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Part 2 of five on running an AI agent fleet.
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Part 3 of five on running an AI agent fleet.
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A friend asked how I use AI day to day.
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After years of building compliance automation inside large organizations, I kept running into the same problem: the tools that exist are either too expensive, too rigid, or too disconnected from how software is actually built today.
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After thinking about it for a long time (very long time), I realized the “AI problem” isn’t new.
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Six months ago, I wrote about the massive security blind spot in AI adoption.
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When Code Scanners Miss the Forest for the Trees The rise of AI-powered coding tools is creating a new kind of compliance risk that most organizations are not prepared for.
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What Are AI Models and How Are They Distributed?
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Following my previous post, I want to expand on the topic with some ideas for data feeds that support open source compliance audits and risk assessments when using an Agentic AI approach.
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Today, I gave a talk called “Taming the SBOM Chaos: Using AI Agents to Audit SBOMs for OSS Compliance.”
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SBOM adoption is accelerating.
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SPDX and CycloneDX are excellent standards for handling Software Bill of Material (SBoM), but full adoption requires time, tooling, and correct intake processes.
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AI has become disruptive in many ways, especially for developers using AI agents to debug software, remediate errors, and even automatically generate the whole code for simple applications.