Here's a pattern I keep seeing. A team wires up an AI agent that can do real things — send emails, run commands, query and modify the database, call external APIs. The demo is magical. It reads a request, figures out the steps, takes them, reports success. Everyone's impressed, and it ships. Then ...
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Read articleMicrosoft's MAI-Transcribe-2-Streaming can now be used by LiveKit Agents through an official...
Read articleOpenAI is taking a cautious approach to text provenance by limiting access to its new text watermark detector at launch. The company has announced a phased rollout of tools built around **textGrain**, a watermarking approach for outputs from models including ChatGPT and Codex. Rather than releasing ...
Read articleOpenAI is extending its content provenance work to **AI-generated text in the European Union**, positioning the move as part of its response to the [EU AI Act](https://scalevise.com/resources/eu-ai-act-transparency-rules-2026/). The company is taking a phased approach: eligible API customers worldwi...
Read articleEvery dev picks up a pile of rules early on. Write tests first. Never commit to main. Keep functions under 20 lines. DRY everything. Comment your code. 100% coverage or it doesn't count.  Some ...
Read articlen8n Cloud users on Starter, Pro, and new trial plans can use TypeSafe AI's Jev model without Gateway credits being deducted until **October 10, 2026, at 23:59 UTC**. The limited promotion gives teams a low-friction way to test [AI-driven decisions](https://scalevise.com/resources/ai-workflow-automat...
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Read articleWhen an autonomous agent struggles on long terminal tasks, the standard engineering response is to add scaffolding. You wrap the model in state machines, inject environment probes, add reflection loops, and supply intermediate test harnesses until it stumbles across a solution. That scaffolding wor...
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