How legal and compliance teams use AI, how to do it well, and what it means for your job. Written for people who review the contracts and manage the risk, not people who build models.
Which software engineering skills matter when AI writes the code? Learn five: directing agents, verifying output, system design, governance, and ownership.
Learn how to monitor AI agents at work with a six-step framework: agent inventory, non-human identity, autonomy tiers, runtime logging, kill switches, and NIST/OWASP alignment.
Employees are pasting trade secrets into ChatGPT. Here's how to build a locally hosted, permission-aware document scanner that stops the leak without a ban.
AI coding assistants cut keystrokes and seem to ease RSI for some developers, but burnout keeps rising. Here's what the data actually shows.
We secretly tested our team on spotting AI vs. human content. Accuracy barely beat a coin flip, matching research from 19% to 76%. Here's what to build instead.
AI models optimize to look correct, not to be correct. Here's how to test AI-generated code and sandbox employee-built tools before they fail in production.
ChatGPT can read a 1040 or W-2, but accuracy is spotty and your data's fate isn't yours to control. Here's what uploading your return really risks.
Open source can't agree on AI code policy. Here's the 6-step framework enterprise IT leaders can use to audit AI-generated and shadow AI code.
AI isn't replacing web developers. It's automating boilerplate. Here's what BLS, Anthropic, and SignalFire data show about the real job shift.
Employee-built AI agents can lie, blackmail, collude, and commit fraud under pressure. Here are 5 documented shadow AI risks and how to govern them.
AI text detectors don't work, and asking the AI to check itself doesn't either. Here's the actual procedure for verifying AI-generated documents and code.
Employees now give AI agents standing access to email and files, not just chatbots. Here's how to govern shadow agent identities before they cost you.
Bans don't stop shadow AI. Here are 5 open-source tools IT leaders use to inventory, secure, and govern employee-built AI agents instead.
Employee-built AI automations inherit a frozen model worldview. Here are 5 ways training cutoffs and model drift quietly break shadow-built tools.
No-code tools let employees build real agents fast. Here's the identity-based, lifecycle-aware framework for governing shadow AI before it breaches you.
Long-running agents like Astra now work unsupervised for days. Here's why IT governance built for software licenses fails, and the framework that replaces it.
AI writes the code and runs incident response, but no one understands the system that broke. Here's the governance gap turning outages into crises.
Banning shadow AI doesn't work. Here's how to govern employee ChatGPT usage and custom GPTs with a tiered, earned-autonomy trust framework instead.
Chrome killed uBlock Origin's full power for good. Here's why enterprise policy couldn't stop it, and which browsers and tools IT teams can still govern.
Employees built a shadow layer of business logic into ChatGPT's memory and custom instructions. Here's how to govern it before it walks out the door.
Employees are building agent swarms with no registry, identity, or owner. Here's the governance model to manage AI agents in the enterprise without banning them.
Debian, the Linux kernel, and GCC just codified AI code rules. Here's how to turn their disclosure and accountability framework into your company's policy.
A practical workflow for reviewing AI-generated code: acceptance gates, risk-based routing, dependency scanning, and where human review still matters most.
Developers built an open-source AI to replace their CEO as a joke. The real lesson: AI can do PM tasks, but not the judgment behind them.