Articles
Practical materials about rolling AI into business operational processes.
After dozens of tests we crossed everyone else out: only Anthropic and OpenAI remained
A practical study of OpenAI, Anthropic, and other providers: limitations, result quality, and model recommendations as of 09.05.2026.
ReadWe gave an agent five days to build a marketplace. It worked, and it hurt
An honest Hermes/founder-agent experiment: an agent moved a product for days and built an alpha flow, while showing why autonomous development is still painful and raw.
ReadAI agents can be trusted. Trust is built by the system architecture around them
Why distrust of AI almost always grows out of poor implementation rather than the agents themselves, and how this is fixed through zero trust and role design.
ReadAnthropic sells skills beautifully. But for enterprise, tools are almost always more reliable
Why skills sound cool, but tools are almost always more reliable for enterprise: security, allowlists, observability, speed, and cost.
ReadAI demos impress everyone. AI products die on the last mile to the user
Why an AI project can look strong in a demo but fail at the moment of real release, integration, and delivery of value to the user.
ReadA beautiful AI demo means nothing: how to know a feature is actually ready for release
A practical breakdown of how to distinguish a beautiful AI demo from a feature that can actually be shipped to production.
ReadOne AI agent ships every day. Another spends a week checking invariants: that is what aggressiveness really is
Agent aggressiveness describes release tempo, acceptable risk, and the choice between startup speed and big-tech reliability.
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