After we repaired retrieval, the model still failed a combined count-and-timeline question. It had relevant evidence, yet the application could not return a useful validated answer.
The next failure was surprisingly small: the model removed Markdown bold markers while copying source text.
The local model finally answered a real question correctly: how many domains are in the AI-SGAP framework?
The next question exposed a different problem. Asked how the risk-floor logic was calculated, the application returned “Not enough evidence.”
In Part 1, our first MLX and Q4 attempts stopped under memory pressure. This installment covers the configuration and validation boundaries we used to make the next tests interpretable.
This series follows the build as it develops. The system is still a pilot; several harder questions remain unresolved.
Selling AI security assurance is selling life insurance. You ask a buyer to pay today for protection against a day they would rather not picture. And the deal stalls for the same reasons.
Every insurance agent knows the pattern. The product makes sense, the prospect nods, and then the subject changes. Nobody enjoys rehearsing their own funeral.
If you’ve spent any time around AI agents lately, you’ve heard someone say “it’s not the model, it’s the harness.” Release notes mention harness improvements. Benchmarks report scores “with our harness.” Engineers argue about whose harness is better.
It’s one of those words everyone uses and almost nobody stops to define. So let’s define it.
Trivy reported zero vulnerabilities. Grype reported ten findings at the same runtime-image checkpoint. Here is what that discrepancy taught us about package identification, advisory sources, filtering, and defensible container-security decisions.
AI/ML Basics Simply defined, Artificial Intelligence (AI) is a field of Computer Science where Systems are taught and can simulate intelligent and/or predictive behavior and/or activities using programs and technology. Machine Learning (ML) is a subspecialty of AI by which a computer improves its own performance by continuously incorporating new data into its statistical model. An Artificial Neural…
OCI’s native capability to obtain packet capture and monitor flow data between components Each compute instance in a VCN has one or more Virtual Network Interface Cards (VNICs). The OCI Networking service uses Security Lists to determine what traffic is allowed through a given VNIC. The VNIC is subject to all rules in all security…
The management plane controls the entire infrastructure. Parts of it will be exposed to customers independent of network location, so it is a prime resource to protect. Its graphical user interface, command line interface (if any), and API need to have stringent and role-based access control. In addition, logging of all relevant actions in a…