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Articole: 156
  1. A CVE scanner tells you if a package has known vulnerabilities.

  2. How and why I built an n8n automation that picks a new tool every week: the topic rotation, the two-agent pick-then-write pipeline, and the actual prompts behind it.

  3. A hands-on run of Tejolote against a real GitHub Actions build: SLSA provenance, a workflow-YAML parser crash, and a run-status race that quietly drops artifacts.

  4. A hands-on walkthrough of ThreatCaddy, a local-first threat investigation workspace built on IndexedDB.

  5. Prototype to production: A deep dive into Dify, the self-hostable LLM app runtime.

  6. How to use Tailscale subnet routing on an OpenWrt router to give every device on your WiFi network direct access to Kubernetes ClusterIP services -- without installing Tailscale on each device.

  7. The complete before-and-after of a cloud infrastructure overhaul done with Claude Code: what was deleted, what was created, what broke, and what I learned. $124/month saved, $1,488/year.

  8. How I used Tailscale to create a private mesh between my OpenWrt home router, Kubernetes cluster, and personal devices -- giving me access to internal services without public endpoints.

  9. How I turned a Raspberry Pi 5 into a full home router running OpenWrt, complete with firewall rules, WiFi AP, ad blocking, and bandwidth monitoring.

  10. How I replaced a DigitalOcean Load Balancer and App Platform with a free Cloudflare Tunnel, including the DNS migration that almost broke everything and deploying cloudflared via Terraform.

  11. The detailed, sometimes messy story of migrating 7 Hugo static sites from a Kubernetes nginx pipeline to Cloudflare Pages -- including debugging Hugo quirks, fixing CI/CD bugs, and building a production deployment workflow.

  12. How I used Claude Code's CLI to audit my DigitalOcean infrastructure, discovered orphaned resources costing me money, and built a plan to slash my cloud bill by 63%.

  13. A deep dive into mitmproxy for security testing.

  14. Not productivity theater — real scripts I run daily, with before/after time savings, what failed, and exactly why each one earned its place in my toolkit.

  15. Kubernetes Secrets aren't actually secret by default.

  16. AI is changing technical work.

  17. Containers aren't magic security boundaries.

  18. Error Debugging with AI: Beyond Stack Overflow

    AI changes debugging from pattern-matching against old answers to a genuine diagnostic conversation about your specific problem.

  19. Documentation is everyone's least favorite task.

  20. The AI tool landscape is overwhelming.

  21. AI-Assisted Code Review: A Practical Framework

    Code review is where AI collaboration gets interesting.

  22. Cross-Platform Scripting Tips and Tricks

    Practical solutions for writing scripts that work across Windows, macOS, and Linux.

  23. Measuring Your AI Collaboration Effectiveness

    Learn to measure what matters in human-AI collaboration.

  24. When to Trust (and Verify) AI Output

    Learn to calibrate your trust in AI suggestions.

  25. Building AI-Assisted Security Tools

    Apply the Centaur framework to security tooling.

  26. AI Pair Programming: Beyond Code Completion

    Move beyond basic autocomplete to true human-AI collaboration.

  27. Learn to build a production-grade network port scanner in Python from scratch, covering TCP connect scanning, SYN scanning, service detection, multi-threading, and ethical considerations.

  28. The Centaur's Toolkit

    Download the free companion resources for The Centaur's Edge.

  29. Practical guide to security automation scripting with Python and Bash, covering log analysis, vulnerability scanning, incident response automation, and API integration with working examples.

  30. Deep dive into advanced Linux networking including network namespaces, policy-based routing, traffic shaping, VXLANs, and eBPF for network observability and control.

  31. Explore the ethical challenges of using AI in cybersecurity, including algorithmic bias, privacy concerns, adversarial use, and frameworks for responsible AI security implementation.

  32. Learn how to leverage AI and machine learning to analyze security logs, detect anomalies, identify threats, and automate log analysis workflows using Python and open-source tools.

  33. A technical deep dive into using AI and machine learning for automated incident response, covering threat detection, containment workflows, and remediation automation with practical examples.

  34. Learn how to leverage AI and machine learning to analyze log files for security threats.

  35. A hands-on account of migrating a technical blog from WordPress to Hugo, including theme selection, content migration challenges, and CI/CD automation lessons learned.

  36. Examine open-source AI model implications: Apache 2.0 vs restrictive licenses, deployment patterns, security risks, and business impact using Llama 2, Mistral, and other major releases as case studies.

  37. Balance AI productivity with critical thinking using the Centaur Mindset framework.

  38. Analyze AI-generated code security: vulnerability patterns, data poisoning attacks, bias detection, and secure implementation strategies for Copilot/ChatGPT-generated code.

  39. Execute Gemini 2.5 Pro locally via CLI: 1M token context window, 60 RPM limit, Apache 2.0 license.

  40. Production WebAuthn/FIDO2 passkey implementation with complete registration/authentication flows, server-side verification, cross-platform syncing, and security analysis.

  41. Build production-grade AI-powered vulnerability scanning systems using OpenAI GPT-4 API.

  42. Implement Anthropic MCP with Azure Blob Storage: client-server architecture, RBAC policies, Redis caching, SSE streaming, and Prometheus monitoring for AI-data integration.

  43. Reduce AI chatbot energy costs with codecarbon metrics, GPT-4/Gemini benchmarking, model quantization, caching strategies, and carbon-aware deployment optimization.

  44. Scan AI-generated code with Endor Labs: integrate SAST/DAST for Copilot/Cursor output, GitHub Actions workflows, custom regex rules, and pre-commit hooks for DevSecOps.

  45. Build production-grade resilient distributed systems with circuit breakers, service mesh, chaos engineering, distributed tracing, and AI-powered failure prediction.

  46. Fabricate PCBs with fiber lasers: 20W laser etching, copper trace cutting, solder mask application, and SMD component assembly.

  47. Boost productivity with GitHub Copilot for VS Code: AI-powered code completion, natural language prompts, prompt engineering, and security best practices for developers.

  48. Deploy GenAI pipelines on Azure with Azure OpenAI Service, prompt engineering, model monitoring, AKS deployment, and CI/CD integration.

  49. Transform e-commerce with AI-powered product recommendations, automated content generation, personalized search, and conversion optimization using collaborative filtering and LLMs.

  50. Enhance vulnerability discovery with AI-powered fuzzing: reinforcement learning input generation, coverage-guided testing, and automated exploit development techniques.