The engineering journal of HexTechGuide.
HexTechGuide is organized as a technical journal, not a conventional blog. We publish architecture reviews, production guides, field notes, incident analysis, and reference articles for teams operating AI and cloud systems in production.
The journal exists to document engineering knowledge that remains useful after individual vendors, frameworks, models, and cloud services change.
Issue 001: Production AI Systems
The first issue focuses on the operational layer of AI infrastructure: GPU inference, confidential computing, cyberdeception, adaptive agents, privacy-preserving threat intelligence, and lightweight publishing infrastructure.
Securing Data in Use: Hardware-Rooted Trust for Confidential AI
Security Architecture · Advanced · 9 min
An architecture review of confidential AI systems that protect sensitive data during computation using hardware-rooted trust, trusted execution environments, remote attestation, encrypted model delivery, and policy-based key management.
RAG-Driven Cyberdeception: Building High-Fidelity Adaptive Honeypots
Security Architecture · Advanced · 8 min
An architecture review of using Retrieval-Augmented Generation (RAG) to build adaptive cyberdeception platforms that generate realistic responses, synthetic assets, and high-fidelity interaction telemetry without exposing production environments.
Runtime Skill Injection: Building Adaptive AI Agent Platforms
AI Infrastructure · Advanced · 10 min
An architecture review of runtime skill injection and adaptive AI agent platforms that evolve through deployment-time capabilities rather than static post-training updates.
Privacy-Preserving Threat Intelligence: Designing Collaborative Detection Systems
Security Architecture · Advanced · 9 min
An architecture review of collaborative threat intelligence platforms that preserve organizational privacy through federated learning, graph-based analytics, causal reasoning, and privacy-preserving data sharing.
Operating GPU Inference at Scale: A Production Checklist
Engineering · Intermediate · 8 min
A vendor-neutral production checklist for operating GPU inference workloads with Kubernetes scheduling, runtime health probes, secrets, observability, scaling, and rollback planning.
Building a Zero-Database Flat-File Publishing Platform with Flask
Python Systems · Intermediate · 9 min
Designing a lightweight publishing platform does not always require a database or content management system. This article explores a flat-file architecture using Flask, Markdown, and in-memory caching to build a fast, maintainable engineering publication.
Deploying Python WSGI Applications on Managed Shared Hosting
Python Systems · Intermediate · 8 min
A production guide for deploying Python WSGI applications on managed shared hosting platforms using Flask, Passenger, clean routing, predictable directory structures, and efficient static asset delivery.
Field Note
Practical observations from real engineering, deployment, infrastructure, or operations work.
Production Guide
Implementation-focused guidance for deploying, scaling, securing, and operating systems.
Architecture Review
Analysis of system design, platform patterns, trade-offs, constraints, and operational consequences.
Incident Analysis
Failure-driven learning from outages, misconfiguration, resource exhaustion, routing errors, and recovery work.
Reference
Evergreen explanations of durable engineering concepts that outlive specific products or versions.
Architecture first. Vendor second.
HexTechGuide intentionally separates engineering patterns from vendor marketing. Products may appear as examples, but the center of each article is the system: how it is designed, operated, secured, observed, and recovered.
This editorial position allows the journal to stay useful even as AI models, inference runtimes, cloud services, and deployment platforms evolve.
AI Infrastructure
GPU inference, model serving, RAG systems, embedding services, AI gateways, runtime design, and scaling patterns.
Security Architecture
Confidential computing, threat detection, cyberdeception, secrets, identity, runtime security, and data protection.
Cloud Architecture
Landing zones, networking, identity, private endpoints, storage, disaster recovery, and cost constraints.
Kubernetes
Scheduling, node pools, probes, ingress, operators, Helm, autoscaling, storage, and cluster operations.
Python Systems
Flask, FastAPI, WSGI, automation, background jobs, application deployment, and performance behavior.
Reliability Engineering
Observability, SLOs, incident response, monitoring, alerting, health checks, runbooks, and recovery procedures.