Autonomous AI systems are collapsing the cost of finding software vulnerabilities toward zero, making known-flaw supply nearly infinite. The scarce, high-leverage work has shifted from discovery to deciding which of the roughly 6% of ever-exploited CVEs actually deserve a fix.
Get started with local LLMs! This post breaks down how the transformer architecture works, why you need an inference engine to run models, and how to set up your first local llm using Ollama.
Running local LLMs isn't just about privacy—it's about cost, control, and understanding how AI really works. Here's where to learn, what to ignore, and how to get started.
AI tools advertising 'web search' actually route queries through proprietary filtering APIs that silently decide what you can find. A reproducible three-query test found an unfiltered SearXNG instance returning 55 links versus 28 and 10 from two major AI search backends.
Qwen's new AgentWorld-35B-A3B highlights a growing trend in local AI: specialized, self-hostable models competing with frontier systems on targeted workloads. The question is increasingly not "Which model is smartest?" but "Which model is best for the job?"
Most announced 'sovereign' AI models are foreign open-weight models in local costume. Real AI sovereignty requires verifiable control over the stack, including auditable provenance, retraining rights, and ownership of cultural defaults.
We took a freshly provisioned bare-metal hypervisor and turned it into a hardened, monitored, VPN-connected production host in a single afternoon. An AI agent handled the tedious verification; a human held authority over every irreversible step.
The first AI golden age was built on renting frontier model compute by the token. The second is built on local inference, small specialized models, and routing architecture that puts the right task on the cheapest capable model.
GLM 5.2 is now available as an open weight model on Hugging Face, ranking fourth overall and competing directly with closed frontier leaders Mythos, Fable, and Opus 4.8. It is the strongest open weight model tested to date, with no vendor agreement or API required.
A low-balance email revealed a compromised LLM API key being silently drained by automated bots. The forensic trail shows how stolen API credentials have replaced crypto mining as the attacker's prize, and what you can do to stop it.
The Mythos/Fable blockade revealed a new reality: a model's benchmark score is zero when it's unavailable by decree. In the age of strategic AI, availability has become a capability of its own—and open-weight models are how organizations reclaim it.
AI agents are commoditizing tool-specific knowledge, shifting the scarce skill from knowing a tool's syntax to knowing which problem is worth solving. Engineers who can define goals, constraints, and success criteria will capture the premium that tool expertise once held.