Early Adoptr: Simplifying AI For Founders & Small Businesses

We talk a lot about keeping a human in the loop, but what does that actually mean in your day to day? You read the AI output, it looks right, you approve it, and you move on. But from late 2027 that might not be enough, because Article 14 of the EU AI Act comes into full enforcement.

So what does it take to be a good human in the loop? You almost certainly have the skills already, and this episode is about putting them to work.

In this week's episode, Jess and Kyle get into what human-in-the-loop AI looks like in practice, the four levels of oversight, the value of domain expertise and context expertise, the five-step framework for being a good human in the loop, and how HITL skills can future proof your career.

What You'll Learn

What human in the loop actually means
What Article 14 of the EU AI Act means for high-risk systems
The levels of human oversight
Domain expertise and context expertise
Judgement, context and accountability as career skills
A five-step framework for owning an AI decision
How much friction to build in, and where
When a recurring mistake is a system problem

Use these links for a discount on the tools we recommend (and it supports the pod!)

Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptr
Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr

Research:

https://www.linkedin.com/pulse/how-good-human-loophitl-ray-floyd-17znc/
https://www.itbrew.com/stories/2026/03/16/what-makes-a-good-human-in-the-loop
https://www.mimasolution.com/ai-act/article-14
https://www.kiteworks.com/regulatory-compliance/human-in-the-loop-ai-compliance/
https://www.datacamp.com/blog/human-in-the-loop-hitl
https://www.ibm.com/think/topics/human-in-the-loop

Timestamps:

00:00 Introduction and Weekly Updates
04:46 AI News of the Week: AI News: Article 50 of the EU AI Act Is Now Live
07:11 Why LinkedIn and Substack Are Labelling AI Content
09:07 Article 14: When Human Oversight Becomes a Legal Duty
09:50 Why Oversight Matters More When AI Takes Action
12:17 What Human in the Loop Actually Means
13:12 Levels of AI Oversight
17:59 The Role of Domain and Context Experts
20:45 What Domain Expertise Means for AI Oversight
25:22 Context Expertise: The Business Knowledge That Lives Only in Your Head
29:46 Why Compliance Risk Lands on You, Not the AI
32:31 Future-Proofing Your Career in the Age of AI
34:39 Judgment, Context, and Accountability in Decision-Making
41:34 The Framework for Becoming a Good Human in the Loop

Get in Touch
hello@earlyadoptr.ai
TikTok: @early_adoptr
Instagram: @early_adoptr
YouTube: @early_adoptr
LinkedIn: https://www.linkedin.com/company/early-adoptr/
www.earlyadoptr.ai

Note: The written and scripted content for this episode was created with the assistance of various AI models.
Get in touch with Early Adoptr: hello@earlyadoptr.ai

Follow Us on Socials & Resources:

IG: https://instagram.com/early_adoptr
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What if your AI ran entirely on a laptop you own, added nothing to your monthly bill, and never sent your data anywhere? That's local AI. It might sound too good to be true, but as token costs climb and concerns about data privacy grow, local AI and small language models could be the solution.

In this episode, Jess and Kyle get into what local AI actually is, why running smaller models on your own machine has become a real option, and where it fits for a non-technical business. They cover the difference between small language models and the big cloud tools, what open weight models change, the jobs local AI is best suited to, the hardware it takes to run one, and why a hybrid of local and cloud is the right answer for almost every small business rather than going all in on either.

MCP Episode:
Small Language Model Episode:
Enterprise Nation AI Agent Webinar

What You'll Learn:

What local AI actually means
How running a small language model on your own laptop keeps sensitive data off a third party's servers
The difference between a small language model and the large models
What "open weight" models are
What jobs local AI is good at
Considerations for the hardware needed to run local AI
What apps you can use to run local AI

Resources:

Small Language Models are the Future of Agentic AI
The Ultimate Guide to Local AI and AI Agents
What is Local AI: The Complete Guide to Running AI on Your Own Hardware
How to Build Local AI

LM Studio
Ollama
Osaurus

Timestamps:

00:00 Introduction and Weekly Updates
04:45 What Local AI Actually Means
07:45 Small Language Models Explained
13:55 What Open Weight Models Are and Why They Matter
13:55 Understanding Open Weight Models
17:31 The Rise of Local AI and Its Applications
27:25 Hardware Considerations for Local AI
33:17 Privacy, Control, and Cost in AI Usage
34:32 The Rising Cost of Tokens
37:45 Speed and Efficiency in AI Models
38:57 Control and Ownership of AI Models
41:02 Challenges of Running Local AI
44:24 Local AI and Agents
47:27 The Hybrid Approach to AI Solutions
48:11 Key Takeaways for Implementing Local AI
49:50 AI News of the Week

Get in Touch:

hello@earlyadoptr.ai
TikTok: @early_adoptr
Instagram: @early_adoptr
YouTube: @early_adoptr
LinkedIn: https://www.linkedin.com/company/early-adoptr/
www.earlyadoptr.ai
Get in touch with Early Adoptr: hello@earlyadoptr.ai

Follow Us on Socials & Resources:

IG: https://instagram.com/early_adoptr
TikTok: https://tiktok.com/@early_adoptr
YouTube: https://www.youtube.com/@early_adoptr
Substack: https://substack.com/@earlyadoptrpod
Hosted on Acast. See acast.com/privacy for more information.

Vibe coding can build you almost anything now. A customer database, a little internal tool, a whole CRM in an afternoon. But some of those things could land you in a world of GDPR pain, and one or two you should never build at all.

In this final episode of the vibe coding series, Jess and Kyle are joined again by Sean Bhardwaj to work out where the line sits for a non-technical founder. They get into why building has become the easy part while distribution (aka getting people to actually use what you make) is still the hard part. They cover what belongs in the never-vibe-code pile, how much time it really takes to learn this properly, and why the answer to whether you should comes down to what you are actually trying to do.

How to find Sean Bhardwaj:

https://breakthroughgrow.com/
https://www.linkedin.com/in/seanbhardwaj/

Vibe Coding Series:

Vibe Coding for Non-Technical Founders: https://www.earlyadoptr.ai/episodes/vibe-coding-for-non-technical-founders-tools-models-and-how-to-start
Why Your AI Keeps Forgetting You (w/ Rob Webster): https://www.earlyadoptr.ai/episodes/why-your-ai-keeps-forgetting-you-and-the-folder-that-fixes-it-w-rob-webster
Claude Code vs Cowork (w/ Sean Bhardwaj): https://www.earlyadoptr.ai/episodes/claude-code-vs-cowork-what-non-technical-founders-need-to-know-w-sean-bhardwaj
Claude Code Without the Code (w/ Sean Bhardwaj): https://www.earlyadoptr.ai/episodes/claude-code-without-the-code-a-non-developer-s-week-in-review-w-sean-bhardwaj
Agentic Loops: https://www.earlyadoptr.ai/episodes/agentic-loops-the-engine-behind-vibe-coding
Vibe Coding: What to Do After the App Is Built: https://www.earlyadoptr.ai/episodes/vibe-coding-what-to-do-after-the-app-is-built

What You'll Learn

Why the difficult part of building software has moved from writing the code to getting real people to actually use what you have made.
The security and data questions to ask before you build anything that holds customer details
What you should never vibe code
When an open-source tool makes more sense
How to learn vibe coding without clearing your calendar,

Use these links for a discount on the tools we recommend (and it supports the pod!)

Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptr
Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr

Timestamps:
00:43 Introduction
05:22 Wrapping the Vibe Coding Series
07:50 AI in the News: AI Models Break Out of a Sandbox and Hack Hugging Face
13:25 Welcome Back Sean: And We Ask the Big Question: Should You Vibe Code?
16:29 Why Building Is Easy Now and Distribution Is the Hard Part
21:38 The Security and Data Risk of Vibe Coding
24:33 Why Vibe Coding Still Needs Human Judgement
26:59 Open Source vs Vibe-Coded: The CRM Example
28:43 What You Should Never Vibe Code
29:59 Governance, AI Policy and When an Agent Goes Rogue
34:43 How to Learn Vibe Coding Without Clearing Your Calendar
40:34 Rolling AI Out Across a Whole Organisation
48:19 You're Not Behind: AI Hype, ROI and Adoption
53:45 Should Non-Technical Founders Just Stay in Cowork?
58:43 Building Is No Longer the Bottleneck, Distribution Is
01:00:56 Can Anyone Vibe Code? The Final Verdicts
01:04:12 Final Reflections on the Vibe Coding Series

Research:

https://www.wired.com/story/openai-models-escaped-containment-and-hacked-huggingface/
Jack Dorsey interview: https://www.youtube.com/watch?v=YTVSwOY19Qs
Get in touch with Early Adoptr: hello@earlyadoptr.ai

Follow Us on Socials & Resources:

IG: https://instagram.com/early_adoptr
TikTok: https://tiktok.com/@early_adoptr
YouTube: https://www.youtube.com/@early_adoptr
Substack: https://substack.com/@earlyadoptrpod
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So you've vibe coded an app....now what?

Vibe coding gives almost anyone the ability to build a working app in an afternoon. In fact, around 63% of people building this way right now have no coding background at all. But once that app is live, the job of keeping it secure, monitored, and running for real users is as hard as it has always been, and if you don't know what you're looking for, you can open yourself to all sorts of risk.

In this episode, Jess and Kyle cover what it actually takes to keep an AI-built app safe and running once it's in front of real users. They break down the concept of vibe slop, what type of security risks are common for vibe-coded apps, and the operational layer that sits between deploying an app and running it safely, including configuration, access control, monitoring, and dependencies. They also walk through a security checklist you can run before anyone else uses what you've built, and more importantly, when it's time to hand what you've built over to a professional.

What You'll Learn
What vibe slop is, and why most AI-built apps have it without their builders realising
Why AI-generated code carries a specific category of security risks
The operational layer between building something and running it safely, covering configuration, access control, monitoring, and dependencies
A practical five-step security checklist to run through before anyone else touches what you've built
How to tell when your app has outgrown what you can safely manage, and what that decision actually looks like in practice

Use these links for a discount on the tools we recommend (and it supports the pod!)

Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptr
Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr

Timestamps:
00:00 Intro
04:44 Why Building With AI Is the Easy Part
07:01 What Vibe Coding Actually Builds
09:32 Vibe Slop: Why AI-Generated Code Isn't Ready to Launch
12:24 Security Risks Vibe Coders Typically Miss
15:17 What Maintaining a Vibe-Coded App Actually Involves
16:17 How Real Users Actually Use a Vibe-Coded App
18:00 The Hidden Layers of App Development
20:59 Deployment vs Configuration: The Key Differences
23:45 Access Control: Who Can Actually See Your Users' Data
25:37 App Monitoring: How to Spot Problems in Your AI-Built App
28:51 Dependencies: The Third-Party Code Running Inside Your App
34:04 AI's Role in Development: Confidence vs Reality
37:53 The Five-Step Security Checklist for AI-Built Apps
40:33 Version Control and Rollbacks: How to Protect What You've Built
43:52 When to Call a Developer: The Signs Your App Has Outgrown You
47:07 Ongoing Maintenance: Keeping Your Vibe-Coded App Safe Over Time
49:29 Key Takeaways for Safe Development
53:37 Wrapping up for the Week
54:09 AI in the News: Apple vs OpenAI and Paying Twice for AI

RESEARCH:
https://charliehills.substack.com/?_bhlid=c1b7f9fda51baf0227c089624042aaa0e89b040f
https://www.wsj.com/tech/ai/vibe-coding-slop-ai-tools-e6a99394
What exactly is vibe coding? (MIT Technology Review)
https://www.wired.com/story/thousands-of-vibe-coded-apps-expose-corporate-and-personal-data-on-the-open-web/
https://www.wired.com/story/normie-vibe-code/
https://www.itbrew.com/stories/2026/04/21/so-your-employee-made-an-app-a-vibe-coding-checklist
https://www.kaspersky.co.uk/blog/safer-vibe-coding-2026/30306/
https://www.vybe.build/blog/vibe-coding-for-non-technical-founders
https://the-stack-overflow-podcast.simplecast.com/episodes/youve-vibe-coded-an-app-now-what
https://www.theguardian.com/technology/2026/jul/10/apple-sues-openai-trade-secrets
https://techcrunch.com/2026/07/13/satya-nadella-has-issued-a-shocking-warning-to-companies-using-ai/

Get in Touch
hello@earlyadoptr.ai
TikTok: @early_adoptr
Instagram: @early_adoptr
YouTube: @early_adoptr
LinkedIn: https://www.linkedin.com/company/early-adoptr/
www.earlyadoptr.ai
Get in touch with Early Adoptr: hello@earlyadoptr.ai

Follow Us on Socials & Resources:

IG: https://instagram.com/early_adoptr
TikTok: https://tiktok.com/@early_adoptr
YouTube: https://www.youtube.com/@early_adoptr
Substack: https://substack.com/@earlyadoptrpod
Hosted on Acast. See acast.com/privacy for more information.

Agentic loops are already running in your business. If you have given an AI tool a research question, walked away, and come back to a finished brief, you have used one. The same mechanism fires a payment reminder after checking whether an invoice has actually cleared, keeps Claude Code testing its own fix until the bug is gone, and sends meeting notes straight into your to-do list the moment a call ends.

In this episode, Jess and Kyle get into how an agentic loop actually runs, how it connects to AI agents and AI workflow automation more broadly, and what separates it from a basic automation. They cover the three types of loop, the compounding maths of how a loop can get expensive fast, and how to build in the right amount of human oversight without losing what makes loops useful in the first place.

This is also where the vibe coding series starts to pull together: everything covered so far, the tools, the project structures, the files and folders, has been setting up for this.

We also cover the launch of the ChatGPT 5.6 models.

Use these links for a discount on the tools we recommend (and it supports the pod!)

Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptr
Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr

Vibe Coding Series:
Claude Skills: https://www.earlyadoptr.ai/episodes/claude-skills-explained-how-to-stop-repeating-yourself-in-every-session
https://www.earlyadoptr.ai/episodes/claude-code-without-the-code-a-non-developer-s-week-in-review-w-sean-bhardwaj
https://www.earlyadoptr.ai/episodes/claude-code-vs-cowork-what-non-technical-founders-need-to-know-w-sean-bhardwaj
https://www.earlyadoptr.ai/episodes/why-your-ai-keeps-forgetting-you-and-the-folder-that-fixes-it-w-rob-webster
https://www.earlyadoptr.ai/episodes/vibe-coding-for-non-technical-founders-tools-models-and-how-to-start

What You'll Learn:
What an agentic loop actually is, how it connects to AI agents and AI workflow automation more broadly
How loops are from a basic prompt-and-response exchange or a standard automation
The three types of loop
The three things every loop needs to work
Why a vague goal compounds quickly
How to improve a loop over time
Why cost and overbuilding are the biggest risks
Where the human in the loop still sits

Timestamps:
00:50 Introduction and Personal Updates
07:36 What an Agentic Loop Is and Why It Powers Vibe Coding
11:01 The Three Things Every Loop Needs to Work
15:23 Scheduled, Event-Triggered, and Goal-Based: The Three Types of Loop
16:32 Loops vs Basic Automations
18:56 The Importance of Human In the Loop
20:43 Improving Your Loop Over Time
24:55 What loops look like in practice
30:52 What loops take off your plate
31:46 Where loops go wrong
36:46 The Importance of Oversight in Automation
37:43 Keeping Loops Simple and Effective
41:39 Practical Takeaways for Implementing Loops
45:11 News of the Week: ChatGPT 5.6 Models
47:05 What's next in the vibe coding series

Resources:
https://www.lennysnewsletter.com/p/how-i-ai-how-to-write-ai-agent-loops
https://haystack.deepset.ai/blog/context-engineering
https://code.claude.com/docs/en/agent-sdk/agent-loop
https://martinfowler.com/articles/exploring-gen-ai/humans-and-agents.html
https://blogs.oracle.com/developers/what-is-the-ai-agent-loop-the-core-architecture-behind-autonomous-ai-systems
https://arxiv.org/html/2607.01641v1
https://www.theverge.com/ai-artificial-intelligence/963464/openai-gpt-5-6-codex-chatgpt-work

Get in Touch
hello@earlyadoptr.ai
TikTok: @early_adoptr
Instagram: @early_adoptr
YouTube: @early_adoptr
LinkedIn: https://www.linkedin.com/company/early-adoptr/
www.earlyadoptr.ai
Get in touch with Early Adoptr: hello@earlyadoptr.ai

Follow Us on Socials & Resources:

IG: https://instagram.com/early_adoptr
TikTok: https://tiktok.com/@early_adoptr
YouTube: https://www.youtube.com/@early_adoptr
Substack: https://substack.com/@earlyadoptrpod
Hosted on Acast. See acast.com/privacy for more information.