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Artwork for The AI Practitioner Podcast

The AI Practitioner Podcast

by Lina Faik
Langgraph
Artificial Intelligence
Research Assistant Framework
Agentops
Checkpointing
AI Bot Traffic
Prompt Engineering
Google ADK
Semantic Caching
Software Engineering
Large Language Models
Skillopt
Causal Discovery
Mlflow
Mlops
Reducers
Time Travel In AI
Observability
Interrupts In AI
Long-Term Memory

Real-world AI, explained simply — with code, use cases, and zero fluff. aipractitioner.substack.com

PublishesTwice monthlyEpisodes16Foundeda year ago
Number of ListenersCategories
EducationTechnology

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Artwork for The AI Practitioner Podcast

Latest Episodes

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Multi-agent systems become valuable when they can reason and coordinate, but they be... more

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Multi-agent systems become powerful when they can adapt, but they become production-... more

Prefer reading instead? The full article is available here. The podcast is also available on Spotify and Apple Podcasts. Subscribe to keep up with the latest drops.

Agent frameworks promise to make AI systems easier to build. But the hard part isn’t... more

Prefer reading instead? The full article is available here. The podcast is also available on Spotify and Apple Podcasts. Subscribe to keep up with the latest drops.

LLMs excel at individual tasks. But most valuable work isn’t a single task, it’s a c... more

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Lina Feich
Host of The AI Practitioner Podcast
Lina Faik
Host of The AI Practitioner Podcast

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PODCAST — Claude Dynamic Workflows: Scaling Complex Work Through Orchestration
Q: What should I see before I run a workflow to ensure I'm not spending money on a bad plan?
You'll get an approval card that shows planned phases, warns about token usage, and a raw script view so you can read the actual JavaScript before you say go, ensuring you understand the plan and costs.
PODCAST — Claude Dynamic Workflows: Scaling Complex Work Through Orchestration
Q: How do you kick off a dynamic workflow, and how do you decide when to use it?
Use the word workflow in the prompt or enable ultra code mode to let Claude decide when a task warrants a workflow; start small and scale by using the six patterns and inspecting the generated script before running it.
PODCAST — LLMs in Causal Discovery: A Deep Dive into Constraint-Based Algorithms
Q: Where do LLMs come in?
LLMs provide structured input for unresolved edges, offering actions and justifications, but they are not relied upon in isolation; they are part of a human-in-the-loop process with statistical checks.
PODCAST — LLMs in Causal Discovery: A Deep Dive into Constraint-Based Algorithms
Q: Okay, so how do you fix it?
Use a combination of hard constraints, temporal ordering, and, where ambiguity remains, an LLM layer that is grounded with rich context to guide edge orientation.
PODCAST — LLMs in Causal Discovery: A Deep Dive into Constraint-Based Algorithms
Q: So what's on the table today?
We're examining constraint-based causal discovery and how to integrate LLMs with traditional algorithms to handle unresolved edges and incorporate domain knowledge.

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Frequently Asked Questions About The AI Practitioner Podcast

What is The AI Practitioner Podcast about and what kind of topics does it cover?

The discussions center on practical AI tooling, scalable architectures, and real-world applications of large language models and agent-based systems. Across episodes, topics cover score-based and constraint-based causal discovery, integrating LLMs for guidance in data-driven workflows, building modular AI toolchains (Claude Skills, Skill.md), and operational frameworks for monitoring and debugging autonomous agents. There's a strong emphasis on production-readiness: memory for AI agents, memory management and caching strategies, memory pipelines, and robust deployment patterns, with concrete datasets (like Adult Census Income) and hands-on workflows. Listeners likely gain actionable guidance for implementing AI-powered products, designing m... more

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1. Hidden Brain

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The AI Practitioner Podcast launched a year ago and published 16 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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