She lived through Y2K, sold for Microsoft, and bet early on the cloud. Now Carmen Aviles is building AI agents on a Mac mini, and she says this wave is bigger than all of them.

Carmen Aviles has spent more than 40 years in tech. Her path runs from shipping e-learning on CDs across Latin America to SAP implementations during the Y2K panic, Microsoft's partner ecosystem, and one of South Florida's first Office 365 practices. Today she's the founder of Aviles AI and helps small and midsize businesses adopt AI without breaking what already works.

Hosts Samantha Viola Wilson and Brittany George ask her what Y2K can teach us about the AI rush and whether AI will really take jobs in the next five years. They also get into how CEOs can get their teams to adopt it: role by role, with incentives, starting from the top. Carmen gives an honest account of building a six-agent real estate marketing system, including the cron job that burned $135 in one day. She explains how Jake Van Clief's Interpretable Context Methodology (ICM) brought her cost down to about $10 per run.

IN THIS EPISODE:

- How is the AI rush like Y2K, and how is it different?

- Will AI replace jobs in the next 5 years?

- How do you get employees to adopt AI? (role-based rollout)

- Is Microsoft behind in AI? (Copilot, Copilot Studio, GitHub)

- How do you cut AI agent token costs?

- Cloud vs. local AI models: who owns your data?

- Using NotebookLM as a personal AI tutor

CHAPTERS

00:00 Meet Carmen Aviles ("Abuela")

00:53 Shipping e-learning on CDs across Latin America

02:23 Y2K, SAP, and the panic that looks like today's AI rush

05:16 Getting hired at Microsoft (via cassette voicemail)

07:11 Betting early on Office 365 and the cloud

09:40 First AI "wow": 2-hour research cut to 30 minutes

10:37 The OpenClaw obsession and a 6-agent marketing system

12:13 Y2K vs. AI: what's the same, what's different

13:40 Early adopters, proof-of-concept people, and skeptics

16:26 Will AI take jobs? Carmen's 5-year outlook

18:32 Kids, critical thinking, and AI in education

20:35 NotebookLM as a personal AI tutor

23:22 How CEOs get teams to adopt AI

25:28 Free Microsoft AI courses and the partner opportunity

27:55 AI adoption has to start at the top

29:30 Is Microsoft behind in AI? Copilot, models, GitHub

34:32 Copilot Studio inside Teams: worth $30 a month?

37:16 Token costs and the $135 cron job mistake

40:26 Building vs. monetizing: the honest update

43:09 ICM: the folders-and-files method that cut costs

46:53 Protecting your IP when vibe coding

48:07 Obsidian, Skool, and knowledge graphs

50:47 Cloud vs. local models: who owns your data?

54:44 AI glasses and DIY robots

58:13 Personal AI: ChatGPT for life, Claude for business

1:00:44 How to reach Carmen

RESOURCES MENTIONED

- OpenClaw

- Interpretable Context Methodology by Jake Van Clief: https://arxiv.org/abs/2603.16021

- Clief Notes community on Skool: https://www.skool.com/cliefnotes

- Google NotebookLM

- Microsoft Copilot Studio

- GitHub

- Obsidian

- Brilliant Labs Halo AI glasses

CONNECT WITH CARMEN AVILES

Business Optimization & Adoption Consultant | Founder, Aviles AI

🌐 https://avilesai.com

💼 LinkedIn: https://www.linkedin.com/in/carmenavilesaiconsulting/

📸 Instagram: @caviles812

✉️ carmen@avilesai.com

🏡 Buying or selling residential or commercial real estate in South Florida? Carmen is a licensed realtor. Reach out by email.

What if the hardest part of AI at work is not the model, butgetting a clear prompt and a repeatable process before you touch the fancytools?

In this episode of Intelligence Resources, Samantha ViolaWilson and Brittany George sit down with Gabor Kis, Business Systems Analyst in Change Management at DTCC, to walk how a longtime Xerox data architect reskilled into AI, won an internal hackathon on AWS Kiro, and now teachesbusiness builders to treat English as their coding language.

Drawing on his experience spanning Xerox Business Solutionsdata architecture and change and release work at DTCC, Gabor shares the path from Google AI Studio interview prep into a six-week AI hackathon, why his teambet on Kiro, and how prompting plus named beginner-to-agentic stages (Aha, Mirage, AI Vampire, Synergy) beat tool-chasing. He tells the Grafana storybehind an app named Grace that took a week of work to about 45 seconds and helped reclaim roughly 69 weeks.

The conversation covers AWS Kiro specs versus vibe coding,free credits and cost math versus heavy Claude Code bills, Copilot as a prompt workshop, CAB GPT prioritizing hundreds of weekly changes by blast radius, and a personal close: use AI to identify your attachment style and improve.

Connect with Gabor: https://www.linkedin.com/in/gaborkis

Intelligence Resources drops every Tuesday.

CHAPTERS

0:00 Welcome to Intelligence Resources with Samantha ViolaWilson and Brittany George

0:11 Brittany welcomes Gabor through daughter Grace

0:39 From Xerox data architect to DTCC change management

1:37 Google AI Studio interview prep and landing the role

2:05 Betting the hackathon on AWS Kiro

2:55 DTCC scale and why change management cannot fail

3:52 Winning the AI hackathon and starting to teach

5:29 English as the coding language for business builders

5:55 The aha moment and the Grafana project named Grace

7:22 How 45 seconds times 69 spreadsheets saved ~69 weeks

8:05 Hesitant colleagues and the AI adoption gradient

8:48 What is the most important AI skill?

9:00 Samantha and Brittany on prompting, process, andpatience

10:26 Prompting as communication, and why the tool mattersless at first

11:24 Cheat sheet: make the model write a 10-out-of-10prompt

13:02 Probabilistic answers, not perfect deterministic ones

13:56 Coursera tracks and the Vanderbilt prompting course

16:00 Stages: Aha, Mirage, AI Vampire, Synergy

17:41 Nine-agent software factory and Sonny the orchestrator

19:13 OpenClaw experiment, 8.5M tokens, and pulling the plug

21:25 What is AWS Kiro, and why enterprise stacks pickAmazon and Microsoft

23:14 Spec development versus vibe coding

24:37 Free credits, pricing tiers, and small-business costmath

27:09 Copilot aversion, and using Copilot as a promptworkshop

29:58 Change management: build it, they will come, teachteachers

32:20 CAB GPT hackathon deep dive: risk and blast radius

34:52 AI security fears for PHI, SSNs, and financial data

36:17 Post-quantum computing and harvest-now decrypt-later

38:17 What quantum computing means (the maze analogy)

40:04 When quantum and AI meet

42:31 Human in the loop, presence, and empathy

45:05 Always-on work, motherhood, and tech resentment

46:51 New stage: slave to the machine

49:51 Personal AI use: attachment style prompt

51:06 Close, LinkedIn CTA, and Tuesday goodbye

#AI #ChatGPT #AWS #Kiro #PromptEngineering#ArtificialIntelligence #FutureOfWork #ChangeManagement

What happens when AI stops being an experiment and starts becoming part of your everyday life?

In Episode 10 of Intelligence Resources, Samantha Viola Wilson and Brittany George sit down for a candid co-host catch-up about the AI tools and agents they are actually using—and the lessons they learned from the ones that failed.

They share how a missed backup led to lost websites and a major rethink of where their data lives, why complicated agent setups were not always worth the effort, and how newer tools are making automation feel more like working with a capable employee.

From sales prospecting, CRM workflows, benefits guides, RFPs, and podcast production to grocery shopping, meal planning, travel itineraries, meeting follow-ups, and launching an Etsy store, this episode is packed with real examples of AI doing practical work.

They also discuss the rising cost of AI subscriptions, the importance of keeping a human in the loop, how to turn repeatable workflows into reusable skills, and why small businesses may have a major advantage when they can move faster than larger organizations.

If you are trying to figure out which AI tools are genuinely useful—and how to move from experimenting to executing—this episode is for you.

Tell us in the comments: What task would you trust an AI agent to handle for you?

Subscribe for more candid conversations about using AI in business and everyday life, and visit intelligenceresources.io for resources and free prompts.

CHAPTERS

00:00 Just the two of us
00:44 Losing two websites and the backup lesson
05:24 Choosing the right AI for each job
08:11 What we really spend on AI
09:10 Why complicated AI agents kept breaking
12:06 Setting up a working agent in minutes
15:06 Meal planning and the 30-avocado mistake
18:45 Launching 55 Etsy products with AI
20:20 The AI travel agent that saved a birthday trip
24:52 Cleaning email and tracking subscriptions
26:58 Building a CFO agent
28:37 Turning an Excel budget into a custom app
31:10 A task manager built around real work
34:51 Map the workflow before building the bot
36:54 Turning repeatable work into reusable skills
40:50 The voice tool Brittany recommends most
41:27 Building an enrollment dashboard in 30 minutes
44:30 The small-business advantage with AI
45:58 From meeting transcripts to automatic follow-ups
46:42 Building an AI agent for RFPs
49:02 AI support for parenting and homeschooling
50:28 Automating the podcast workflow
53:11 Should Intelligence Resources host a live event?
53:44 Final thoughts and listener feedback

#IntelligenceResources #AIAgents #ArtificialIntelligence #BusinessAutomation #AIForBusiness #SmallBusinessAI #WorkflowAutomation #GenerativeAI #FutureOfWork #Productivity #Entrepreneurship #AITools #DigitalTransformation #WomenInBusiness

How do we know what to trust in a world filled with misinformation, outdated headlines, hidden incentives, and AI-generated content?

In this episode of Intelligence Resources, Samantha Viola Wilson and Brittany George sit down with Aki, founder and CEO of Credible AI, to explore how artificial intelligence can help people evaluate information, identify bias, and make better-informed decisions.

Drawing on his experience at companies including Microsoft, Twitter, and Uber, Aki shares the inspiration behind Credible AI and its mission to build a credibility layer for the internet. The conversation covers misinformation, critical thinking, political bias in AI models, transparency in healthcare research, conflicts of interest, and the growing challenge of distinguishing credible information from persuasive content.

Aki also introduces Skim, a platform designed to help users quickly understand videos and articles, follow developing narratives, and surface the information that matters most to them or their businesses.

The conversation closes with a look at how AI could reshape social media, knowledge sharing, business intelligence, and even everyday routines like planning events and tracking fitness goals.

Visit https://skim.plus to learn more.

CHAPTERS

00:00 Introduction
00:55 From Princeton to Microsoft, Twitter, and Uber
02:47 Success, luck, privilege, and the fourth cookie
06:04 The story behind Credible AI
09:27 Could Credible AI exist without artificial intelligence?
11:04 Bias, nuance, and rebuilding critical thinking
13:07 The danger of outdated information
14:38 Aligning business incentives with users
17:13 AI-generated content and online fact-checking
19:34 Does it matter whether content was created by AI?
22:27 Building a credibility layer for the internet
23:18 Political bias within AI models
27:10 Credibility, funding, and bias in healthcare research
29:16 Why conflicts of interest should be disclosed upfront
32:31 The risks of relying on a single data point
33:19 Patient experiences, peptides, and medical research
36:43 Fake reviews and the loss of trust online
37:14 Can AI help restore critical thinking?
40:00 The difference between Credible AI and Skim
42:54 How Skim could support businesses and professional teams
47:45 AI advertising and potential conflicts of interest
49:18 How AI could transform platforms like X and Reddit
52:18 How Aki uses AI in his personal life
53:30 Using AI to plan and track fitness goals
56:09 Where to find Aki and Skim

#CredibleAI #AIForBusiness #MediaLiteracy #CriticalThinking #ArtificialIntelligence

What happens when you combine a business owner’s instincts, a veteran CFO’s judgment, and AI’s analytical power?

Phil Nahajewski, partner at Florida CFO Group and creator of Philnancial OS, joins Brittany George to explain his “three-brain” approach to financial decision-making.

Phil shares how AI helped a $100 million cement company evaluate a major expansion decision in less than 24 hours—work that might previously have required a consultant, $20,000, and 45 days.

They also explore why AI should be treated as a first-draft engine rather than a final decision-maker, which finance jobs are most vulnerable to automation, and why experienced human judgment remains indispensable.

In this episode, you’ll discover:

• How to triangulate business decisions using three brains
• Why Phil moved his business workflows from ChatGPT to Claude
• How he turned 36 years of CFO experience into 63 AI-powered decision rules
• Why business owners need financial insight every Monday morning
• Which finance roles AI may replace—and which it cannot
• How mentorship can preserve expertise in an AI-first workplace
• Why your values may be one of the most important things you give your AI

Intelligence Resources features people using AI inside real businesses today—not merely predicting what it might do someday.

CHAPTERS

00:00 Meet Phil Nahajewski
01:01 The three-brain approach
02:15 A $20,000 decision made in a day
04:14 What each brain contributes
06:04 Why Phil moved to Claude
08:00 The fastest way to learn AI
10:25 Building a second brain
12:15 When AI gets it wrong
13:10 Can AI replace the CFO?
14:24 Dueling AI assistants
16:23 Which jobs are most at risk?
17:20 The Monday morning philosophy
18:45 Building Philnancial OS
21:34 Turning experience into 63 rules
23:36 Mentoring the next CFO generation
26:55 How law and accounting will change
28:21 AI: cost cutter or capacity builder?
30:24 What AI should never decide alone
32:38 How finance teams will shrink
33:28 Phil’s advice for business owners
33:53 Using AI for personal growth
36:08 Where to connect with Phil

CONNECT WITH PHIL

Visit Florida CFO Group or connect with Phil Nahajewski on LinkedIn to learn more about his fractional CFO services and Philnancial OS.

#AIForBusiness #ArtificialIntelligence #FinancialStrategy #CFO #BusinessAI #FutureOfFinance #AIAutomation #FractionalCFO #BusinessPodcast #FutureOfWork

AI is transforming marketing, hiring, content creation, sales, and the agency business model. But is it actually saving us time, or just helping us create more work?

In this episode of Intelligence Resources, Samantha Viola Wilson and Brittany George sit down with Marialuisa Curran, founder and CEO of mezmRISE, to discuss what using AI inside a real growth strategy agency actually looks like.

Marialuisa shares how AI has changed the way she builds teams, creates content, analyzes data, supports sales, and delivers value to clients. She also explains why AI cannot replace strategic thinking, what separates a valuable employee from a task taker, and where automated outreach crosses the line into inauthentic AI slop.

In this conversation:

• Why problem solvers are becoming more valuable than task takers
• How AI has changed agency hiring and team structure
• When AI saves time and when it creates more work
• Why better prompts require real experience and judgment
• How to make AI generated content sound more human
• What makes an AI sales pitch effective or painfully obvious
• Why agencies must rethink hourly billing
• How to protect sensitive client information
• Why AI should support strategy, not replace it
• Creative ways to use AI at work, at home, and in your community

What do you think? Is AI making you more productive, or is it quietly adding more to your workload? Share your experience or questions in the comments.

If this conversation helped you, like the episode, subscribe, and share it with someone navigating AI at work.

#ArtificialIntelligence #AIForBusiness #FutureOfWork #MarketingStrategy #AIMarketing #Entrepreneurship #BusinessGrowth #ContentMarketing #SalesStrategy #AgencyLife #Leadership #IntelligenceResources

Emily Adams left the Amish community at 17 after growing up without electricity. Today, she works across tech, manufacturing, AI readiness, founder development, and innovation.

In this episode of Intelligence Resources, Samantha Viola Wilson and Brittany George talk with Emily about her path from learning computers for the first time to building companies, supporting founders, organizing Tampa Bay Tech Week, and helping businesses understand what it actually takes to implement AI.

We discuss AI tools, vibe coding, founder mistakes, pitch decks, token usage, clean data, manufacturing gaps, and why AI only works when the operational foundation is strong.

Chapters:

00:00 Introduction
02:36 From the Amish community to tech
03:41 Emily’s first experience with a cell phone and computer
04:23 Feeling behind and becoming a high performer
06:00 Breaking into cybersecurity
07:42 Building Tampa Bay Tech Week
09:35 What people actually want to learn about AI
11:04 Emily’s first experience using ChatGPT
12:48 Building a human design platform
14:36 Vibe coding with Claude and when developers are still needed
16:41 Helping non-technical founders build tech companies
18:53 Funding, investors, and protecting founders
21:01 Founder mistakes, pitch decks, and market validation
23:04 AI slop and why vague pitch decks fail
24:21 How AI saves Emily 10 to 20 hours per week
27:44 The downside of AI overuse and burnout
30:15 Favorite AI tools: Claude, ChatGPT, Otter, Opus, and more
34:44 Bad AI product ideas and token usage problems
36:34 Using AI to evaluate business proposals
40:03 What Emily is building next
41:06 Manufacturing, AI readiness, and the data problem
43:26 Will AI replace manufacturing workers?
47:04 Using AI for YouTube and personal productivity
47:49 Where to find Emily Adams

#ArtificialIntelligence #AIForBusiness #WomenInTech #StartupFounder #AIReadiness #FutureOfWork #BusinessLeadership #ManufacturingInnovation #VibeCoding #ClaudeAI #ChatGPT #IntelligenceResources

Can you really build an app with AI without being a developer?

In this episode of Intelligence Resources, Samantha Viola Wilson and Brittany George sit down with insurance entrepreneur Drew Tyler to discuss how AI is changing app development, website creation, insurance, legal work, and entrepreneurship.

Drew shares how he went from working in insurance to building websites, AI agents, and health-tech applications using tools such as Claude, Claude Code, Lovable, Base44, ChatGPT, and Gemini. He also explains how an app that might traditionally cost $75,000 to begin developing can now be prototyped with AI tools costing around $50 per month.

But creating a polished prototype is not the same as launching a secure, production-ready platform.

The conversation explores:

• What vibe coding actually is
• How non-developers can turn an idea into a working prototype
• Where developers are still essential
• The risks of outsourcing development internationally
• How to protect intellectual property and proprietary business ideas
• Why AI agents perform better when assigned one focused responsibility
• How AI is changing insurance, legal research, websites, and administrative work
• Why every AI-generated spreadsheet, document, and recommendation still needs human review
• How Drew and Brittany are using AI to build Well Funded
• Whether AI will replace junior employees, paralegals, developers, or entire departments

This episode offers an honest look at both the opportunities and limitations of building a business with AI.

Watch the full episode and subscribe to Intelligence Resources for practical conversations about using AI to build, operate, and grow a business.

#ArtificialIntelligence #VibeCoding #AIAgents #AppDevelopment #FutureOfWork