AI coding tools still struggle with speech APIs.
So we shipped 3 tools in April to fix that:
1️⃣ dg CLI for terminal speech AI workflows
2️⃣ dg mcp for AI coding tools
3️⃣ deepgram/skills so your agent loads Deepgram context on install
Now your agent can build with Deepgram context already loaded.
The eval-to-prototype loop just got a lot shorter.
Blog: https://t.co/o8MKz0DKbT
CLI: https://t.co/3Eqp0Rt7EJ
Skills:
MCP — The Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
Why it matters
Coding agents routinely get speech API calls wrong. An MCPThe Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.Full definition → server plus installable skills puts the correct Deepgram surface in front of the AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → before it writes code, shortening the loop from evalA repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.Full definition → to working prototype.
