{"podcast":{"title":"Data Engineering Podcast","slug":"data-engineering-podcast","podcast_index_feed_id":403671,"rss_url":"https://serve.podhome.fm/rss/1c0357c0-6aba-5766-a2d5-2090d8dab6bc","website_url":"https://www.dataengineeringpodcast.com","image_url":"https://assets.podhome.fm/f6ff0caa-931b-4c08-bfdd-08dc7f5cd336/638557928872209534cover.jpg","author":"Tobias Macey","episode_count":510,"summary":"This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.","last_synced_at":null,"page_url":"https://stenobird.com/podcast/data-engineering-podcast"},"episode":{"title":"Beyond Prompts: Practical Paths to Self‑Improving AI","slug":"beyond-prompts-practical-paths-to-self-improving-ai","published_at":"2026-03-16T01:50:52+00:00","page_url":"https://stenobird.com/podcast/data-engineering-podcast/beyond-prompts-practical-paths-to-self-improving-ai","show_page_url":"https://stenobird.com/podcast/data-engineering-podcast","url":"https://www.dataengineeringpodcast.com/self-improving-ai-practical-strategies-episode-505","audio_url":"https://op3.dev/e/dts.podtrac.com/redirect.mp3/serve.podhome.fm/episode/f6ff0caa-931b-4c08-bfdd-08dc7f5cd336/639092222286896116ea4fb885-653c-45df-bfbd-3e9a171a99b6.mp3","summary":"Building production-grade AI requires moving beyond simple prompting toward agentic systems with intelligent memory layers. Raj Shukla explains how to architect feedback loops and domain-specific knowledge graphs to create self-improving, reliable enterprise agents.","meta_description":"Learn how to build self-improving AI systems using agentic architectures, memory layers, and domain-specific knowledge graphs for enterprise reliability.","key_points":["Main idea: True AI scalability comes from building around the model with data ingestion, sensors, and action layers rather than just tuning prompts","Practical takeaway: Use intelligent memory layers—like markdown files and filesystem primitives—to allow agents to accumulate context without retraining","Failure mode: Model version brittleness can cause havoc in enterprise systems when API updates change expected behaviors or deprecate versions","Practical takeaway: Implement domain knowledge graphs to provide the necessary semantics and context that foundation models lack","Main idea: The future of enterprise AI lies in companies owning their own reasoning and memory layers to avoid dependency on model providers"],"chapters":[{"start_ms":60000,"title":"Introduction to Agentic Systems","summary":"Raj Shukla introduces the concept of vertical AI and the mission of building autonomous enterprises through specialized agents."},{"start_ms":330000,"title":"Defining the Environment","summary":"A discussion on how human feedback and environmental constraints create the necessary conditions for model improvement."},{"start_ms":620000,"title":"Dynamic Context and Improvement","summary":"How selecting specific examples and dynamic inputs can significantly boost model performance in complex tasks."},{"start_ms":890000,"title":"Mitigating Hallucinations with Tools","summary":"Using tool usage and structured execution to prevent LLM hallucinations during complex calculations."},{"start_ms":1170000,"title":"The Evolution of Sub-agents","summary":"The transition from simple search to advanced agentic workflows involving autonomous code-writing sub-agents."},{"start_ms":1450000,"title":"Achieving Enterprise Reliability","summary":"Strategies for staged rollouts and building confidence in autonomous systems within regulated industries."},{"start_ms":1730000,"title":"Protecting IP and Domain Knowledge","summary":"How to leverage domain knowledge graphs to ensure customer-specific context remains secure and sovereign."}],"topics":["Agentic AI","Machine Learning Operations","Enterprise AI","Knowledge Graphs","Reinforcement Learning","AI Architecture","Autonomous Agents","Data Engineering"],"duration_seconds":3710,"processing_state":"processed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/data-engineering-podcast/episodes/beyond-prompts-practical-paths-to-self-improving-ai/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/data-engineering-podcast/beyond-prompts-practical-paths-to-self-improving-ai.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}