Automation Path

Identify tasks worth automating. Cost/benefit analysis for AI automation.

Write Python scripts that use LLMs for data processing, summarization, and classification.

Create agents that can browse, search, extract data, and make decisions autonomously.

Design systems where multiple AI agents collaborate on complex tasks.

Process and transform data at scale using LLMs. ETL with intelligence.

Set up logging, alerting, and quality checks for production AI workflows.

Cost optimization, caching strategies, and fallback patterns for production AI.