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Two Rust Clients for Gemma 4: Calling the Endpoint vs. Calling the MCP Server 🦀

This article provides a step by step guide to two small Rust CLIs that ask a self-hosted Gemma 4 E2B the same question. The first calls the model's OpenAI-compatible HTTP endpoint directly. The second is an MCP client: it launches the rig's own MCP server and asks through its tools. https://github.com/xbill9/gemma-rust https://github.com/xbill9/gemma-rust-mcp Both CLIs are demos, and their output is read by an audience. So neither hides anything behind a --verbose flag: every run prints the targ

rustmcpgemma
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ExternalSoftware Engineering
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When an AI Tool Harms You, Who’s Actually Liable?

Picture the ordinary version of this. You ask an AI assistant a question that actually matters — about a refund policy, a dose, a tax rule, a contract clause — and it answers with the fluent confidence these tools always have. You act on it. It was wrong. Now you are out of pocket, or worse. Whose problem is that? The answer-first version is unsatisfying but honest: it depends on where you live and who you sue, and almost every party involved has arranged things so the answer isn’t “us.” There i

airegulationsafetyexplainers
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ExternalSoftware Engineering
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Two Readers Broke My Checks. Not One of My Numbers Moved.

Last week I published a post about nine measurement bugs I found in my own evaluation harness, all of which happened to favour my results. Two readers replied with things I hadn't found. Both were about my checks rather than my numbers. I verified both and fixed both. My results did not change at all. That turned out to be the interesting part. Some setup. The harness mutates a source file in a temp copy and runs the test suite against it. To prove that mutations actually reach the interpreter,

testingpythonai
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ExternalSoftware Engineering
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Everyone Measures AI Usage. 70% Can't Measure What It Returned.

Anthropic surveyed 132 of its own engineers about Claude Code. Merged pull requests per day rose 67 percent. Daily use of the tool climbed from 28 to 59 percent. Self-reported productivity gains ran between 20 and 50 percent. But then someone checked the organization's delivery dashboard and saw that the delivery metrics had not moved. That gap is the whole subject of this piece. A tool can be used constantly, rated highly by the people using it, and leave no trace on the numbers a business actu

financialairoi
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