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Building Institutional Memory Into Your AI App: Capturing Unstructured Decision Data with Amazon Bedrock Knowledge Bases
Teams don’t lose data—they lose reasoning. A team selects Site 7. The system logs it. But six months later, no one remembers why. That missing “why” is where institutional knowledge actually lives. Th
blog.gainesai.com23 min read
#ai-architecture#amazon-bedrock#knowledge-bases#retrieval-augmented-generation-rag#rag#enterprise-ai
Ethan Frost
AI builder & open-source advocate. Curating the best AI tools, prompts, and skills at tokrepo.com
the dynamodb-with-1h-TTL > AgentCore Memory call is gold — most capture sessions are sub-10-min self-contained, so the Lambda scratchpad + S3 narrative shape fits way better than a persistent store you don't need.
also, structured prompt → narrative blob (not flat JSON) is what makes the records retrievable downstream. flat JSON gives the embedder zero semantic anchors. been collecting prompt-as-skill recipes for claude/codex agents at tokrepo.com — happy to swap notes on the conversational-debrief pattern.