Taryn Plumb is a Contributing Writer and Editor at various publications. She specializes in AI and cybersecurity, focusing on themes such as artificial intelligence, machine learning, and software development. Taryn's work has been featured in notable outlets including Maverick Studios, SDxCentral, and VentureBeat.
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Taryn Plumb's coverage largely centers around enterprise technology, focusing on cybersecurity, AI and ML, telecom, and data management. Her preference for citing data and press releases suggests that she values content backed by verifiable information and official sources.
Given her focus on emerging trends in the tech industry, Taryn would likely be receptive to pitches from experts who can provide insights into upcoming technologies or comment on the implications of new tools within the specified domains. Additionally, offering access to exclusive data or research findings related to these topics may also capture her interest.
Since there is no specific geographic focus mentioned for Taryn Plumb's reporting, it seems she covers global technological developments rather than being confined to a particular region.
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The tech giants will embed their engineers directly into customer teams, challenging decades of dominance by systems integrators in enterprise technology deployments.
General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document review cycles from 60 days to 10.
By: Taryn Plumb
As the company trims thousands of jobs, it's also investing in embedded engineering teams; CIOs should expect this shift to reshape customer support, implementation, and partner engagement.
By: Taryn Plumb
The AI architecture that let Liberty Mutual shrug off the Fable 5 outage
By combining AI models, supercomputing, satellites, and launch capabilities, the newly unified company is making an ambitious play for AI infrastructure.
Researchers have uncovered a sustained campaign using GitHub's public APIs and ghost accounts to profile enterprise software environments while blending into normal developer activity.
By: Sabine Frömling
As agentic AI and autonomous agents trend in 2026, enterprises face a major new hurdle: standard IAM stacks aren't built to govern these non-human actors.
The new release adds multi-agent workflows, parallel execution and built-in governance as enterprises look beyond AI coding assistants to accelerate software delivery.
With lazy imports, JIT compilation, Python-generated C, or the Python-esque Mojo, it has never been easier to make Python go faster.
By: Maria Korolov, Taryn Plumb, Hal Lonas, Grant Gross
Stop worrying about prompt injection; your next major breach will be caused by an authorized AI agent doing exactly what you permitted it to do.
