Your central hub for the latest AI models, DevSecOps tools, best practices, and curated resources. Built by practitioners, for practitioners.
Stay updated with the newest large language models, multimodal systems, and specialized AI tools transforming DevSecOps workflows.
Latest: Feb 2026 (Opus 4.6) / Sept 2025 (Sonnet 4.5) | Context: 200K
tokens
Industry-leading for agentic coding, computer use, and tool use. Sonnet 4.5 set benchmark records in coding
and reasoning. Includes Claude Agent SDK for building autonomous DevSecOps agents.
Latest: 2025-2026 | Context: 128K tokens
Multimodal capabilities with vision, faster inference, and enhanced function calling. GPT-4.5 brings
improved reasoning. Ideal for multi-step automation and real-time alerting.
Release: 2024-2025 | Context: Up to 128K tokens
Open-source powerhouse available in multiple sizes (8B to 405B parameters). Llama 3.3 70B matches 405B
performance at lower cost. Deploy locally for air-gapped environments.
Release: December 2025 | Context: 1M+ tokens
Next-generation multimodal AI with native agentic capabilities. Massive context window for analyzing entire
codebases, logs, or documentation in a single pass. Built-in search grounding.
Release: 2025-2026 | Context: 128K tokens
Cost-effective open models rivaling GPT-4. DeepSeek V3 (671B MoE) offers incredible value. R1 brings
chain-of-thought reasoning. Great for self-hosting DevSecOps workloads.
Focus: Code generation, multilingual, and analysis
Qwen 2.5 excels in multilingual and code tasks with models from 0.5B to 72B. CodeLlama and StarCoder2 are
fine-tuned for vulnerability detection and refactoring.
Modern tools integrating AI for smarter pipelines, proactive security, and autonomous operations.
Snyk: AI-powered vulnerability detection with auto-remediation suggestions
GitGuardian: Secret detection with ML-based false positive reduction
Semgrep: Static analysis with custom rule creation via LLMs
GitHub Actions: Copilot-assisted workflow generation
GitLab CI: Predictive pipeline optimization
Argo CD: GitOps with intelligent drift detection
Datadog: AI-powered anomaly detection and root cause analysis
New Relic: Automatic instrumentation and intelligent alerting
Grafana Loki: Log aggregation with natural language queries
Terraform: IaC generation via AI coding assistants
Kubernetes: Autopilot clusters with self-healing capabilities
AWS/GCP/Azure: Native AI ops services (CloudWatch Insights, etc.)
Copilot Testing: AI-generated unit and integration tests
Mabl: Intelligent test automation with self-healing locators
Katalon: AI-augmented test orchestration and analytics
Claude Agent SDK: Build autonomous DevOps agents
LangChain: Chain LLM calls for complex automation workflows
OpenAI Assistants: Persistent agents with tool use and file access
Explore my open-source DevSecOps projects, automation scripts, and AI experiments.
This website! A wiki-style resource for AI models and DevSecOps tools. Blue-green deployment on AWS EC2 with GitHub Actions CI/CD.
View Repository →Bash automation script for troubleshooting Kubernetes pods. Collects logs, describes resources, and checks common misconfigurations.
View Repository →Python tool for managing Elasticsearch index retention policies. Automates deletion of old indices based on age or size thresholds.
View Repository →Ansible playbook for automated server security hardening. Configures SSH, firewall rules, fail2ban, and security updates.
View Repository →Check out my full GitHub profile for additional repositories, contributions, and experiments in DevSecOps, AI, and cloud infrastructure.
GitHub Profile →The five biggest shifts in AI-powered DevSecOps happening right now in 2026.
2026 marks the shift to fully autonomous AI agents in DevSecOps pipelines — not just code assistants, but agents that plan, execute, and self-correct across build, test, deploy, and monitoring workflows with Claude Agent SDK and similar frameworks.
AI models with computer use capabilities (like Claude Opus 4.6) can directly interact with infrastructure UIs, terminals, and cloud consoles — enabling natural language infrastructure management and autonomous incident response.
Security tools now leverage LLMs for continuous policy reasoning, threat modeling, and compliance mapping. AI analyzes attack surfaces in natural language, generating remediation plans that adapt to your specific architecture.
Model Context Protocol (MCP) standardizes how AI models interact with external tools and data sources. GitHub's MCP Registry and similar platforms are creating unified ecosystems for AI-powered DevSecOps workflows.
2026 sees explosive growth in open models (DeepSeek V3, Qwen 2.5, Llama 3.3) that match closed-model performance at 10-100x lower cost. Self-hosted LLMs for DevSecOps are now enterprise-viable for sensitive workloads.
With software supply chain attacks surging, AI now analyzes dependency graphs, detects malicious packages in real time, generates SBOMs automatically, and monitors open-source ecosystems for compromised libraries before they reach your pipeline.
Essential resources for staying current with AI developments and DevSecOps best practices.
Hugging Face Models
— Largest collection of
open-source models
Ollama Library — Local
model deployment made
easy
Open LLMs
List — Curated list of
open-source LLMs
arXiv AI
Papers — Latest academic
research
AI Snake Oil —
Critical analysis of AI
claims
Simon Willison's Blog —
Practical AI insights
r/devops —
Active Reddit community
r/netsec —
Security discussions
DevOps Community — Slack
workspace
DeepLearning.AI —
Andrew Ng's AI courses
Google Cloud
Skills — Free cloud/AI
training
Microsoft Learn DevOps —
Azure DevOps paths
Play with
Docker — Free Docker
sandboxes
KillerCoda — Interactive
Kubernetes & DevOps
labs
LMSYS Chatbot Arena —
Compare AI models head-to-head
OWASP DevSecOps —
Industry-standard security guidelines
NIST SSDF —
Secure Software Development
Framework
CISA SBOM — Software
Bill of Materials standards