Search Results: AgenticWorkflows

OpenTinker's new architecture eliminates the need for local GPUs in reinforcement learning, offering built-in distributed training and seamless agentic workflows. Its high-level Python API abstracts system complexity, enabling developers to focus on task design while scaling experiments efficiently.

Ahead of DevDay 2025, OpenAI previewed Agent Builder—a visual drag-and-drop platform for creating complex AI agent workflows. This strategic move challenges established automation tools by leveraging OpenAI's native AI models and promises to accelerate agent development for businesses and developers.

The santa-lang Workshop demonstrates how LLM agents can autonomously implement programming language interpreters through structured, test-driven workflows. By breaking development into gated stages and enforcing strict CLI contracts, this experiment reveals how AI approaches complex engineering tasks across Python, Rust, and other languages. The project offers unprecedented insights into agentic reasoning and cross-language implementation patterns.

Discover how to architect sophisticated AI agent systems in Ruby using model routing, PostgreSQL-powered RAG, and parallel multi-agent coordination. This technical deep dive reveals production-ready patterns for building resilient, specialized AI workflows that outperform single-model approaches.

After years of rapid evolution and uncertainty, key AI markets like foundation models, coding tools, and legal AI have crystallized with dominant players now apparent. Venture capitalist Elad Gil reveals how capital moats, hyperscaler partnerships, and agentic workflows are reshaping competition, offering critical insights for developers and tech leaders navigating this transformed landscape.