#Automation
Articles about Automation — exploring patterns, best practices, and real-world implementations in production systems.
6 posts tagged with automation. ← All posts
Beyond the interactive terminal, Claude Code can run headless in scripts and CI — which unlocks automation, and raises the stakes on permissions, review, and trust.
The capstone: running Claude Code headless in scripts and CI (PR review, batch ops, scheduled jobs) — and the guardrails it demands: least privilege, sandboxing, gating the produced artifact with human review, and the series' layered recap.
The series finale — where LLM reviewers genuinely help on every pull request, where they quietly fail, and how to build a human-plus-AI workflow that speeds review up without letting judgment or accountability leak away.
The capstone: using AI/LLM reviewers well and where humans stay essential — AI as a tireless first pass that clears the noise, its limits (design judgment, contextual security, accountability, hallucinations), and a healthy human+AI division of labor.
How to run code review across a whole team or organization without turning it into a bottleneck: treat review latency as a first-class metric, distribute the load, let automation handle the toil, and measure the things that actually predict quality.
Making review work across a team without becoming a bottleneck: review velocity as a first-class metric, ownership and routing (CODEOWNERS), automating toil so humans do judgment, healthy SLAs, and measuring the right things.
Hooks turn "please always run the formatter" from a hope into a guarantee — deterministic shell commands that fire on Claude Code's lifecycle events, no matter what the model decides.
Hooks are shell commands that fire deterministically on lifecycle events — auto-format on edit, block edits to protected paths, run checks, notify. When to use a hook (guarantee) vs CLAUDE.md (influence) vs permissions (gate), and keeping them safe.
Scaling red-teaming beyond manual probing — the building blocks of an automated harness (seed library, mutation, orchestrator, scorer), LLM-driven adaptive attackers, the real tools by role (PyRIT, garak, promptfoo, Giskard), and wiring it all into CI as a repeatable gate.
Scaling red-teaming: the harness building blocks (attack seeds, mutation, orchestrator, scorer), adaptive LLM-driven attackers, the real tools by role (PyRIT, garak, promptfoo, Giskard), and integrating an automated red-team gate into CI.
The opening post of a DevSecOps series — how security stops being a gate at the end of delivery and becomes an automated, shared responsibility built into every stage of the pipeline.
The opener to a DevSecOps series: building security into the delivery lifecycle instead of bolting it on — shift-left (and shift-right), security as everyone's job, the CI/CD pipeline as the enforcement point, and the automated controls the series wires up.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.