DeepSeek-R1 in practice with step.ai
Blog post from Inngest
DeepSeek-R1 is a cheaper and open-source model that excels at agentic reasoning, superior multilingual capabilities, large context windows, and generalization across domains. It was tested in real-world examples with Inngest as an orchestrator library and interface to explore its Multi-Lingual marketing content generator, Agentic arXiv Research Assistant, and other use cases. The model demonstrated strong performance in understanding and generating content in multiple languages while maintaining cultural nuances. Its large context window capability enabled it to provide relevant search queries for arXiv research papers, even when asked questions in French. However, the model still lacks support for tool calling and system prompts, which are essential for creating agentic applications.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Serverless | 14 | 547 | 133 | 74 | -30% |
| LLM | 3 | 3,709 | 434 | 145 | +39% |
| Edge Computing | 2 | 73 | 34 | 21 | +46% |
| RAG | 2 | 1,794 | 220 | 80 | +16% |
| Developer Experience | 1 | 418 | 168 | 95 | +43% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.