From the meLink team
Author: Marc Uberstein
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Thomson Reuters Model Is a $40M Bet on Trust
Thomson Reuters built Thomson around proprietary expertise and verification. The $40m bet shows why trustworthy AI is a system, not…
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AI Dependency Map: Know What Your Agent Relies On
An AI dependency map shows the services, sources, permissions, owners, and fallbacks behind an agent before a small failure becomes…
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Qwen 3.8 Reverse Engineering Took 30 Minutes
A fresh Qwen 3.8 field report shows why teams should test open models on reviewable engineering work, not just benchmark…
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AI Apology Design Is a Customer Experience Test
AI apology design turns a wrong answer into a clear recovery: honest correction, safe next steps, and a human route…
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MCP Roadmap Puts Agent Identity First
The new MCP roadmap makes agent identity, delegated authority and operational safety the next practical challenge for builders.
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AI Model Choice Starts With the Job, Not the Benchmark
Choose AI models by the job they must finish, the evidence they need, and the failure they must avoid—not a…
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Claude Code 2.1.239 Fixes a Costly Proxy Failure
Claude Code 2.1.239 fixes a proxy retry failure that could double API billing – an essential lesson in reliable agent…
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AI Context Budget: Give Agents Less to Do More
An AI context budget gives each agent only the evidence and state it needs, making answers faster, safer, and easier…
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On-Device Piano Model Hits 108 Notes a Second
A 125M on-device piano model reaches 108 notes per second on an iPhone, offering a lesson in latency, privacy, and…
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AI Pricing Model: Don’t Sell Unlimited Work
An AI pricing model should price a useful outcome, show the boundary of ordinary use, and make costly exceptions a…