Historical Context & Impact - The 1921 Tulsa Race Massacre, triggered by a sensationalized report, resulted in the deaths of 300 Black Americans and the destruction of over 12,200 homes, businesses, and churches in the Greenwood district [1][2] - The Tulsa Race Massacre was largely suppressed for decades, with police records vanishing and newspaper archives being tampered with [3] - Viola Ford Fletcher, a survivor of the massacre, became a memory keeper and fought for justice, bringing attention to this forgotten history [3][6] Community & Resilience - Greenwood, also known as Black Wall Street, was a prosperous and organized Black community before its devastation [2][9] - Black communities like Greenwood represent Black prosperity, resistance to white supremacy, and the fight for recognition as American citizens [15] - Despite the devastation, the Black community in Tulsa rebuilt, demonstrating resilience and a belief in themselves [22] Memory & Legacy - Preserving the memory of events like the Tulsa Race Massacre is crucial to counteracting amnesia and neofascist upsurges that seek to erase Black history [14][16] - Communities must take responsibility for preserving their history, teaching it, and refusing to let the stories of the past be buried [24][25] - Black women, like Mother Fletcher, play a significant role in holding up legacies and nurturing communities [28][29]

Karpathy said:"Agents don't have continual learning."Finally, someone's fixing this limitation in Agents.Composio provides the entire infra that acts as a "skill layer" for Agents to help them evolve with experience like humans.Learn why it matters for your Agents below: https://t.co/1Qv9Dx6ewtAvi Chawla (@_avichawla):First tools, then memory......and now there's another key layer for Agents.Karpathy talked about it in his recent podcast.Tools help Agents connect to the external world, and memory helps them ...

Product Overview - Langsmith Agent Builder is a new no-code agent experience that allows users to build and describe agents in natural language, incorporating memory for adaptation and learning [1] - The core of building an agent lies in crafting a detailed prompt, with Langsmith Agent Builder providing tools like metaprompting to assist in this process [2][3] - Agents can remember interactions and update prompts in a memory bank, enabling continuous learning and adaptation [4] Key Features - Metaprompting helps users refine their initial ideas into detailed prompts through follow-up questions [3][6] - Agents can connect to internal tools or APIs with proper Oauth and credentials [8] - A test chat feature allows users to debug agents by pausing execution before tools are used [10] - Memory enables agents to update instructions based on interactions, allowing them to learn and adapt over time [11][12][14] - The agent inbox allows users to monitor agents, receive notifications, and provide assistance when needed [18] Agent Management - Users can monitor agent threads, categorized as idle, busy, interrupted, or errored, to manage agent performance [16] - The agent builder is not a visual workflow builder but focuses on agent autonomy and memory [19] Example Use Case - A daily briefer agent can be created to read a user's calendar and send a report via Slack at a specified time [5][7] - The agent can be instructed to perform specific tasks, such as writing a poem, and will update its memory to incorporate these instructions [11][12][13]