Micro1 Pays Vetted Experts Hourly to Train AI Models, but Placement Is Not Guaranteed

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Micro1, a Palo Alto company, supplies credentialed human specialists to AI labs and enterprises to create and evaluate tasks used for training frontier AI models. Contractors work remotely as independent workers paid in USD, with senior engineers, attorneys, and finance or engineering specialists earning the highest rates. Applicants face an AI-conducted interview and skills assessment, and there is no fee to apply. Certification makes candidates eligible, but matching to paid projects can take days to weeks, and the company pays referral fees only after a candidate is certified, matched, and completes 10 hours of work. The article warns readers to be wary of anyone requesting payment to unlock work.

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Developer open-sources four MIT-licensed tools for AI-driven e-commerce work

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ProgrammingDEV Community ·

Planning Active Directory Protected Users membership and managing its exceptions

Microsoft's Protected Users group applies fixed protections against credential theft, such as blocking credential caching, NTLM and Digest delegation, and limiting Kerberos to newer encryption. Because these restrictions cannot be toggled per account, adding a user is a compatibility decision as well as a security one. The article recommends first inventorying authentication dependencies through logs, then running a small pilot that tests interactive sign-in, administration, Kerberos tickets and delegation. Organizations should keep a tested break-glass account, record approvals and rollback steps, and review membership regularly so the group stays small and current. Protection only applies on supported hosts and domain controllers, so the platform should be verified before reporting an account as protected.

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ProgrammingDEV Community ·

Treat AI Agent Tools Like Public APIs to Prevent Duplicate Actions

A developer's first production AI agent issued the same refund three times after a payment API returned a 502 error and the model retried the call. The root cause was a missing idempotency key, a bug familiar from standard HTTP client code rather than a language model problem. The article argues that the model should be treated as an unpredictable API caller, so tools need the same safeguards as public APIs, including versioning, timeouts, idempotency, scoped credentials, and rate limits. It recommends classifying every tool as read, write, or destructive, with that classification enforced in code rather than documentation. The author also advises generating idempotency keys in the application, since models will retry calls for many reasons.

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