Improving token efficiency in GitHub Agentic Workflows
… We try to normalize this by tracking LLM API call counts alongside token counts; constant LLM turns-per-run and falling tokens-per-call indicate genuine efficiency improvement. …
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Validating agentic behavior when “correct” isn’t deterministic
… Semantic analysis via LLM: When visual metrics are ambiguous, we use a multimodal LLM to decide if differences are semantically meaningful. For example, the LLM knows to ignore a timestamp change or a different window decoration but will flag a different error message or missing UI control. …
Vibe coding with GitHub Copilot: Agent mode and MCP support rolling out to all VS Code users
… Today is also a hallmark moment in the history of technology: our mothership turns 50! …
How researchers are using GitHub Innovation Graph data to reveal the “digital complexity” of nations
… Kevin: Have things changed since generative AI tooling came along? Have you found generative AI tools to be helpful? Johannes: Absolutely. We use LLM tools regularly now for things like debugging data pipelines, drafting boilerplate code, and even sanity-checking statistical approaches. …