{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Code and Cognition","title":"Turning the Page on MIT’s GenAI Report, What’s Happening in 2025","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/c35a7cf8\"></iframe>","width":"100%","height":180,"duration":1420,"description":"In this episode, we reflect on what were the real-world challenges of building generative AI applications in 2024  and how to avoid them in 2025. Drawing insights from a recent MIT Technology Review report and our firsthand experience building Data Pilot, we unpack what’s holding enterprises back from moving GenAI apps into production—and how to fix it.From hallucinations and latency to the need for reliable structured output, we cover the hard lessons, practical tools, and architecture decisions that make the difference. You’ll also get a behind-the-scenes look at how Data Pilot helps teams prototype, test, and refine prompts using the latest LLMs like Claude and GPT-4.\nIf you're serious about shipping GenAI features at scale, this is the conversation for you.\n\nTopics Covered:1. The top 6 barriers to GenAI production adoption in 2024 and how best approach them\n2. Why most LLM projects fail due to hallucinations and lack of guardrails\n3. The role of system prompts and how to use them effectively\n4. Debugging “self-talking” AI: how Claude can spiral without proper prompt roles\n5. What structured output really means—and why it’s non-negotiable\n6. Why prompt engineering is just the beginning—and data infrastructure is key\n7. How Data Pilot streamlines prompt iteration, testing, and structured data generation\n8. The hidden trade-offs between accuracy, latency, and cost when selecting LLMs\nTools & Concepts Mentioned:1. System Prompts (LLM guardrails)2. Retrieval-Augmented Generation (RAG)3. JSON & XML output formats4. Data Pilot – a workbench for LLM development5. Claude, GPT-4, Meta’s LLMs6. Prompt iteration and synthetic data generation\nKey Themes:\"System prompts are the first line of defense—without them, the LLM just talks to itself.\"\n\"Structured output isn’t just nice to have—it’s how you scale, debug, and improve.\"\n\"Data Pilot lets you develop prompts with the help of an AI co-pilot that knows how it wants to be talked to.\"\nOlio Apps can help you build your...","thumbnail_url":"https://img.transistorcdn.com/FibZYR2Jc4bAsvUYB_faLieYy39Memr1SvaXdzAp7Qc/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82ODFl/ZTE4MWM5YjQyMzM2/MzhkNjViNzUxYmFl/YmIyYi5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}