Scheduled social research agent: A walkthrough with LangChain's managed platform
LangChain developer Casper shares a detailed walkthrough of building an agent that researches Hacker News and X, drafts posts, and sends them to Slack on a schedule. The article covers setup, tools, memory, and deployment, highlighting a formatting hiccup the agent corrected. It's a practical look at combining platform features for autonomous social media research.
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The article describes a walkthrough by LangChain developer Casper of building a scheduled agent using the company's managed deep agents platform. The agent scans Hacker News and X, drafts three social media posts daily, and delivers them to Slack at 9:00 AM Pacific without human intervention.
Key components include the mda CLI for scaffolding, a Hacker News search tool using the Algolia API, and two X tools requiring a bearer token. The agent's instructions are split into a static instructions.md and a skill that can be loaded dynamically, with memory to avoid repeating topics across runs. Scheduling and Slack integration are configured via cron and a channel definition.
The article notes a practical issue: the agent's markdown formatting didn't render well in Slack, but it corrected itself when told. Casper reports saving time using the agent daily, though these are his claims. The walkthrough illustrates how tools, skills, memory, schedules, and channels combine for an autonomous workflow.