AI Chat Detection Is Here in AirDroid Parental Control!
Say hello to AI Chat Detection! And learn how to receive alerts about potentially risky conversations in your child's ChatGPT, Gemini, and Character.AI.
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Run CI Tests Without Pushing: Microbuilds with Chunk sidecars
AI coding agents write code faster than your pipeline can catch mistakes. What if the agent could validate against CI before you ever push? In this 5-minute demo, we set up CircleCI's Chunk CLI and run a microbuild using Chunk sidecars, secure Linux microVMs that spin up in ~1 second in your CircleCI account, mirror your working directory (no git push required), and give your agent CI-grade feedback while it's still in context.
The skill gap AI can't close, with Hywel Carver of Skiller Whale
If 90% of code is now AI-generated, what happens to the engineers who never had to write it themselves? The ability to review code well, to catch what the LLM missed, depends on mental models that only come from practice. That tension sits at the center of this conversation.
Detecting Data Masking Gaps in a CI Pipeline | The Tony and Tonie show Ep44
Your schema changed. Did your masking rules keep up? Here’s how Flyway and Test Data Manager can catch gaps and prevent PII exposure in dev and test. Tony and Tonie discuss how Flyway and Redgate Test Data Manager can work together in a CI pipeline to detect schema changes that introduce unmasked sensitive columns, helping teams keep production-derived test data protected as the database evolves.
AI inference vs. training: What they are and how they differ
AI inference and training are terms you'd run into if you have been around software engineering or even just scrolled through the news. Both are integral to delivering the AI-powered experiences we have come to expect from many of the applications we use daily. According to McKinsey, by 2030 inference will overtake training as the dominant workload in AI data centers, making up more than half of all AI compute and roughly 30-40% of total data center demand.
Internet Performance Monitoring: Understand Digital Experience from the User's Perspective
Internet Performance Monitoring (IPM) provides end-to-end visibility into what happens between your infrastructure and your users, across networks and services you don’t own or control. The internet is your network now. Your apps live in the cloud, your users are everywhere, and the systems that deliver your applications and services to them use hundreds of providers, ISPs, and networks beyond your control. In practice, that means infrastructure monitoring is the foundation.
How Fragmented Data Breaks AI Strategy feat. Sterling Parker, Ivanti
Your AI is only as good as the data it sits on — and fragmented IT data isn't just inefficient; it's dangerous. Watch Ivanti's Sterling Parker, SVP of Global Solutions and Services at Ivanti, explain why a unified IT platform and a clean system of record are the true foundation of secure, scalable AI.
AI Governance: Closing the Policy Gap feat. Brooke Johnson, Ivanti
AI governance isn't optional — it's the difference between scaling AI confidently and exposing your organization to serious risk. Watch Brooke Johnson, Ivanti's Chief Legal Counsel, SVP HR and Security, break down why AI policy alone isn't enough and what it actually takes to close the governance gap.
Speed with Confidence: Managing Delivery Risk in an AI-driven Development World
In the modern development landscape, we are seeing a shift in how work is managed. The rise of AI-assisted development and highly distributed teams means that work is moving faster than ever before. However, this increased velocity often comes with a hidden tax: complexity. We are seeing more parallel work streams, more intricate dependencies, and a constant stream of shifting priorities. In this environment, simply moving fast is not enough to guarantee success.
Automating Device and OS Compliance in Air-Gapped Networks with Agentic AI
For network operations and security teams, maintaining compliance across device hardware and operating systems is a complex and time-consuming task. At any given moment, your network contains thousands of devices from dozens of different vendors. To keep this infrastructure secure, you must constantly know which devices are approaching end-of-life (EOL) milestones, and which platforms are vulnerable to active common vulnerabilities and exposures (CVEs).