{"version":"1.0","type":"card","id":"e429ddb0-2f4f-412b-99c3-febdb07d331c","url":"https://stacklist.com/card/e429ddb0-2f4f-412b-99c3-febdb07d331c","title":"The Context Window Mirage: Dynamic Task-Specific RAG","source_url":"https://www.codestory.co/episodes/s12-bonus-the-context-window-mirage-why-generic-prompt-engineering-fails-enterprise-workflows-and-the-rise-of-dynamic-task-specific-rag-orchestration-with-ankit-dheendsa-co-founder-ceo-of-morphos-ai/","note":"Code Story podcast features Ankit Dheendsa, Co-Founder and CEO of Morphos AI, discussing why generic prompt engineering fails enterprise workflows and how dynamic, task-specific RAG orchestration addresses LLM hallucinations.","image":{"url":"https://ucarecdn.com/75642a39-2885-4fd0-a106-b6928266a6a4/","alt":"The Context Window Mirage: Dynamic Task-Specific RAG","width":1400,"height":1400},"stack":{"id":"4a7cc3d8-26c0-4ce0-839a-302d608bd60a","title":"Code Story Season 12: Founder Interviews & Startup Insights","url":"https://stacklist.com/c/podcast/stack/4a7cc3d8-26c0-4ce0-839a-302d608bd60a"},"created_at":"2026-07-24T21:44:24.779Z","updated_at":null,"aco":{"summary":"Code Story podcast features Ankit Dheendsa, Co-Founder and CEO of Morphos AI, discussing why generic prompt engineering fails enterprise workflows and how dynamic, task-specific RAG orchestration addresses LLM hallucinations. Morphos AI's product Katana is an SDK and API hybrid that reduces vector storage, increases accuracy, and decreases latency for companies utilizing retrieval augmented generation.","tags":["rag-orchestration","llm-hallucinations","vector-storage","prompt-engineering","enterprise-ai","startup","podcast"],"key_entities":[{"name":"Ankit Dheendsa","type":"person","confidence":0.98},{"name":"Morphos AI","type":"organization","confidence":0.97},{"name":"RAG (Retrieval Augmented Generation)","type":"technology","confidence":0.95},{"name":"LLM Hallucinations","type":"concept","confidence":0.92},{"name":"Katana","type":"technology","confidence":0.88},{"name":"Vector Storage Reduction","type":"concept","confidence":0.9},{"name":"Code Story","type":"organization","confidence":0.95},{"name":"Toronto","type":"location","confidence":0.85},{"name":"Prompt Engineering","type":"concept","confidence":0.88}],"classification":"transcript","language":"en","confidence":0.85,"provenance":{"model":"claude-opus-4-6","tool":"@stacklist/mcp-server@2.0.0","confidence":0.85,"timestamp":"2026-07-24T21:44:35.225Z"},"token_counts":{"approximate":10709,"cl100k":12099},"content_hash":"sha256:96e24ad09766f0710ebbec0c245ec278f05715bde650364dc6704926619424a0","acp_version":"0.2","body_available":true,"body_tokens":10709,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/e429ddb0-2f4f-412b-99c3-febdb07d331c.json","html":"https://stacklist.com/card/e429ddb0-2f4f-412b-99c3-febdb07d331c","md":"/api/public/card/e429ddb0-2f4f-412b-99c3-febdb07d331c.md","stack_json":"/api/public/stack/4a7cc3d8-26c0-4ce0-839a-302d608bd60a.json"}}