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