Use Cases

This cookbook demonstrates building a Slack data analyst bot using Claude Managed Agents and Bolt for Python. Users mention the bot with a CSV file to receive narrative analysis reports in-thread, with support for multi-turn follow-ups within the same session. The implementation handles file uploads, streams agent progress updates, and manages session persistence across Slack threads.

The Claude Agent SDK provides built-in session management functions to build conversation history sidebars without writing custom parsers. This cookbook demonstrates how to list, read, rename, tag, and fork sessions stored as JSONL transcripts on disk. By leveraging SDK primitives like list_sessions(), get_session_messages(), and rename_session(), developers can implement session browsers for desktop apps, IDE extensions, and chatbots without managing file I/O directly.

This cookbook demonstrates building a Claude-powered threat intelligence enrichment agent that autonomously investigates Indicators of Compromise (IOCs) by querying multiple threat intel sources, correlating findings, mapping to MITRE ATT&CK, and generating structured reports for SIEM/SOAR integration. The agent uses Claude's tool-use capabilities to decide which intelligence sources to query, chain tool calls based on discoveries, and convert free-text analysis into analyst-ready JSON reports. The architecture uses simulated threat intel backends that can be swapped with real APIs (VirusTotal, AbuseIPDB, Shodan, etc.) without changing orchestration logic.

This guide teaches how to build knowledge graphs from unstructured text using Claude's structured outputs for entity extraction, relation mining, and entity resolution. Rather than training traditional NER and relation classifiers, Claude handles each stage via prompts, enabling multi-hop graph reasoning without a database. The approach uses Haiku for high-volume extraction and Sonnet for entity resolution, with techniques transferable to production databases like Neo4j or PostgreSQL.

This cookbook teaches how to build financial dashboards, portfolio analytics, and automated reporting workflows using Claude's Excel, PowerPoint, and PDF skills. It covers three main use cases: creating comprehensive financial models with formulas and charts in Excel, generating executive presentations from financial data, and automating multi-format reporting pipelines. The guide includes setup instructions, data loading examples, and helper functions for working with the Anthropic SDK to create professional financial documents directly through Claude's interface.

The article argues that building custom workplace search products using LLMs is now economically viable and preferable to buying expensive vendor solutions. Modern tools like LangChain, LlamaIndex, and vector databases enable companies to build sophisticated internal search chatbots in days rather than months, with full customization and lower costs than traditional enterprise search products.

Skyfall AI created Mini Amusement Parks (MAPs), a RollerCoaster Tycoon-style business simulator benchmark to evaluate whether AI agents can manage real business operations with stochastic events, incomplete information, and resource constraints. Testing revealed humans outperformed GPT-5 agents by 9.8x, with AI systems failing at long-term planning, maintenance prioritization, and handling randomness—demonstrating that current LLMs lack the operational intelligence needed for true AI CEO capabilities.

Skyvern is an open-source AI agent platform that automates browser-based workflows using LLMs, allowing users to define goal-based prompts to complete complex tasks across websites without brittle code-based solutions. The platform features a React UI for real-time monitoring, workflow chaining, authenticated sessions with 2FA support, and cached workflows for reusable interactions, with token costs reduced 80% using GPT-4O.

Tavus, an AI research company, has developed a real-time conversational video agent achieving sub-1 second latency by optimizing their Phoenix-2 model architecture. Key innovations include switching from NeRF to Gaussian Splatting for 70+ fps generation, hyper-optimizing each component (vision, ASR, LLM, TTS), and implementing specialized end-of-turn detection to enable natural human-AI conversations.