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Local-first AI
AI PDF Reader combines retrieval, local models, desktop packaging, and product UX.
Architecture · Cloud · Security
I design cloud and AI systems with security, clarity, and real-world use in mind.
Peru N · Software Architect · Cloud Engineer · Security Engineer
I design secure, scalable software systems and turn complex cloud or AI workflows into products that feel clear, usable, and trustworthy.
Featured projects
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Deep-dive blogs
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Primary repo
Agentic IaC Reviewer
Software ArchitectCloud EngineerSecurity EngineerTechnical Leadership
Recent architecture work
Product architecture, trust boundaries, and delivery decisions across recent projects.
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Cloud platforms
Platform and landing zone work focused on governance, delivery, and operational clarity.
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Security design
Threat models, trust boundaries, and secure delivery decisions are part of the project story.
Featured case studies
Projects that show systems thinking, cloud execution, and secure design
Selected projects with architecture visuals, security analysis, and implementation outcomes.
2026-06-23
Agentic Kubernetes IaC Security Reviewer
Combined deterministic security scanning with bounded agent remediation to make infrastructure findings easier to trust and act on.
Built an agent-assisted CLI that turns Kubernetes, Terraform, and Dockerfile scanner output into prioritized security reviews, control-backed explanations, and safely staged remediation artifacts.
Security EngineeringPlatform EngineeringDevSecOpsAI Products
• Turned raw infrastructure scan output into a prioritized review workflow engineers can act on faster.
• Added control-backed explanations that make findings easier to defend in platform and security discussions.
• Reduced remediation risk by staging generated fixes outside the source tree with bounded retry logic.
2026-04-17
AI PDF Reader
A private, local-first document AI product with grounded retrieval, desktop packaging, and strong UX.
Built a local-first AI PDF Reader that lets users upload documents, retrieve grounded answers, generate study guides, and run as both a web app and offline desktop experience.
AI EngineeringSoftware ArchitectureLocal-First AISecurity Engineering
• Delivered a product that can run in browser mode or as a desktop app for Windows and macOS.
• Combined PDF parsing, chunking, embeddings, retrieval, and local LLM answers into one polished workflow.
• Improved privacy posture by supporting local GGUF models and offline packaging for sensitive document use cases.
2025-11-08
Secure Developer Platform and Landing Zone
Turned fragmented cloud onboarding into a governed self-service platform.
Built a secure internal developer platform with standardized landing zones, golden pipelines, observability baselines, and policy controls for multi-team cloud delivery.
Cloud EngineeringLanding ZonesDevSecOpsGovernance
• Cut environment provisioning from weeks to less than one day.
• Improved policy compliance with standardized identity, network, and logging baselines.
• Increased developer confidence through reusable pipeline templates and guardrails.
Notes
Writing on architecture, delivery, and security
Short pieces on platform design, technical decisions, and implementation patterns from recent work.
Security Architecture•2026-06-23•6 min
What This Agentic IaC Security Reviewer Says About My Architecture Style
This project shows how I turn noisy infrastructure security findings into an explainable, remediation-focused workflow by combining proven scanners with bounded agent reasoning.
Security ArchitecturePlatform EngineeringAI Products
Read insightAI Product Engineering•2026-04-17•7 min
Building AI PDF Reader as a Real Product, Not Just an AI Demo
The difference between an AI demo and an AI product is everything around the model: UX, retrieval quality, runtime setup, packaging, trust, and documentation.
AI EngineeringProduct ThinkingTechnical Leadership
Read insightSoftware Architecture•2026-04-17•6 min
Architecture Lessons from AI PDF Reader
AI PDF Reader brings together product architecture, privacy, retrieval quality, and delivery discipline in one local-first system.
Architecture ReviewsSoftware ArchitectureAI Products
Read insightSecurity Engineering•2026-04-17•6 min
Threat Modeling a Local-First AI Desktop App
Local-first AI products feel safer by default, but they still need careful threat modeling around files, models, prompts, packaging, and desktop boundaries.
Threat ModelingDesktop SecurityLocal AI
Read insightElsewhere
Links
GitHub, LinkedIn, email, and project links.