Most people are still typing questions into a chatbot. Brian Albert is building software while he sleeps.

Brian went from running a digital marketing agency with a team of content creators to replacing that whole function with AI the month ChatGPT arrived, and growing a YouTube following of 25,000 by simply giving away what he figured out. In this conversation we get tactical: the email workflow he runs for about $30 a month, why he builds his own tools instead of renting someone else's wrapper, what "disposable software" means, when to use a project versus a gem, and the one thing he thinks actually lasts. Playfulness.

Key takeaways:

• Why Brian replaced content creators with AI in January 2023
• The email-triage workflow anyone can build for ~$30/month
• Build vs. buy: the case for owning your own automation
• "Disposable software": agents that build throwaway tools on demand
• Projects vs. gems vs. custom GPTs, and when each one fits
• How to get unstuck by asking a different model
• The skill Brian says will still matter in six months

Connect with Brian Albert: https://www.linkedin.com/in/brian-albert-executive/

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email the show: [email protected]

00:00 You can do anything with AI

00:47 Only 0.04% automate with AI

02:46 How Brian feels about this moment

04:07 Firing the content team in 2023

05:04 Six friends, then 25,000 followers

06:17 Giving everything away for free

07:39 A first agentic email workflow

09:42 Is it actually hard to build?

12:39 The real monthly cost, about $30

16:54 Build it yourself vs. buy the product

19:48 Add the next step to the automation

22:11 Was Brian always technical?

22:58 Starting with a PRD

25:29 A voice-driven book-writing app

26:02 Getting unstuck by asking another model

27:56 Disposable software, explained

30:45 Building apps vs. a whole eng team

30:54 Cowork and scheduled agents

36:01 Is this feeding the AI slop problem?

38:54 Unique perspective, value, adjust

41:22 Spotting AI writing, the do-not-use list

43:01 One thing to go do right now

45:07 Projects vs. gems vs. custom GPTs

47:25 The skill worth investing in, playfulness

50:36 Wrap up

What if AI could make your employees feel more valued, not less?

Jason Stover, Executive Vice President at SSA Group and the builder behind Scout — SSA's internal AI platform — joins Sara and Dan to share how a people-first philosophy is driving one of the most thoughtful AI adoption strategies in the hospitality industry. From getting laid off teams through COVID, to discovering ChatGPT and not sleeping for weeks, to accidentally sending an AI-written email that almost got him flipped off by a colleague, Jason's story is equal parts honest, funny, and genuinely inspiring.

Key takeaways:

• Why the hospitality industry may be more AI-resistant than most — and why that's a strategic advantage
• How Scout was born, and what makes it different from generic AI tools
• The fight-flight-freeze response to AI adoption, and how to move your team past it
• Why AI adoption strategy starts with one question: "How does this impact me?"
• The email incident that changed how Jason thinks about AI communication forever
• How SSA is using behavioral psychology to personalize the AI experience for each employee
• What it really means to lead with empathy when rolling out new technology
• Why giving a long-tenured employee a four-day week might be the best ROI AI can deliver
• Jason's honest take on the future of work and the industries most at risk
• The number one piece of advice for any business leader who is still dancing around the AI topic

Connect with Jason Stover: https://www.linkedin.com/in/jason-stover-4b6b7a1b/

Follow Sara & Dan: Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email the show: [email protected]

00:00 Episode preview & intro

01:15 Jason's parallel path: people & tech

01:43 Digital scales & predictive analytics

03:11 How Jason stays curious about AI

03:51 The YouTube channels he follows

04:44 EVP blocking Fridays for AI discovery

04:54 Journey from dishwasher to VP at SSA

06:38 The pivot: stepping down to focus on AI

06:47 COVID, layoffs, and the ChatGPT moment

09:47 Why it's always about people, not just AI

10:21 Meet Scout — SSA's internal AI platform

10:56 Tank Stover: the persona that started it all

14:08 Early feedback: fight, flight, or freeze

15:33 How employees are actually using Scout

17:26 Building career paths with AI in hospitality

18:10 Building trust in AI tools with frontline staff

18:47 The million-dollar question: transparency

19:55 What most CIOs get wrong about rollout

20:46 Trips and falls along the way

20:57 The email incident that changed everything

24:17 Rethinking who to bring AI to first

26:05 Repurposing saved hours for human connection

27:14 AI helping us be more human

27:41 Tangible vs. soft ROI of AI investment

28:47 The four-day workweek conversation

31:59 How Scout connects siloed departments

33:21 Crystal ball: the future of SSA with AI

36:15 Demographics, retention & daily pay

39:10 Leading with empathy — advice for leaders

39:31 Stop freezing: come up with a strategy

40:39 What Jason admires about Anthropic & Claude

41:13 A united leadership team behind the vision

42:16 Advice for young people navigating AI

43:04 Behavioral Essentials & personalizing Scout

46:20 The data trust problem

46:40 Using AI to discover your own strengths

47:18 Where to find SSA & closing thoughts

47:41 Outro

What if you could build your company's next internal tool in a weekend, for $30?

Aaron Trockman is a partner manager at Glean who had zero formal coding experience — and then built PartnerSync, a fully functional partner automation platform used daily across his sales organization, in about 10 hours using AI tools. In this episode, Sara and Dan sit down with Aaron to unpack exactly how he did it, what tools he used, what it actually cost, and what it means for the future of work. Aaron's story is a clear signal: AI is democratizing product development, and professionals who embrace these tools will have a massive advantage.

Key Takeaways:

• Aaron built a working MVP for around $30 in AI credits using Base44, then migrated to Lovable + Supabase.
• His AI workflow: dump the problem into Glean → generate a prompt with Prompt Cowboy → build in Lovable → debug with Gemini/ChatGPT.
• The tool he built, PartnerSync, replaced a capability they were evaluating from Crossbeam at significant additional cost.
• Key principle: assess complexity and margin for error before committing — internal tools with ~5–10% error tolerance are ideal for vibe coding.
• AI is democratizing product development — a team of one can now ship what once required a team of five.
• The future of work isn't AI replacing jobs — it's people who use AI replacing people who don't.
• The platform play is shifting: companies are building custom internal tooling instead of buying bloated SaaS they only use 30–40% of.
• Prompting tips: assign AI a persona (researcher, UX engineer), tell it to forget its last approach, and switch tools when you hit a wall.
• Job security comes from making your team more effective — not just from being able to build.
• Aaron's one action for listeners: take your biggest problem right now and ask ChatGPT, Gemini, or Glean how to solve it. Just start.

Connect with Aaron Trockman: https://www.linkedin.com/in/aarontrockman/

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email the show: [email protected]

00:00 Intro & cold open

00:47 What is Glean? Sara's pitch

02:06 Aaron's role: partner manager

02:54 Building PartnerSync — the story

04:57 Replacing a $$$$ SaaS tool for $30

06:06 The AI workflow: start to finish

07:11 Prompt Cowboy & prompt engineering

07:52 Base44 vs Lovable — why he switched

08:57 What is throttling? Plain language

09:46 Total cost: under $100 to MVP

10:33 Sara's Lovable build attempt

12:13 When AI lies about APIs

12:50 AI = brilliant dev with ADHD

14:55 How to scope AI-built projects

16:25 ISVs, internal use & margin for error

16:54 How to push through roadblocks

17:57 Prompting as building a team of one

18:53 Three hours on a multi-model build

20:40 Job security in the AI era

21:46 AI democratizes product development

24:47 How AI changed Aaron's mindset

25:41 Someone using AI will take your job

26:24 What Aaron wants to build next

27:39 Scope: too big vs. your wheelhouse

29:56 The future of SaaS & the platform play

31:21 One action to take in 30 minutes

32:16 Outro

We're taking a short break to upgrade our equipment & set!

In this episode, Sara gives a brief tour of their home & recording spaces, highlighting the challenges they've faced and the changes they plan to make.

Subscribe so that you don't miss new episodes! Be back soon!!

AI is changing everything, from how we work to how we learn to how we take care of our families. But is it replacing jobs… or creating entirely new opportunities?

In this episode of Promptly Speaking, Sara and Dan sit down with Sreeveni Kancharla (“Sree”), CIO at SailPoint, to unpack what the AI revolution really means for leaders, employees, and the next generation entering the workforce.

Sree brings a rare, grounded perspective from the front lines of enterprise transformation, balancing innovation, governance, productivity, and humanity in a world where AI agents are becoming part of everyday work.

💡 Topics We Cover:

1. How AI is reshaping the workforce and where the real opportunities are
2. Why AI shouldn’t replace people, but amplify them
3. How leaders should think about productivity, governance, and strategy
4. Why junior employees still matter in an AI-driven world
5. How AI can support personal life decisions, learning, and creativity
6. The importance of human judgment, critical thinking, and boundaries
7. Why embracing AI is no longer optional, but blind trust is dangerous

⏱ Timestamps:

00:00 AI, Job Displacement, and Opportunity

00:43 Introducing Sree and Her Role as CIO

02:01 Why AI Is Different From Past Tech Revolutions

02:41 The Pressure on Leaders to Define AI Strategy

04:39 Junior Roles, Internships, and the Future Workforce

08:09 Why Human-in-the-Loop Still Matters

15:20 Using AI in Personal Life: Healthcare, Family, and Trust

18:20 AI as a Creative and Learning Tool

24:38 How AI Empowers the Next Generation

26:50 Rethinking Business Processes with AI Agents

31:51 Productivity, Strategic Thinking, and Leadership Time

36:49 Learning Habits, Curiosity, and Staying Relevant

39:08 Final Advice: How to Start Embracing AI Today

How to Find Sree:

LinkedIn: https://www.linkedin.com/in/sreeveni-kancharla/

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: [email protected]

Everyone's been talking about AI this year. Where does it move the needle? Where does it fall short?

In the final Promptly Speaking episode of 2025, Sara and Dan take a moment to reflect on what they've learned from their guests, and through their own experimentation with AI in life & work.

Now, more than ever, it's important that we stop and take a moment to think about where we're trying to go in this world of technology that's moving so fast.

⏱ Timestamps:

01:23 Embracing AI in Daily Life

04:07 The Power of Continuous Learning

04:36 Optimizing Business Processes with AI1

3:44 Real-World Applications of AI

16:38 Reflecting on the Future

22:34 Humanizing Technology

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: [email protected]

What if the biggest risk in AI adoption isn’t falling behind, but moving too fast without clarity?

In this episode of Promptly Speaking, Sara and Dan speak with Scott Barghaan, a longtime enterprise sales leader whose career spans EMC and Salesforce, and who now teaches future business leaders at the Kellogg School of Management. Scott unpacks how AI is actually reshaping the practice of sales, not through flashy tools or automated outreach, but through better preparation, deeper customer context, and higher expectations for judgment. He explains how executives are often pressured to adopt AI before clearly defining the problem they are trying to solve, and why AI delivers real value only when it is applied to concrete constraints around scale, cost, and margin rather than introduced as a solution in search of a use case. The conversation explores how buyers are showing up differently, how great sellers adapt without losing authenticity, and what practical, grounded AI adoption looks like for teams of any size.

💡 Topics We Cover:

- Why buyers now enter sales conversations later, more informed, and more skeptical

- Board-level pressure to adopt AI and how it shapes executive decision-making- Why starting with tools instead of problems leads to disappointment

- Using AI to prepare for better conversations, not replace sellers

- Customer context as the real advantage in modern sales

- Where AI genuinely helps sales teams today and where it can backfire

- The risk of AI-assisted communication sounding polished but hollow

- Buying committees, political capital, and why “helping buyers buy” matters more than ever

- How small teams can pilot AI, measure impact, and scale responsibly

- Teaching sales and leadership during a major technology shift

⏱ Timestamps:

00:00 Introduction to AI, sales, and executive pressure

01:04 Scott’s career journey from enterprise sales to academia

02:41 Advising AI startups and supporting non-profits

04:49 Customer-centric selling in the AI era

08:42 How the role of the salesperson is changing

11:16 Leveraging AI for research, preparation, and insight

25:28 Why buying is harder than selling

31:15 Convincing executives to embrace AI thoughtfully

33:02 Why this technology shift feels different

33:50 AI’s role in business transformation

34:29 Challenges and opportunities with AI adoption

35:21 What successful AI implementation actually looks like

36:42 Addressing fear, risk, and resistance around AI

41:03 Lessons from teaching at Kellogg

46:03 Final reflections and practical takeaways

How to Find Scott:

LinkedIn: https://www.linkedin.com/in/sbarghaan/

Kellogg: https://www.kellogg.northwestern.edu/academics-research/faculty/barghaan-scott/

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: [email protected]

In this episode of Promptly Speaking, Sara and Dan speak with Matt Crowson, a fellowship trained ear surgeon who has spent the last decade working at the intersection of clinical medicine, data, and artificial intelligence. Matt explains why diagnostic error is far more common than most patients realize, using ear infections as a powerful and personal case study. He shares how a machine learning model he co-developed at Mass General achieved roughly 95% accuracy in diagnosing pediatric ear infections, compared to the average human accuracy, which is closer to 60 to 70%, and why that gap matters for both everyday care and global health.

The conversation goes beyond diagnostics to focus on where AI is already making meaningful progress in healthcare today, particularly in reducing administrative burden through tools like ambient documentation and message triage. Together, they explore the barriers to AI adoption in healthcare, including privacy, liability, fragmented data systems, and regulation, as well as the growing role of clinicians in shaping AI products.

The episode closes with practical advice for patients on how generative AI can be used responsibly right now to better understand medical bills, insurance documents, and care options, while acknowledging the real tradeoffs around data privacy and trust.

💡 Topics Covered:

• Why humans are surprisingly bad at diagnosing common conditions
• How AI can reduce diagnostic variability without replacing clinicians
• Pediatric ear infections as a global health problem
• AI in low-resource and rural healthcare settings
• Administrative burnout and “pajama time” for clinicians
• Ambient scribes and inbox triage as early AI wins
• Payers vs providers and how healthcare actually works
• Accountability and liability when AI is involved in care
• Why healthcare AI moves slower than other industries
• How patients can use generative AI today without over-trusting it

⏱ Timestamps:

00:00 Introduction to ear infections and AI in healthcare

00:44 Meet Matt Crowson: from ENT surgeon to AI advocate

01:36 Payers vs providers and how the healthcare system functions

02:39 AI and administrative burden in clinical work

04:55 Privacy, safety, and regulatory barriers to AI adoption

09:37 What a Chief Medical Officer does in an AI company

13:37 AI in rural healthcare and pediatric ear infection case study

26:35 Accountability and liability in AI-assisted care

26:51 The scalpel analogy and human responsibility

29:57 AI’s potential impact on healthcare costs

30:41 Generative AI and patient empowerment

36:10 What the future of AI in healthcare may realistically look like

36:40 How AI tools are implemented inside hospitals

38:35 Real-world AI deployments and auditing41:14 Vendor and healthcare system partnerships

42:01 Practical advice for patients using generative AI

45:07 Final reflections

How to Find Matt:

LinkedIn: https://www.linkedin.com/in/matthewgcrowson

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: ⁠[email protected]⁠

In this episode of Promptly Speaking, Sara and Dan sit down with Neil Shepherd — a Silicon Valley engineer, entrepreneur, and former leader at PayPal, Scale AI, Cohere, and Play.ai — for a direct, deeply informed look at the AI disruption already unfolding.

Neil breaks down why this wave of technology is unlike any before it, why white-collar roles are more exposed than people think, and why the next five to seven years will reshape entire industries. He dives into how AI is transforming marketing, legal work, medicine, and manufacturing in very different ways — from one-person teams running $60M campaigns to diagnostic models outperforming specialists — and what that means for your career trajectory.

He also shares his latest venture, The American Dream Index, a data-driven tool that quantifies what it truly costs to build a stable, middle-class life in America — and why so many people feel like they’re falling behind.

💡 You’ll learn:

• Why AI is moving faster than any disruption in modern history
• Which roles are most vulnerable over the next few years
• The real skill divide: entrepreneurial thinkers vs handle-turners
• How marketing, law, medicine, and manufacturing are being reshaped by ai
• What separates people who adapt from those who get left behind
• Why curiosity, experimentation, and communication are the new power skills
• How Neil is using AI to map the American dream — and why it’s drifting out of reach for many

🧠 Whether you’re an operator, a leader, or just trying to stay ahead, this conversation offers clear-eyed insight into a future that’s arriving much faster than most people expect.

⏱ Timestamps:

00:00 Disruptive Technology: Why This Wave Is Different

00:19 The American Dream and Shifting Goalposts

00:37 Meet Neil Shepherd

02:05 AI’s Acceleration and Job Disruption

06:27 Marketing’s Massive Transformation

08:58 Career Advice in the Age of AI

15:39 AI in Medicine

19:34 The Future of Robotics and Manufacturing

22:52 Entrepreneurs vs Handle-Turners

23:27 What Job Security Really Looks Like Now

24:11 Adapting to Technological Change

27:04 Introducing the American Dream Index

29:05 Meaning, Purpose, and Mid-Career Reinvention

33:32 Curiosity, Experimentation, and Adaptability

38:37 The Communication Skill That Now Sets You Apart

43:36 Final Thoughts and What to Do Next

How to Find Neil:

LinkedIn: https://www.linkedin.com/in/neilshep/

American Dream Index: www.americandreamindex.com

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: ⁠[email protected]⁠

What happens to creativity when anyone can generate “good enough” writing in seconds?

And how do you keep your voice — your taste — when machines want to average everything out?

In this episode, Sara and Dan sit down with Simone Stolzoff — author of The Good Enough Job and the upcoming How to Not Know — to talk about the real skills we need in an age of nonstop change: uncertainty tolerance, identity beyond work, and the confidence to experiment even when everything feels foggy.

But we go deeper:

• What does originality look like when AI can draft anything?
• How do writers protect the parts of their work that only come from human judgment?
• What’s worth delegating to AI — and what should never leave your hands?

Simone breaks down how he uses AI to push his ideas, not replace them, why first drafts should still come from humans, and why taste, discernment, and creative rejection might be the most important skills of the next decade.

💡 You’ll learn:

• How writing is actually evolving in a world of large models
• Why taste is the new competitive edge
• How to use AI as a developmental editor without flattening your voice
• The danger of tying your identity to work in a volatile economy
• Why uncertainty isn’t a threat — it’s what gives life meaning
• The mindset shift that reduces anxiety and increases agency
• How to anchor yourself as everything around you changes

🔥 If you’re navigating AI, career uncertainty, creative work, or the pressure to “figure it all out,” this episode will give you clarity — and momentum.

⏱ Timestamps:

00:00 Introduction: The AI Awakening

00:21 Navigating Uncertainty in a Polycrisis World

00:52 A Confession and Reconnecting with an Old Friend

02:15 The Good Enough Job: Rethinking Work and Identity

04:10 Generative AI: Transforming the Creative Process

11:10 How to Not Know: Embracing Uncertainty

20:07 The Future of Work: Autonomy and Adaptation

24:39 Segmenters vs. Integrators: Work-Life Boundaries

25:32 The Role of Generative AI in Work Autonomy

26:29 Transitioning to Self-Employment

28:10 Balancing Self-Employment: Pros and Cons

31:45 Building and Finding Community as an Entrepreneur

36:33 Embracing Uncertainty in Work and Life

39:43 Action Bias: Moving Forward with Generative AI

How to Find Simone:

Website: https://www.simonestolzoff.com/

LinkedIn: https://www.linkedin.com/in/simone-stolzoff-5a16b648/

X: https://x.com/SimoneStolzoff

Instagram: https://www.instagram.com/thepizza_bagel/

TED Talk: https://youtu.be/cfKFbh8LPvU?si=yXlz4FzgHK3OPNH7

Follow Sara & Dan:

Sara: https://www.linkedin.com/in/saralynneroberts/

Dan: https://www.linkedin.com/in/danroberts27/

Email: [email protected]