{"podcast":{"title":"AI Convo Cast","slug":"ai-convo-cast-7218040","podcast_index_feed_id":7218040,"rss_url":"https://anchor.fm/s/101530384/podcast/rss","website_url":"https://www.AIConvoCast.com","image_url":"https://d3t3ozftmdmh3i.cloudfront.net/staging/podcast_uploaded_nologo/43071849/43071849-1752663089770-6d4571d306591.jpg","author":"AI Convo Cast","episode_count":379,"summary":"AI Convo Cast is your daily source for the latest developments in artificial intelligence, machine learning, software development, and technology. Each episode offers concise, AI-generated insights into breakthroughs, trends, and innovations shaping our world. Stay informed and engaged with up-to-date news and analysis in the rapidly evolving tech landscape.","last_synced_at":"2026-06-16T20:19:55.629187+00:00","page_url":"https://stenobird.com/podcast/ai-convo-cast-7218040"},"episode":{"title":"DeepSeek V4, OpenAI GPT 5.5, and MCP Security Risks","slug":"deepseek-v4-openai-gpt-5-5-and-mcp-security-risks","published_at":"2026-04-25T09:15:00+00:00","page_url":"https://stenobird.com/podcast/ai-convo-cast-7218040/deepseek-v4-openai-gpt-5-5-and-mcp-security-risks","show_page_url":"https://stenobird.com/podcast/ai-convo-cast-7218040","url":"https://podcasters.spotify.com/pod/show/aiconvocast/episodes/DeepSeek-V4--OpenAI-GPT-5-5--and-MCP-Security-Risks-e3ieko9","audio_url":"https://anchor.fm/s/101530384/podcast/play/119017673/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-3-25%2Faf6a19f8-8f31-2ed9-abed-a348d8e11f04.mp3","summary":"In this episode, we discuss DeepSeek V4 and its one million token context window, OpenAI GPT 5.5 pricing and agentic coding performance, MCP security risks, and Microsoft Research AutoAdapt for domain adaptation. We break down DeepSeek V4 Pro and V4 Flash, mixture of experts efficiency, long context AI agents, and why developers are comparing GPT 5.5 coding gains against higher token costs. We also examine the MCP Model Context Protocol controversy involving toolchains like LangChain, LiteLLM, Flowise, Cursor, and VS Code, plus how AutoAdapt automates RAG, fine tuning, LoRA, and enterprise LLM adaptation under budget, latency, privacy, and accuracy constraints. https://www.aiconvocast.com Help support the podcast by using our affiliate links: Eleven Labs: https://try.elevenlabs.io/ibl30sgkibkv Disclaimer: This podcast is an independent production and is not affiliated with, endorsed by, or sponsored by DeepSeek, OpenAI, Microsoft, Anthropic, NVIDIA, LangChain, LiteLLM, Flowise, Cursor, VS Code, Eleven Labs, or any other entities mentioned unless explicitly stated. The content provided is purely for informational and entertainment purposes only and does not constitute professional, financial, legal, security, or technical advice. Some links may be affiliate links, and we may earn a commission if you use them, at no additional cost to you.","meta_description":"In this episode, we discuss DeepSeek V4 and its one million token context window, OpenAI GPT 5.5 pricing and agentic coding performance, MCP security risk…","key_points":[],"chapters":[],"topics":[],"duration_seconds":1063,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/ai-convo-cast-7218040/episodes/deepseek-v4-openai-gpt-5-5-and-mcp-security-risks/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/ai-convo-cast-7218040/deepseek-v4-openai-gpt-5-5-and-mcp-security-risks.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}