HeyJaredThe AI Practitioner Podcast
Real-world AI, explained simply — with code, use cases, and zero fluff. aipractitioner.substack.com
- Indexed episodes, last 90 days
- 4
- Latest publication
- Sep 9, 2026
- Audience
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- Earliest in this view
- Jul 10, 2026
Latest episodes
PODCAST — Inside TabFM: How In-Context Learning Enables Prediction on Unseen Tables (opens the original)
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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. Most tabular machine learning workflows start the same way: clean the data, engineer features, tune hyperparameters, and train a new model from scratch. Google Research’s TabFM proposes a very different approach: treat the dataset itself as context and make predictions in a single forward pass, without task-specific training. In th
PODCAST — LLM Cost Prediction: From Single Prompts to Agentic Systems (opens the original)
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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. LLM costs are easy to calculate after execution, but estimating them before a prompt or agent actually runs is a much harder problem. In this episode, the focus is on predicting LLM and agent costs before execution , from estimating output length for a single model call to reasoning about the much more variable execution paths of A
PODCAST — Evaluating Google ADK Agents: From Execution Traces to Regression Tests (opens the original)
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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. Building agents that take real-world actions is impressive, but ensuring they continue to behave correctly as they evolve is a much harder challenge. Manual reviews of execution traces and subjective “vibe checks” quickly become a development bottleneck. In this fourth episode of the Google ADK series, the focus moves from deployme
PODCAST — Deploying Google ADK Agents: From Local Script to a Managed Cloud Runtime (opens the original)
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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. Multi-agent systems become valuable when they can reason and coordinate, but they become even more valuable when they are production-ready and can run reliably as a service. In this third episode of the Google ADK series, the focus moves beyond agent design and orchestration to deployment. Using the same multi-agent writing pipelin
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