A podcast featuring founders, tech leaders, CTO's, CEO's, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai - Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application - Let us schedule your podcast interviews on the world’s top podcasts.

Also visit: aiforfounders.co and ryanestes.info

Show more...
2 weeks ago
55 minutes 18 seconds

AI for founders
Founder’s guide to 10x visibility

AI for Founders with Dave Polykoff, Founder of Zenpost

Episode Summary

In this episode of AI for Founders, Ryan Estes sits down with Dave Polykoff, the founder of Zenpost — a content engine helping founders, consultants, and service providers turn one video shoot into a month of high-converting content. Dave breaks down how he built Zenpost into a systemized growth machine that scales personal brands, the frameworks behind consistent visibility, and how AI is transforming content creation at speed and scale.

If you’re a founder or marketer looking to grow your brand, streamline your content pipeline, and actually generate leads from what you post — this episode is your roadmap.

Key Takeaways

  • One Shoot, One Month of Content: Zenpost’s batching framework turns a single recording session into 30+ assets across channels.
  • Content as a Growth Engine: How to 10x visibility while reducing creation time.
  • The Founder’s Flywheel: Consistency, Authenticity, and Distribution working together to build authority.
  • AI in Content Operations: Automating editing without losing the human touch.
  • Scaling Systems: Why structure beats spontaneity when building personal brands.

Frameworks Discussed

The Zenpost Engine

  • Record once → Repurpose everywhere.
  • Break long-form into micro-moments.
  • Match tone to platform, not persona.
  • Automate the scheduling, not the storytelling.

The Consistency Equation

Frequency x Quality x Distribution = Reach

The Founder Visibility Loop

Create → Publish → Engage → Measure → Refine → Repeat weekly.

Resources & Links

  • Zenpost
  • Follow Dave Polykoff
  • Follow Ryan Estes
  • Subscribe to the AI for Founders newsletter

Sponsors

The sponsors of this episode are the most beautiful people on planet earth. See for yourself:

  • ambient.us - Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co - A podcast featuring founders, tech leaders, CTOs, CEOs, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai - Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application - Let us schedule your podcast interviews on the world’s top podcasts.

Connect

  • Learn more
  • Host: Ryan Estes
Show more...
2 weeks ago
49 minutes 11 seconds

AI for founders
AI Comment Moderation, Brand Safety, and Viral Conversions: Stanify.ai’s Playbook

AI for Founders — Show Notes

Guest: Hank Leber, cofounder of Stanify.ai
Topic: Turning the comment section into conversions with multilingual, human-in-the-loop AI

Episode Summary

Hank Leber breaks down how Stanify.ai automates brand-safe engagement in social comment sections and DMs at scale. We cover auto-moderation that preserves healthy debate, multilingual on-brand replies, a human-in-the-loop workflow, and why smart Q&A in comments now powers answer-engine optimization for LLMs. If you run paid social, manage community at scale, or need brand-safe engagement across languages, this playbook shows how to capture viral moments instead of missing them.

Key Takeaways

  • Comment sections are revenue surfaces: Real-time replies in comments increase conversion, reduce CAC, and protect ad spend.
  • Human-in-the-loop wins today: Let AI draft 99% of replies while humans approve the nuanced 1% that defines brand voice.
  • Moderate without sanitizing: Hide true hate or harassment and escalate the rest so healthy debate and authenticity remain.
  • Multilingual at native quality: Replies mirror language and script automatically, including mixed-language comments.
  • LLM routing > single-model bias: Use different models for different jobs (safety, slang, product knowledge).
  • Answer Engine Optimization (AEO): High-quality Q&A in comments is becoming training fuel for LLM recommendations.
  • Viral windows are short: Engagement must land during the spike; retroactive replies miss most of the lift.
  • Protect paid social: Automated moderation on ad comments preserves ROAS and brand equity at scale.
  • Enterprise to SMB: The same workflows power Fortune 100 portfolios and Shopify merchants.
  • AI as data engine: The real endgame is structured insights from conversations, not just faster replies.

Frameworks Mentioned

  1. CommentOps Flywheel: Listen → Detect intent → Draft reply → Human approve/skip → Post → Capture signals → Improve playbooks.
  2. Safety Ladder: Classify → Hide where appropriate → Escalate → Public reply or DM → Record resolution.
  3. Human-in-the-Loop Guardrails: AI drafts → Brand-voice constraints → Reviewer approves/edits/skips → Continuous tuning.
  4. Multi-LLM Router: Choose best model per task (slang, safety, product knowledge, multilingual response).
  5. AEO Playbook: Identify recurring questions → Seed precise answers in comments → Capture long-tail intent.
  6. Viral Wave Tactics: Detect spike → Throttle replies → Prioritize high-intent threads → Convert during window.
  7. Paid Social ROAS Shield: Auto-hide toxic ad comments → Answer purchase blockers fast → Measure CTR/CPC/CPA lift.

Who This Episode Is For

Founders, CMOs, growth and community leads, performance marketers, and creators who need scalable, brand-safe engagement, especially teams running paid social or managing global communities.

Resources & Links

  • Stanify.ai (book a demo): https://stanify.ai/
  • Hank on X: https://x.com/HankLeber

Sponsors
ambient.us - Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
codestory.co - A podcast featuring founders, tech leaders, CTO's, CEO's, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
warmstart.ai - Build lasting business relationships and stay connected with your network, effortlessly.
kitcaster.com/application - Let us schedule your podcast interviews on the world’s top podcasts.

Links: aiforfounders.co | ryanestes.info

Show more...
2 weeks ago
44 minutes 23 seconds

AI for founders
Drew Falkman builds products at the speed of thought

AI for Founders – Guest: Drew Falkman

Summary

In this episode of AI for Founders, Ryan Estes talks with Drew Falkman, a veteran product strategist and AI coach who’s been building digital products for more than two decades. Drew has worked with major brands like HP, Adobe, AARP, and American Airlines, and today he’s leading the charge in AI product acceleration—helping founders build and test products faster than ever before using tools like Lovable, Magic Patterns, and Strella.

This conversation explores the evolution of vibe coding, agentic coding, and generative UI, and how these innovations are collapsing the gap between an idea and a finished, functional app. Whether you’re a product designer, founder, or creative experimenting with AI, this episode reveals how to go from zero to prototype in days—and how the rise of AI-driven interfaces could completely reshape the SaaS industry.

Key Takeaways

  • From Web 1 to Web 3 to AI: Drew started in the early days of the internet, ran a web agency, consulted for Fortune 500 companies, and now builds AI tools that democratize product creation.
  • The Power of Vibe Coding: Tools like Lovable and Cursor let founders and creators build working prototypes in hours, not months.
  • Agentic Coding: AI agents can now “clean up” code, debug, and iterate, turning early vibe-coded prototypes into stable products.
  • Generative UI: Drew predicts the rise of AI that builds user interfaces in real time based on each user’s needs—an entirely new product paradigm.
  • Rapid Validation: Using Magic Patterns and Strella, founders can now design, prototype, recruit testers, and analyze feedback in a single week.
  • The End of SaaS as We Know It: Drew believes the future will favor self-built tools tailored to each founder’s exact workflow, with SaaS companies providing modular backends instead of full platforms.
  • Creative Founders Win: Liberal arts thinking—creativity, adaptability, and critical reasoning—will dominate in the age of AI-driven creation.
  • Personalized Media: The conversation explores the coming shift toward personalized films, entertainment, and storytelling, where AI adapts stories to each individual viewer.

Frameworks & Concepts

  1. Vibe Coding Workflow: Start with a written idea → Generate working prototype → Test with AI user tools → Ship version one.
  2. Generative UI Framework: Understand user context → Auto-generate interface → Iterate in real time → Personalize UX per user.
  3. Rapid AI Validation Stack: Magic Patterns for front-end prototyping, Strella for AI user interviews and analytics, Lovable for functional MVPs.
  4. Founder-Build Model: Build tools alongside your audience, test for engagement before monetization, then layer backend and payments once validated.

Resources

  • Magic Patterns
  • Strella
  • Lovable
  • AI Product Accelerator

Sponsors

The sponsors of this episode are the most beautiful people on planet earth. See for yourself:

  • ambient.us - Your AI Chief of Staff that preps you for every meeting, keeps your team accountable & aligned, and helps you stay on top of key initiatives.
  • codestory.co - A podcast featuring founders, tech leaders, CTO's, CEO's, and software architects, reflecting on their human story in creating world changing, disruptive digital products.
  • warmstart.ai - Build lasting business relationships and stay connected with your network, effortlessly.
  • kitcaster.com/application - Let us schedule your podcast interviews on the world’s top podcasts.

More from AI for Founders

Visit aiforfounders.co for new episodes, tools, and insights.

Connect with Ryan at ryanestes.info

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2 weeks ago
39 minutes 43 seconds

AI for founders
Building an AI Chief of Staff: Ambient by Lawrence Coburn

Show Notes: Lawrence Coburn, CEO & Co-founder of Ambient

Serial founder Lawrence Coburn (DoubleDutch, Twine) returns with Ambient, an AI Chief of Staff that helps founders and CEOs reclaim time and upgrade decision quality. After interviewing 400 Chiefs of Staff, Ambient focuses on three high-leverage workflows: daily prep dossiers, secure leadership meeting notes, and red/yellow/green tracking on make-or-break initiatives. We cover the CoS vs EA vs AI division of labor, why “push not pull” is the future UX, and how calendar-anchored intelligence powers fundraising and execution.

Key Takeaways

  • AI Chief of Staff is a role, not a feature: Ambient targets the Office of the CEO with purpose-built workflows.
  • Three core workflows: Daily Prep dossiers, secure leadership notes, and red/yellow/green initiative tracking.
  • Push, not pull: Deliver insights to inbox and calendar instead of adding another dashboard.
  • Decision quality over volume: Raise the bar beyond “directionally correct.”
  • CoS vs EA vs AI agent: Different horizons; all improve with fuller context access.
  • Throughput goal: Realistic CEO ceiling ~1.8x with AI augmentation.
  • Fundraising Mode: Investor-ready dossiers with icebreakers, similar investments, red flags, and mutuals.
  • No easy moats in gen-AI: ICP focus and deep workflow ownership create the edge.
  • Founder wellness: Exercise, sleep, and family time support better decisions.

Frameworks

1) Office of the CEO OS (CoS–EA–AI)

  • EA (Day-to-day): Calendar, inbox, travel, near-term logistics
  • Chief of Staff (Strategic): Planning, investor/board prep, cross-functional execution
  • AI Agent (Context Amplifier): Aggregates calendar, transcripts, Slack, email; summarizes, flags risk, recommends next steps

2) Ambient’s Three-Workflow Stack

  • Daily Prep: Auto dossiers for each calendar event
  • Rhythm of Business Notes: Secure capture, action items, ownership, alignment detection
  • R/Y/G Initiatives: Proactive status on the few company-critical projects

3) Push UX Principle

  • Deliver outputs to the inbox and calendar
  • Minimize new tools and logins
  • Let insights find the executive

4) Decision Quality Ladder

  1. Directionally correct
  2. Context complete
  3. Option-space explored
  4. Explicit tradeoffs
  5. Chosen action with owner and follow-ups

5) Pricing Mindset for AI Ops

  • Bias to simplicity at early stage
  • Explore outcome/usage components later without adding anxiety or hidden complexity

Resources & Links

  • Ambient (AI Chief of Staff)
  • Lawrence Coburn (LinkedIn)
  • Lawrence Coburn (X/Twitter)
  • Girls on the Run Rockies

Connect

  • Subscribe to AI for Founders
  • About Ryan Estes

Sponsors

The sponsors of this episode are the most beautiful people on planet earth. See for yourself:

  • ambient.us
  • codestory.co
  • warmstart.ai
  • kitcaster.com
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3 weeks ago
58 minutes 24 seconds

AI for founders
Inside the $50M mission to fix clinical evidence

Guest:

Dr. Brigham Hyde, Co-Founder & CEO of Atropos Health

Episode Summary:

In this episode, Ryan Estes interviews Dr. Brigham Hyde to explore how Atropos Health is closing medicine’s “evidence gap” — the staggering reality that only 14% of clinical decisions are based on high-quality evidence. With products like ChatRWD® and GENEVA OS™, Atropos uses generative AI to transform real-world data into validated evidence in minutes, not months.

This discussion is for founders, data scientists, healthcare innovators, and investors who want to understand the intersection of AI, regulation, and scientific rigor in healthcare.

Key Takeaways:

  • The 14% Problem: Most clinical decisions lack strong evidence. Atropos aims to fix that with real-world data and AI.
  • From Research to Real Time: ChatRWD® generates personalized evidence in minutes.
  • Rigor Over Hype: Eliminating AI “hallucinations” in healthcare applications.
  • GENEVA OS™ Framework: Automating evidence generation through secure, federated data networks.
  • Scaling Trust: Why partnerships with institutions and pharma matter for adoption.
  • Global Expansion: Navigating data privacy and regulatory diversity.
  • Ethical AI: Building systems that balance speed with safety.
  • Investor Perspective: How VCs evaluate AI healthtech startups.
  • Leadership Philosophy: Balancing scientific precision with entrepreneurial execution.
  • Future Vision: The rise of AI-enabled, evidence-based healthcare systems.

Frameworks Mentioned:

The GENEVA OS™ Model

  • Gather – Securely access real-world patient data across networks.
  • Evaluate – Apply validated statistical methods using generative AI.
  • Normalize – Harmonize data for consistency and comparability.
  • Explain – Deliver transparent evidence clinicians can trust.
  • Validate – Confirm reproducibility before deployment.

The Atropos “Speed-to-Rigor” Balance

  • Automate data analysis pipelines.
  • Maintain clinical validation checkpoints.
  • Ensure auditability and traceability of outputs.

Resources & Links:

  • Atropos Health Official Site
  • VentureBeat Article
  • BusinessWire Release
  • Fierce Healthcare Coverage
  • Dr. Brigham Hyde on LinkedIn
  • AI for Founders
  • Ryan Estes
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3 weeks ago
48 minutes 40 seconds

AI for founders
Build Remote Operations that Work: Isaac Kassab (Pearl Talent)

How Isaac Kassab Scaled Pearl Talent to $10M in ARR

Guest: Isaac Kassab (Pearl Talent)
Host: Ryan Estes, AI for Founders

Overview

In this episode of AI for Founders, Ryan Estes sits down with Isaac Kassab, cofounder of Pearl Talent. Isaac shares how he bootstrapped the business to $1M ARR in 7 months and scaled it to $10M by year three. You’ll hear actionable insights about using conversational agents for recruiting, structuring remote-first operations, and achieving high retention in global talent networks.

Who This Is For

  • Startup founders scaling remote teams
  • HR, recruiting, operations leaders exploring AI + global staffing
  • Anyone wondering how to combine systems and human judgment
  • Tech executives seeking scalable process playbooks

Key Takeaways / Highlights

  1. Bootstrapped growth with discipline
    $1M ARR in 7 months, $10M by year 3. Emphasize credible readiness over polish.
  2. Conversational Agents as scalable “humans”
    Use cases: vetting, onboarding, data collection. Pattern: AI input → scoring / validation → human review.
  3. Retention is mission-critical
    Pearl targets ~86% retention. Focus on onboarding, culture, continuous support.
  4. Client trust comes from proof
    Use quantifiable metrics (cost saved, uplift) rather than vague promises.
  5. Systems over personalities
    Process and structure outperform charisma. Build repeatable workflows.
  6. Vertical specialization vs. horizontal expansion
    Depth in select industries > being broad. Use domain expertise to differentiate.
  7. Frameworks for scale
    Leverage conversational agents across repetitive touchpoints. Insert structure around human work. Monitor early warning signals.

Frameworks & Models Discussed

Framework / Model

Purpose

Components

Conversational Agent Pattern

Automate human-like conversation in operations

Input (user text) → Scoring / Validation → Human Review / Decision

Readiness over Polish

Buyer qualification philosophy

Documented proof (resume, funds, advisors) > polished pitch

Retention Signal Monitoring

Early detection of friction

Engagement, response times, performance degradation

Domain Specialization Strategy

Competitive focus

Serve verticals deeply rather than broadly

Resources & Links

  • Pearl Talent
  • Windmill Growth case study (“142% website growth”) — windmillgrowth.com
  • GIMBHI Q&A interview with Isaac Kassab — gimbhi.com


Produced by AI for Founders. More episodes and transcripts at aiforfounders.co. Learn more about Ryan Estes at ryanestes.info.

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3 weeks ago
1 hour 2 minutes 18 seconds

AI for founders
From Farm to Mac App Store: How Heberti Built Pinery for Authors

Building Pinery with Heberti Almeida

Summary

From a stormy Brazilian farm to the Mac App Store. Former Square engineer Heberti Almeida spent seven years turning a side project into Pinery, a focused Markdown writing and self-publishing app for Mac. We cover privacy-first on-device AI, clean ePub and PDF export, subscription pricing that sustains indie software, and how tractor time can sharpen product thinking.

Who this is for

  • Indie hackers
  • Technical founders
  • Author-creators
  • Anyone seeking a calm, private, production-grade writing workflow

Product snapshot

  • Pinery: Markdown editor for writing, designing, and exporting books
  • Exports: ePub 3, clean digital PDF, static website
  • Focus: Distraction-free writing, live preview, customizable typography and design
  • Privacy: File-based, offline friendly, iCloud optional, exploring on-device AI proofreading
  • Model: Mac App Store with monthly and annual subscriptions
  • Early traction: ~600 users and 40 subscribers within the first month


Key takeaways

  • A single-purpose tool can beat feature bloat when the output quality is excellent
  • Privacy by design creates trust and a durable product moat
  • Product Hunt and creator newsletters can drive meaningful early traction without paid ads
  • Subscription pricing is the most reliable way to sustain indie software and ship updates
  • Alternating deep work with physical work can accelerate problem solving and reduce stress

Frameworks discussed

1) Privacy-First Authoring

  1. Keep manuscripts local as plain text Markdown
  2. Offer optional cloud sync controlled by the user
  3. Add on-device AI for proofreading and tone adjustments
  4. Never transmit manuscript text to third-party LLMs by default

2) Lean Publishing Loop

  1. Write in focus mode
  2. Live preview for structure and flow
  3. Design pass with typographic controls
  4. Export to ePub or PDF
  5. Ship and iterate on reader feedback

3) Calm Tool Product Strategy

  1. Decide the core outcome
  2. Remove non-essential features
  3. Obsess over export fidelity
  4. Embrace opinionated defaults
  5. Document power features without cluttering the UI

4) Indie Pricing Rationale

  1. Map pricing to a single successful outcome
  2. Favor annual plans with a fair monthly option
  3. Use App Store subscriptions for sustainable updates
  4. Expect some pushback and stay the course

Links and resources

  • Pinery website
  • Pinery on the Mac App Store (search “Pinery”)
  • Pinery on Product Hunt
  • Heberti on X
  • AI for Founders
  • Ryan Estes
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1 month ago
48 minutes 35 seconds

AI for founders
Newsletters outsell social: Eunice Tan on building kawara.ai

AI for Founders with Eunice, Co-founder and CTO of Kawara.ai

Topic: Turning creator content into newsletter-driven sales

Summary

Eunice explains how content-led growth is reshaping sales for creators and lean startups. Kawara.ai helps solopreneurs turn YouTube and other consumed or created content into weekly newsletter drafts that convert. We cover why newsletters outperform social for sales, how to keep voice quality high with AI, and the roadmap from drafts to full revenue workflows.

Who this is for

Founders, creators, and solo operators who want reliable conversions from audience to revenue. Teams that need to publish consistently without adding headcount. Builders exploring agentic workflows and AI-assisted content systems.

What You Will Learn

  • Why newsletters often drive 60 percent or more of creator conversions
  • How a small list can outperform a large social audience for booked calls and sales
  • The system to go from video and links to a publish-ready newsletter in minutes
  • How to keep your voice intact with AI while reducing time to draft
  • The path from newsletters to a broader sales engine across platforms

Key Takeaways

  • Owned audience beats rented audience. Email creates durable relationships that survive algorithm shifts.
  • Consistency converts. Weekly newsletters provide the multi-touch needed for higher ticket decisions.
  • Small list. Big impact. A 2,000-subscriber list can book more revenue than a 50,000-subscriber channel when the offer and cadence are right.
  • Time to value matters. Templates and opinionated defaults reduce friction for busy solopreneurs.
  • Trust is earned. Show your work early. Hide the magic later. Users accept more automation after visible reasoning builds confidence.
  • Price tests never end. Start founder-friendly. Adjust as value and costs become clearer.
  • Bootstrap first if you can. Keep optionality. Take capital from partners who bring network and conviction.

Frameworks Discussed

1) Content-Led Sales Loop

Listen to audience signals. Publish a weekly story-driven email. Link to a clear offer or call booking. Collect replies and clicks. Feed insights back into next week’s draft.

2) Newsletter Engine in 5 Steps

  1. Connect sources you create
  2. Connect sources you consume
  3. Pick a proven template
  4. Generate a draft in your voice
  5. Edit for one clear CTA and ship

3) Voice Integrity with AI

Start with user tone guidance. Use creator-tested templates for structure. Allow light prompts for nuance. Constrain choices to prevent paralysis. Audit outputs for drift.

4) Trust Ramp for Agentic Products

Phase 1. Show reasoning and steps.
Phase 2. Collapse steps into summaries.
Phase 3. Hide steps by default. Reveal on demand.

5) Product Choice Hygiene

Few choices. Strong defaults. Obvious next action. Measurable outcomes.

Light Case Study Mentioned

YouTube creator with 51,000 subscribers and a 2,000-subscriber newsletter reported roughly twice as many booked client calls traced to the newsletter versus YouTube. Multi-touch consistency and owned distribution were the difference.

Tools and Links

  • Kawara.ai
  • Justin Welsh Sunday newsletter reference
  • Ali Abdaal newsletter reference
  • James Clear newsletter reference


Connect

  • aiforfounders.co
  • ryanestes.info
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1 month ago
56 minutes 27 seconds

AI for founders
Somatic leadership for founders: Owen Marcus on stress, presence, and performance

AI for Founders — Owen from Meld on Somatic Leadership, Founder Resilience, and Community

Guest: Owen Marcus, co-founder of Meld (Men’s Emotional Leadership Development)

Topic: Building embodied leadership for founders through somatics, nervous system training, and high-trust men’s groups.

Why listen: A field guide for high performers who’ve maxed out intellect and want scalable tools to reduce stress, improve relationships, and lead with presence.

Key Takeaways

  • Bottom-up leadership beats top-down willpower: Somatic awareness unlocks intuition, safety, and executive presence when thinking harder no longer works.
  • Retrain your baseline: Repeated body-based practices shift the nervous system from chronic stress (allostasis) to a calmer default, improving decision quality.
  • Community is the multiplier: Safe, consistent men’s groups accelerate growth, model vulnerability, and create durable accountability founders rarely have.
  • Virtual works (~80%): Online groups deliver most of the value when live isn’t feasible; depth still thrives in well-held containers.
  • Accountability with consent: Hold people to outcomes they choose; vulnerability and challenge rise together when agreements are explicit.
  • Mind your language: Therapy-speak can become an excuse or a weapon. Favor direct experience over labels.
  • AI as coach, not crutch: Meld’s early “solo coach” prototype uses AI to guide somatic reflection between sessions and reinforce behavioral change.

Outline & Frameworks

  1. Somatic Leadership Loop: Notice sensations → Name them → Normalize safety → Downregulate physiology → Choose aligned action.
  2. Communal Container Design: Clear agreements (confidentiality, optional participation) → Modeled check-ins → Competitive vulnerability → Integration to life and work.
  3. Founder Stress → Resilience Path: Over-indexed on intellect → Somatic awareness → Nervous system regulation → Secure attachment behaviors → Better leadership and relationships.
  4. 80/20 Delivery Model: Live work for depth; virtual for consistency and reach. Expect ~80% transfer when the container is tight.
  5. Accountability-with-Consent: Challenge in service of chosen goals, paired with vulnerability for sustainable behavior change.
  6. Ritual → Spontaneity Ladder: Build stabilizing rituals (meditation, training, check-ins) that open the door to authentic spontaneity.

Who This Is For

Founders, CEOs, and execs who feel overloaded, want sharper presence, better relationships, and a community that tells the truth.

Episode Resources

  • Meld: https://meld.community
  • Kitcaster (podcast guesting for founders): https://kitcaster.com
  • Stephen Porges / Polyvagal Theory: https://www.stephenporges.com
  • Somatic Experiencing (Peter Levine): https://traumahealing.org

Links: aiforfounders.co | ryanestes.info

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1 month ago
56 minutes 49 seconds

AI for founders
Cold email, LinkedIn, and the $2M lead gen playbook

Royan Nidea on Scaling to $100K Months with Setters Philippines

In this episode of AI for Founders, Ryan Estes sits down with Royan Nidea, founder of Setters Philippines, a consulting and lead generation firm that has scaled to millions in revenue by helping coaches, consultants, and B2B founders consistently land qualified calls and build thought leadership.

Royan shares how he generated $16 million from just 4,000 emails, the five-step process he uses to scale clients to $100K months, and why balancing automation with personalization is the key to sustainable growth. He opens up about the early challenges of building his company, the mistakes that shaped his playbook, and the systems he relies on today.

Whether you’re a founder, consultant, or B2B leader looking to create a predictable pipeline, this episode is packed with frameworks and insights you can apply immediately.

Key Takeaways

  • How Setters Philippines scaled to ~$2 million in revenue and serves global B2B clients.
  • The exact outreach process Royan uses to generate millions with cold email and LinkedIn.
  • Why “30 calls + 30 days of content” is the engine for growth and credibility.
  • The balance between personalization and automation in modern lead generation.
  • Lessons learned from early mistakes and the importance of building lean but effective teams.
  • The role of systems, technology, and virtual assistants in freeing founders to focus on growth.
  • How Royan thinks about ethics, long-term relationships, and sustainable scaling.

Frameworks Discussed

  1. 5-Step Scaling Process: Cold Email → LinkedIn Outreach → Appointment Setting → Content Systems → Sales Conversion
  2. 30/30 Rule: Book 30 calls and publish 30 days of content per month to build both pipeline and credibility.
  3. Personalization at Scale: Mixing automation tools with human touch to maximize ROI.
  4. Lean Operations Model: A small but specialized team driving $2M+ revenue.

Resources & Links

  • Setters Philippines
  • Royan Nidea on LinkedIn
  • Indian Business Times: How Virtual Assistants Can Help Businesses

For more founder-focused conversations, visit: AI for Founders | Ryan Estes

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1 month ago
46 minutes 23 seconds

AI for founders
Future of Payments: AI Agents, Micropayments, and Embedded Finance

Episode Summary

In this episode of AI for Founders, Ryan Estes sits down with Alfonso Gómez-Jordana Mañas, co-founder of Crossmint and former Google/WhatsApp product manager. Alfonso shares how he went from building “I am not a robot” CAPTCHA to building the rails for a programmable economy. They explore AI agents as financial actors, how micropayments could reshape the internet, and why stablecoins are doubling every few months.

This conversation is a roadmap for founders, builders, and investors who want to understand the intersection of AI, blockchain, and the future of online trust.


Key Takeaways

  • Identity and Trust: From CAPTCHA to Crossmint, Alfonso’s career has focused on distinguishing humans from machines and securing digital interactions.
  • Programmable Economy: Stablecoins, wallets, and NFTs are the building blocks for embedded finance and AI agent commerce.
  • AI Agents as Financial Actors: Agents will soon research, negotiate, and transact on behalf of humans, creating both opportunities and new risk models.
  • Micropayments as Defense: Instead of fighting bots with detection, shift to economic incentives—introducing costs for interactions reduces abuse.
  • Democratizing Creativity: AI tools replace mediums like watercolor or code-writing, but taste and curation remain uniquely human.
  • Regulatory Landscape: New clarity around stablecoins and blockchain is accelerating adoption, but frameworks for equity and tokenized investment are still needed.
  • Habit Formation Idea: Alfonso suggests programmable contracts that automatically deduct money if commitments (like gym workouts) aren’t met—an example of blockchain-enabled accountability.
  • Vision for 2030: A synergistic world where humans set intent and agents execute, reshaping commerce, communication, and creativity.


Frameworks Discussed

  • Intent + Verification Model: Humans express intent, AI agents execute, humans verify results.
  • Economic Incentive Framework for Spam/Abuse: Reduce abuse not by detection but by shifting ROI and adding micropayment costs.
  • Programmable Economy Stack:
    • Stablecoins = money
    • Wallets = storage
    • NFTs = ownership
    • APIs = infrastructure
  • Programmable Habits: Smart contracts enforcing behavior through economic penalties or rewards.


Resources and Links

  • Crossmint
  • Alfonso on Twitter/X
  • Cloudflare & Coinbase micropayments (X402)
  • AI for Founders newsletter
  • Ryan Estes
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1 month ago
51 minutes 28 seconds

AI for founders
Before You Shake Hands, read this. Elle George on partnership alignment

Elle George on Founder Alignment, Partnerships, and Hard-Won Lessons


Episode Summary

Founder and author Elle George breaks down her new book “Before You Shake Hands”, a practical system for assessing alignment before partnerships, co-founder agreements, or investor deals. She shares hard lessons from a two-decade legal saga, the exact questions she now asks, and how to structure conflict protocols before momentum blinds everyone.


Who this episode is for

Founders, CEOs, operators, first-time investors, and anyone considering a co-founder or strategic partner who wants fewer surprises and fewer trips to court.


What you will learn

  • How to run an alignment check before you sign anything
  • The five domains to vet in every partnership
  • How to document conflict protocols up front
  • Investor questions that expose goals and timelines early
  • Why spiritual discipline and daily routines support better decisions


Key Takeaways

  • Alignment beats traction. Momentum masks risk. Stop and align goals, values, roles, legal, money, and exit plans before papering anything.
  • Ask first-principle questions. Why invest. What is the five-year end state. How will conflicts resolve. Who decides at ties.
  • Document the downside. Agree on “what if we hate each other,” capital calls, buy-sell terms, and tie-breaker rules before you commit.
  • Battle scars matter. Do not avoid hard histories. Ask how a partner handled legal, credit, or operational failures and what changed.
  • Culture shows in small signals. Hiring prompt she loves, “What work bores you.” It is a precision question for role fit.
  • Discipline scales intuition. Routine, reflection, and written agreements turn gut feel into repeatable decisions.


Frameworks from the Episode

1) The Alignment Framework — Five Domains

  • Values and trust
  • Roles and responsibilities
  • Legal and documentation
  • Financials and capital calls
  • Exit strategies and scenarios

2) Partnership Diligence Checklist

  • Why do you want to work with me or invest in this business
  • What are your goals for the company and the timeline to reach them
  • What is your exit preference and under what conditions
  • Describe your biggest business challenge and how you handled it
  • Any prior legal or financial issues, what you learned, what changed
  • Conflict plan, decision rights, tie-breaker mechanism
  • Buy-sell mechanics, valuation method, funding obligations

3) Conflict Protocol Up Front

  • Define disagreement thresholds that trigger a decision process
  • Name who has final call on specific domains
  • Establish a written tie-breaker and escalation ladder
  • Pre-agree on mediation or arbitration path and venue

4) Investor Fit Questions

  • End-state in five years and expected liquidity path
  • Capital intensity expectations after initial check
  • Governance, reporting, and operating cadence preferences
  • Support offered beyond money and how success is measured

5) Founder Operating Rituals

  • Morning affirmations and meditation for clear decision-making
  • Weekly reflection on assumptions and alignment drift
  • “No gossip” rule to protect culture and focus

Resources and Links

  • Founder Challenge by Kitcaster: https://media.kitcaster.com/founder-challenge
  • AI for Founders: https://aiforfounders.co
  • Ryan Estes: https://ryanestes.info
Show more...
1 month ago
55 minutes 9 seconds

AI for founders
Building virtual power plants with AI and blockchain
Solmag.ai and the Future of Peer-to-Peer Energy | AI for Founders

Solmag.ai and the Future of Peer-to-Peer Energy

In this episode of AI for Founders, Ryan Estes interviews Alex, founder of Solmag.ai, a company building virtual power plants that enable peer-to-peer solar energy trading. From his journey after a first startup exit to a mission of helping humanity reach Type I civilization on the Kardashev scale, Alex shares how Solmag is tackling energy distribution, grid optimization, and decentralized networks.

Listeners will learn how communities can share surplus solar power, what regulatory shifts are coming in Europe, how AI is used to price and route electricity, and why Solmag could redefine the economics of clean energy. This is a must-listen for founders, climate-tech investors, real estate developers, EV infrastructure operators, and anyone passionate about the future of decentralized energy.

Key Takeaways

  • From Exit to Energy: Alex’s search for meaning after a startup exit led to a mission to transform global energy.
  • Solmag.ai’s Vision: Virtual power plants connecting solar households.
  • Peer-to-Peer Trading: Local energy sharing cuts costs and boosts prosumer revenue.
  • Hardware + Cloud: Gateway device and cloud aggregation enable real-time trading.
  • Regulatory Landscape: Europe’s 2026 legislation will open new opportunities.
  • AI in Energy: Routing algorithms optimize distribution like Waze for electricity.
  • Scalability Challenge: Expanding from 100 homes to entire cities.
  • Investment Path: Pre-seed round in motion, aiming for Series B growth.
  • Future Outlook: 25M solar rooftops today, projected 100M by 2030.
  • Big Picture: Humanity must grow energy harnessing 8,700x to reach Type I civilization.

Frameworks Outlined

Kardashev Energy Framework

  • Current: Type 0.73
  • Type I: Harness all Earth’s energy
  • Future: Compact, space-based, or nuclear solutions

Virtual Power Plant Model

  • Gateway devices installed in homes
  • Cloud aggregation of energy data
  • Peer-to-peer transactions within communities
  • Scaling network effects for efficiency

Energy Pricing Logic

  • Utilities: 30–40% margins
  • Solmag: 10% transaction fee
  • Users retain ~85% of market value
  • Local energy should cost less than long-distance grid supply

Resources

  • Solmag.ai
  • Solmag Whitepaper
  • Kardashev Scale Background
  • AI for Founders
  • Ryan Estes
Show more...
1 month ago
49 minutes 56 seconds

AI for founders
Secure First, Scale Fast: ProArch CTO/CISO on AI That Won’t Break Compliance

AI for Founders — Ben Wilcox (ProArch)


Episode Summary

CTO/CISO Ben Wilcox breaks down how to build a secure foundation before layering on AI and data. We cover compliance early vs. late, agentic AI realities, Microsoft Copilot in the enterprise, change management for AI adoption, and leadership lessons from Ben’s background as a racing instructor.


Who This Is For

Founders, CTOs, CISOs, product leaders, and operators at startups to mid-market enterprises who want fast AI adoption without compliance blowups.


Topics & Keywords

AI security, compliance, data privacy, PII, PCI, SOC 2, Microsoft Copilot, agentic AI, change management, enterprise AI adoption, Microsoft ecosystem, security foundation, data governance, quality engineering, automation, remote work.


Key Takeaways

  • Security first, then AI: Bake in privacy, identity, and compliance controls early. Retrofitting compliance later is expensive and slow.
  • Know your customer’s rules: Map target markets to regulatory obligations (PII, PCI, HIPAA/PHI, SEC/FIN). Expect security questionnaires even as an early startup.
  • Use third-party rails for risk: Offload card data (PCI) to providers like Stripe to reduce scope and audit burden.
  • Agentic AI is early but useful: Frameworks shift quickly; move now with pragmatic pilots rather than waiting for “perfect.”
  • Quality doesn’t stop at ship: LLM versions drift. Add continuous quality loops to ensure outputs remain accurate as models change.
  • Adoption is a change-management problem: Treat rollout as an org-wide initiative with training, policy, and measurement.
  • Personal AI stack that works: Microsoft Copilot (Office/Teams), ChatGPT, Claude.
  • Leadership lesson from racing: “Eyes up.” In business: keep eyes on AI, security, and data.
  • Microsoft alignment matters: Pairing security + data + AI in one ecosystem compresses cost and time-to-value.


Frameworks from the Episode

1) Secure-Data-AI Ladder

  1. Secure Foundation: Identity, least-privilege, logging, audit, encryption, segmentation.
  2. Data Layer: Catalogs, lineage, quality SLAs, access controls, privacy by design.
  3. AI Layer: Use cases with measurable accuracy targets, human-in-the-loop, monitoring.

2) Compliance-Early Checklist (Startup Edition)

  • Identify regulated data: PII/PHI/PCI/Financial.
  • Map jurisdictions: state privacy laws + breach notification obligations.
  • Offload payments (PCI) to third-party.
  • Centralize logs and audits from day one.
  • Prep for security questionnaires: architecture, data flows, vendor list, DPA, incident process.

3) Agent Lifecycle & Quality Loop

  • Define business outcome + acceptable accuracy.
  • Ship a constrained pilot with guardrails.
  • Instrument telemetry, prompt/response logs, feedback.
  • Regression tests on model or framework updates.
  • Retrain/tune or adjust prompts; repeat.

4) AI Change-Management Playbook

  • Executive mandate and narrative.
  • Everyone uses AI as a personal assistant first.
  • Role-specific enablement, office hours, champions.
  • Policies for sensitive data, identity, and auditing agent actions.
  • Adoption KPIs: usage, time saved, outcome quality.

Outline

  • Ben’s dual role (CTO/CISO) and ProArch focus
  • Why security before AI
  • Compliance landmines: PII, PCI, state privacy laws
  • Off-the-shelf rails to reduce risk
  • Agentic AI today: reality vs. hype
  • Continuous quality for shifting LLM baselines
  • Copilot + ChatGPT + Claude in practice
  • Microsoft ecosystem advantages
  • Leadership via racing: “eyes up”
  • Change management for enterprise AI
  • Remote culture and durable growth

Resources & Links

  • ProArch
  • Microsoft Copilot for Microsoft 365
  • OpenAI ChatGPT
  • Anthropic Claude
  • n8n
  • Zapier
  • Stripe
  • Waymo

aiforfounders.co | ryanestes.info

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1 month ago
56 minutes 19 seconds

AI for founders
Welcome to AI for Founders. I'm Ryan Estes. Here, you'll find tip-of-the-spear conversations with leaders in business, innovation, and health. Each episode will be packed with valuable insights as we learn how these remarkable individuals built moats around their companies to shield them from a future of uncertainty. You'll hear incredible stories of overcoming obstacles, learn about their daily routines that drive success, and discover the life-changing decisions that gave them the lift to reach new heights. Get ready to be informed, inspired, and uplifted.