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Vector databases can be an important component for building reliable AI agents and scalable semantic search applications. In this episode, Arjun Patel from Pinecone breaks down how to optimize your RAG pipeline, choose the right embedding models (sparse vs. dense), and implement effective chunking strategies for better data retrieval. We also explore the new Pinecone plugin for Claude Code, demonstrating how to build a recommendation system and chat with your documents using Pinecone Assistant without writing complex code.

https://www.pinecone.io/

https://www.linkedin.com/in/arjunkirtipatel/

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00:00:00 - Intro

00:01:11 - What Vector Databases Unlock

00:04:40 - Optimal Chunking Strategies for RAG

00:09:07 - How Embedding Models Work

00:17:25 - Improving Search with Re-ranking

00:26:52 - SQL vs Vector Database Architecture

00:35:48 - Claude Code & Pinecone Assistant Demo

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Unlock the power of AI fine-tuning for image and video models with Greg Schoeninger, CEO of Oxen.ai. In this episode, we explore how to move beyond simple prompt engineering to training custom open-source models for as little as $1. Discover the technical strategies for building high-quality datasets, the trade-offs between LoRAs and full fine-tunes, and how to achieve consistent characters and styles in generative video.

We dive into real-world examples, including how to generate massive product catalogs for a fraction of the cost of enterprise APIs and the story behind the viral "Isometric NYC" project built with Claude Code. Greg breaks down the entire AI lifecycle—from data curation and labeling with Vision Language Models (VLMs) like Qwen and Gemini to deploying efficient, specialized models that outperform general-purpose giants. Whether you are looking to optimize GPU costs, automate video workflows, or build your own AI tools, this conversation provides the blueprint for scaling your AI capabilities.

Links from the episode:

Oxen AI: https://www.oxen.ai/

Fine Tuning Fridays: https://luma.com/oxen

Isometric NYC Project: https://cannoneyed.com/projects/isometric-nyc

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https://x.com/gregschoeninger

00:00:00 - Intro

00:01:47 - When to Switch from Prompt Engineering to Fine-Tuning

00:11:05 - How to Build a Dataset for AI Fine-Tuning

00:21:52 - LoRA vs. Full Fine-Tuning Explained

00:27:53 - Case Study: Fine-Tuned Qwen 3 VL vs. Google Gemini

00:36:33 - Case Study: Isometric NYC with Claude Code

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Unlock the ability to build AI tools without coding experience as Justin Borge joins Tool Use to demonstrate how he built Helios, a personal management system, using only LLMs like Gemini and Claude. Justin breaks down his transition from marketer to growth engineer, sharing his exact workflows for using JSON documentation to give AI a perfect memory of his business and goals. He reveals his unique "bullying" strategy for debugging code using persona-based prompts and explains how he created a human-in-the-loop system to safely edit local files without hallucinations. This conversation covers everything from writing your first Python script to mastering meta-prompting for maximum productivity.

https://www.linkedin.com/in/justinborge/

https://justinborge.com

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00:00:00 - Intro

00:03:49 - Top AI Tools & JSON Workflows

00:10:06 - Transitioning from Marketing to Engineering

00:12:23 - How to Debug Code Without Coding Knowledge

00:13:56 - Persona Prompting & "Bullying" LLMs

00:18:09 - Live Demo: Helios AI Management System

00:31:29 - How to Start Building AI Tools Today

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Discover the power of the Ralph Wiggum Loop with Ryan Carson as we explore the future of AI coding agents, autonomous workflows, and building one-person companies. In this episode, we break down how to implement Jeff Huntley’s simplified bash script loop using tools like Claude Code and Amp to ship features faster than ever. Ryan shares his tactical advice on creating high-quality PRDs, defining clear acceptance criteria for agent browser testing, and moving beyond human-in-the-loop development. We also dive into advanced AI engineering strategies, including self-healing systems, MCP servers like Sentry and Fizzy, and how to use LLMs to automate business operations through CRON job insights and email marketing drips. Whether you are an AI engineer or a founder, learn how to stop writing syntax and start orchestrating a fleet of agents to amplify your delivery speed and creative joy.

Follow Ryan's Work:

Untangle: https://www.untangle-us.com/

Ralph Loop Repo: https://github.com/snarktank/ralph

Ryan on X: https://x.com/ryancarson

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00:00:00 - Intro

00:01:17 - How the Ralph Wiggum Loop Works

00:02:46 - Fresh Context Windows vs. Context Rot

00:12:15 - Deterministic Harnessing and Agent Hooks

00:17:59 - Agent Browser Testing & Acceptance Criteria

00:28:13 - Automating Business and Marketing Loops

00:39:09 - PR Review Bots and AI Engineering Workflows

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Tool Use is a weekly conversation with the top AI experts.

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Claude Code is evolving from a terminal-based developer tool into the Everything Agent that manages your entire life. In this episode, Eric Buess returns to show us how he built a hands-free, voice-controlled AI system that handles everything from school emails and calendar scheduling to monitoring family text messages. We dive deep into advanced Claude Code strategies, including how to use the hook system to intercept model prompts and the Ralph Wickham loop to enable truly autonomous task completion. Eric explains why he moved away from static claude.md files in favor of programmatic hooks that steer the model with surgical precision. We also explore the power of adversarial sub-agents that fact-check AI claims and the Titus wake word system that lets him command his terminal from a car or Meta Ray-Ban glasses. Whether you are a developer looking to maximize the Anthropic Agent SDK or a productivity enthusiast wanting to reclaim your time, this masterclass in agentic workflows will change how you think about AI automation.

Keep up with Eric: https://ericbuess.ai

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00:00:00 - Intro

00:02:20 - The Claude Code Hook System & Vertical Stack

00:03:08 - Why Agentic Hooks Matter for Automation

00:11:58 - Replacing claude.md with JSON Rules & Hooks

00:16:43 - Multi-Agent Workflows & Adversarial Validation

00:29:58 - Autonomous Task Loops & Self-Referential Injection

00:41:00 - Hands-Free AI: Voice-Controlled Claude Code

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Sukh Saini, an exited founder and the creator of Engyne, joins Tool Use to break down the essential strategies for AI product distribution and personal branding. With a track record of 38 products, Sukh shares how he transitioned from a self-proclaimed horrible employee to a successful entrepreneur by mastering the business loop of building, selling, and scaling. This episode covers the vital shift from managing multiple low-revenue apps to focusing on exponential growth through high-conviction projects like Retail, which he sold after finding a unique distribution edge within the Stripe marketplace.

Learn why building in public is a massive advantage for establishing trust and why marketplaces like Canva, Stripe, and the ChatGPT store are the next big frontiers for indie developers. Sukh also details his practical framework for validating demand through industry research and hypothesis-driven customer calls, ensuring you solve high-value problems before writing a single line of code. Whether you are interested in B2B SaaS, AI app stores, or building a thought leadership brand on LinkedIn, this conversation provides a tactical playbook for any builder looking to win in the AI era.

Engyne: https://engyne.ai/

Sukh's LinkedIn: https://www.linkedin.com/in/sssaini/

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00:00:00 - Intro

00:01:21 - How to build a winning product loop

00:04:26 - Mastering product distribution and the Stripe marketplace

00:08:12 - Why building a collection of small apps is a mistake

00:14:56 - Validating SaaS demand before writing code

00:21:56 - Tactical framework for finding customer pain points

00:27:59 - The competitive advantage of building in public

00:42:27 - Unlocking distribution through the ChatGPT app store

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Master your AI career in 2026 with this comprehensive guide on how to get a job in AI as a developer or non-technical professional. Mike Bird, AI and Engineering Lead at BoxOne Ventures, breaks down his personal journey from software developer to AI leader and shares insider secrets on the modern hiring process. Learn why traditional resumes are failing in the age of AI screeners and why you should embrace building in public, networking at AI Tinkerers events, and creating obnoxious resumes to stand out from thousands of bot-driven applications. Whether you are looking to become an AI engineer, a specialized AI consultant, or the AI champion at your current company, this episode provides actionable strategies on leveraging tools like Claude Code, Cursor, and more to proof-of-concept your way into the fastest-growing industry in human history. We dive deep into the technical skills required for 2026, including managing fleets of AI agents and mastering security audits, while also addressing career pivots for those in their 40s or 50s.

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00:00:00 - Intro

00:01:02 - Career Pivot Strategy: From Dev to AI Lead

00:03:35 - Beat AI Screeners: The Case for the "Obnoxious" Resume

00:10:43 - 2026 AI Engineer Interview: Technical Screens & Vibe Checks

00:16:08 - AI Consulting vs Productizing: Knowledge Arbitrage Tips

00:20:08 - Build in Public: How to Increase Your AI Luck Surface Area

00:25:30 - Non-Technical Strategy: Becoming an AI Champion

00:30:32 - Realistically how long it takes to transition into AI

00:36:26 - Is it too late to learn AI if you are 40+ or 50+?

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Tool Use is a weekly conversation with the top AI experts.

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In this 2025 year-end wrap-up, we dive deep into the massive shifts in the AI landscape, from the surprise release of GPT-5.2 to the rise of open source models like DeepSeek. Mike Bird and Richardson Dackam reflect on a year defined by accelerating iteration cycles, the growing energy bottleneck for data centers, and the emergence of reasoning models that have changed how we approach complex tasks. We also look ahead to 2026, predicting the evolution of browser agents, the integration of AI in physical robotics, and why the next frontier of artificial general intelligence might actually be found in biological simulation. Whether you are interested in fine-tuning open models, the future of AI-generated content, or how programmable payments through crypto will enable the agentic future, this episode covers the essential trends every AI builder needs to know.

Check out Richardson's work

https://www.nshipyard.com/

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https://x.com/RichardsonDx

00:00:00 - Intro

00:00:26 - Frontier Model Race: Gemini 3 vs GPT-5.2

00:07:27 - Open Source AI and the DeepSeek Market Shock

00:12:06 - The Future of AI Interfacing: Voice & Multimodality

00:30:39 - Browser Agents and Agentic Tools for 2026

00:41:58 - Physical AI: The Humanoid Robot Revolution

00:48:20 - The Next Frontier: Why Biology is the Bottleneck for AGI

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Tool Use is a weekly conversation with the top AI experts.