ragTech

In this episode of ragTech, software engineers Saloni, Natasha and Victoria explain how they use agentic coding tools in their jobs, and how it's different from 'vibecoding.'✨Follow us on our socials!- Website: https://ragtechdev.com/- Instagram: https://www.instagram.com/ragtechdev/- Spotify: https://open.spotify.com/show/1KfM9JTWsDQ5QoMYEh489d- More Links: https://linktr.ee/ragtechdev0:00 Hook0:52 Intro1:02 Meet the Hosts2:29 Defining Vibe Coding6:20 Saloni's Agentic Workflow10:04 Standardizing Atomic Modular Code13:59 The 383-Commit PR Story17:10 The Designer Prototype Gap18:41 Staying In Control21:36 Overcoming Fear of Replacement25:34 The Productivity Illusion31:22 Wrapping Up32:31 Outro

Natasha, Saloni, and Victoria dig into how AI is reshaping the way we learn: cognitive atrophy, AI literacy, and what it means to raise kids in an AI world. Do you think schools should teach AI?✨Follow us on our socials!- Website: https://ragtechdev.com/- Instagram: https://www.instagram.com/ragtechdev/- Spotify: https://open.spotify.com/show/1KfM9JTWsDQ5QoMYEh489d- More Links: https://linktr.ee/ragtechdev

Loop engineering; Compound engineering; Context engineering; Harness engineering... It feels like there's a new AI buzzword every week! But are these actually new concepts, or just marketing spin on things engineers and users of coding agents have always done?In this episode of ragTech, Natasha, Saloni, and Victoria break down the latest wave of AI engineering jargon flooding social media, asking the REAL question: who benefits when we keep renaming the same ideas?We cover:🔁 Loop Engineering: designing feedback loops so an AI agent can test and refine its own output📈 Compound Engineering: building workflows where agents accumulate and reuse knowledge across runs🛡️ Harness Engineering: the guardrails that keep AI agents safely contained🧠 Context Engineering: curating exactly what info an agent needs to perform well🚀 Forward Deploy Engineers: why this role commands a premium (hint: it's not just technical skill)Why gatekeeping terminology can diminish people's confidence — and how to talk about these concepts without making others feel behind!Whether you're a seasoned engineer or just starting to explore AI tooling, this conversation is a reminder: most of these "new" ideas are just familiar patterns wearing new names. Don't let the vocabulary intimidate you; chances are, you're already doing it!

As three techies who know more about AI than the typical person, we're often asked the question by friends around us if AI is a bubble... and we've hesitated to give a straight answer until now. We break down this topic not from a "should I buy the stock" angle, but from the perspective of people who work in tech and watch this thing unfold from the inside every day.We define what an economic bubble actually is (comparing it to previous bubbles like the housing crisis, dotcom collapse), look at exactly what promise AI companies are selling to get those trillion-dollar valuations, talk about why "artificial intelligence" is a branding choice and not just a descriptor, get into LLMs vs. world models and why leading researchers are already calling LLMs a dead end, and end up somewhere none of us expected — asking whether society is even structured to receive the value AGI would create.Chapters:0:00 Intro1:30 What is a Bubble?5:00 Bubbles in History (Housing Crisis + Dotcom)11:00 Is AI the Next Bubble?14:30 The Promise of AGI18:30 AI is a Branding Decision22:00 Measuring AI's ROI30:00 The Reality Gap40:00 AI and Human Society48:00 The Data Problem (Model Collapse)52:00 Final Thoughts✨Follow us on our socials!- Website: https://ragtechdev.com/- Instagram: https://www.instagram.com/ragtechdev/- Spotify: https://open.spotify.com/show/1KfM9JTWsDQ5QoMYEh489d- More Links: https://linktr.ee/ragtechdev

Is AI ethical? That's the question we're exploring in Episode 51 of RAG Tech. Prompted by Natasha's recent talk on responsible AI at the AI Collective, the three of us sat down to have an honest conversation about data privacy, creative rights, and what intentional AI use actually looks like in practice. We cover: • The Ghibli AI controversy: how OpenAI trained on Studio Ghibli's iconic hand-drawn art without consent or compensation, and why that's different from human artistic inspiration • Data privacy by default: your photos, videos, and emails are being used to train AI models unless you explicitly opt out (and yes, Gmail was sued for $400B+ over this) • The environmental cost of AI: did you know generating a single AI image uses roughly as much energy as charging a full iPhone? • Intentional AI: Natasha's framework for asking: what is the actual cost of using AI for this task, and is it worth it? • Why women's skepticism of AI • The call to action: sit in the uncomfortable space between championing AI and understanding its ethical costs ✨Follow us on our socials!- Website: https://ragtechdev.com/- Instagram: https://www.instagram.com/ragtechdev/- Spotify: https://open.spotify.com/show/1KfM9JTWsDQ5QoMYEh489d- More Links: https://linktr.ee/ragtechdev