This session introduces Dana, a local-first agent programming language designed for building AI agents. Get a working expert agent in minutes:

• Long running, multi-step agent workflows on a single line: step1 | step2 | [step3a, step3b, step3c] | step4
• Built-in concurrency for parallel LLM calls with zero async keywords
• Deterministic execution with learning loops that improve reliability over time

Whether you're dealing with sensitive data, air-gapped requirements, or cloud API limitations—come see what agent development looks like when everything runs locally.

This session introduces Dana, a local-first agent programming language designed for building AI agents. Get a working expert agent in minutes:\n- Long running, multi-step agent workflows on a single line: step1 | step2 | [step3a, step3b, step3c] | step4\n- Built-in concurrency for parallel LLM calls with zero async keywords\n- Deterministic execution with learning loops that improve reliability over time\n\nWhether you're dealing with sensitive data, air-gapped requirements, or cloud API limitations—come see what agent development looks like when everything runs locally.

Async Python for Data Science: Speeding Up IO - Bound Workflows\nMost Python scripts in data science are synchronous — fetching one record at a time, waiting for APIs, or slowly scraping websites. In this talk, we’ll introduce Python’s asyncio ecosystem and show how it transforms IO - heavy data workflows. You'll see how httpx , aiofiles , and async constructs speed up tasks like web scraping and batch API calls. We’ll compare async vs threading, walk through a real - world case study, and wrap with performance benchmarks that demonstrate async's value.\nKeywords: p ython 3.x , AsyncIO, Web Scraping, API, Concurrency, Performance, Optimization

Most Python scripts in data science are synchronous — fetching one record at a time, waiting for APIs, or slowly scraping websites. In this talk, we’ll introduce Python’s asyncio ecosystem and show how it transforms IO-heavy data workflows. You'll see how httpx, aiofiles, and async constructs speed up tasks like web scraping and batch API calls. We’ll compare async vs threading, walk through a real-world case study, and wrap with performance benchmarks that demonstrate async's value.