Tags
intermediate
10 publicationsUltralearning in a Polarized Labor Market
An essay on education, self-study, and deliberate learning as a technical and human response to an increasingly polarized labor market.
npm's supply chain is broken — the Axios attack explains why
Technical analysis of the Axios npm supply chain attack in March 2026: what happened, what the malware did, why CI/CD is the real target, and how to protect yourself.
When AI Stops Being a Tool and Becomes an Attack Surface
When AI becomes an attack surface: prompt injection, end-to-end attack chains, at-risk architectures, and defensive actions.
Device Code Phishing + Vishing: How Attackers Compromise Microsoft Entra Accounts Using Legit Login Pages
Device code phishing combined with vishing targeting Microsoft Entra: how the OAuth flow gets abused, what to monitor, and how to mitigate.
The State of the Art in AI Agents (2026): What ‘Modern’ Actually Means
A practical overview of modern AI agent systems: tool use, retrieval, memory, verification, multi-agent patterns, evaluation, and security.
Separation of Responsibilities in Spring-Based Systems: What Kotlin Makes Explicit
How Kotlin's type system sharpens responsibility boundaries in Spring-style architectures without replacing architectural discipline.
The Skills Required to Truly Learn
A reflective essay on learning as disciplined endurance of uncertainty, revision, and silence.
The Cost of Abstraction: When Layers Hide Security and Reliability Risks
Argues that abstraction layers can obscure failure modes, shift risk across boundaries, and weaken assurance unless their assumptions are made explicit.
Why Traditional Threat Modeling Breaks Down in Generative AI Systems
Probabilistic behavior, distributional risk, and system composability invalidate core assumptions of classical threat modeling for generative AI.
Why Most Postmortems Miss the Real Failure Mode
Postmortems often substitute proximate triggers for causal structure, obscuring system dynamics and latent conditions that drive failure.