HeyJaredLearn with Arjan
Hey! So nice to see you here! ❤️😊🙏So the idea is to try to share what I know, it may not be accurate but it is what I think. I would love to hear if things are otherwise.
- Indexed episodes, last 90 days
- 10
- Latest publication
- Sep 20, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 6, 2026
Latest episodes
Giving Models Hands: Mastering AI Tool Calling and Actions (opens the original)
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In this episode, we explore how Large Language Models move beyond pure text responses by acquiring "hands"—the ability to interact with external APIs and execute code through Function Calling. We break down the exact contract between an LLM and a server, detailing how tools are declared using JSON Schemas, requested by the model, executed in server code, and synthesized back into natural language answers. We also examine real-world tool implementation, including calculator functions and turning
Beyond the Chatbot: Building Autonomous AI Agents & Sequential Workflows (opens the original)
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In this episode, we explore the paradigm shift from single-prompt reactive chatbots to goal-oriented, multi-step AI agents. We unpack the core cognitive loop—Perceive, Plan, Act, Observe, and Repeat—and see how agents autonomously break down complex goals into sequential tasks. Discover how to implement chained LLM workflows in Node, manage state and memory accumulation, and apply crucial safety controls like Human-in-the-Loop (HITL) and artifact verification to stop compounding errors. Whether
AI-Assisted Software Engineering: Using AI as a Development Partner, Not a Replacement (opens the original)
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How do you stay in control of your codebase when AI can write your code for you? In this episode, we explore the profound shift in the software engineering paradigm—moving from being a simple "code typist" to acting as an architect and director . While AI tools are incredible at eliminating boilerplate and pattern-matching training data, they do not build "mental models" or understand the deep, architectural "why" behind your system.We dive into the dangerous trap of "vibe coding" and blindly cl
Context Engineering: Designing the data that feeds the AI (opens the original)
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Context Engineering: Designing the data that feeds the AI is a deep-dive podcast series exploring the architectural control plane that powers modern agentic AI systems. Moving far beyond basic prompt engineering, this show untangles how data engineers and AI developers design, structure, and govern the runtime payloads that models consume to execute reliable, real-world workflows.If this podcast were created directly from your notebook's sources, its episode or series description would highlight
Prompting & Structured Outputs: Controlling LLM behavior and enforcing data schemas (opens the original)
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In this episode of Prompting & Structured Outputs, we explore how the artificial intelligence industry transitioned from the "Wild West" of raw prompt engineering—where developers simply crossed their fingers and hoped for valid JSON—to the modern paradigm of mathematical constraints. We trace the evolution of structured data generation, analyzing why early solutions like standard JSON Mode only guaranteed syntactically valid outputs but still permitted hallucinated schemas and missing keys. Dis
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