#CI/CD

Articles about CI/CD — exploring patterns, best practices, and real-world implementations in production systems.

7 posts tagged with ci/cd. ← All posts

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Pratik Dhanave · ·6 min read

Claude Code in Production Workflows

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.

#Claude Code#CI/CD#Automation#AI#AI Agents#Guardrails
Pratik Dhanave · ·12 min read

SAST, DAST, and Security Testing in CI

How the four families of automated security tests — static analysis, dynamic analysis, secret scanning, and instrumented runtime testing — fit together across a pipeline, and why tuning signal-to-noise matters more than adding scanners.

Automated security testing in the pipeline: SAST vs DAST vs IAST and their trade-offs, secret scanning (including git history), where each runs, and making findings actionable so false-positive fatigue doesn't get the scanner muted.

#DevSecOps#SAST#DAST#CI/CD#Security#Testing
Pratik Dhanave · ·14 min read

Evaluation and Quality Gates

Governance is only as real as your ability to measure it. This is the MEASURE function of an AI risk program made concrete — a versioned eval set, the metric families that matter for an LLM system, and a CI gate that fails the build when quality regresses instead of just logging a warning.

Governance enforced through evaluation — the Measure function made real: build a versioned eval set, pick the metric families (quality, faithfulness, safety, bias, PII, cost/latency), and turn eval into a CI quality gate that fails the build on regression.

#AI Governance#Evaluation#CI/CD#LLMs#Governance
Pratik Dhanave · ·13 min read

Agent Evaluation in CI: Regression Gating

How to wire agent evaluations into continuous integration in Go — running a slow, model-calling eval harness under `go test`, setting per-metric thresholds that fail the build on a regression, and living honestly with the fact that these gates are softer than unit tests.

How to wire agent evaluations into continuous integration in Go — running a slow, model-calling eval harness under `go test`, setting per-metric thresholds that fail the build on a regression, and living...

#AI Agents#Evaluation#Go#CI/CD#Backend Engineering#Testing
Pratik Dhanave · ·11 min read

What DevSecOps Is

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.

#DevSecOps#Security#CI/CD#Automation
Pratik Dhanave · ·5 min read

Testing Agents Without a Model

The full pipeline should run in CI with zero API keys and zero network. A deterministic classifier is the test double that makes an agentic system testable.

Put the seam at the router: same interface, a deterministic classifier for tests. The whole orchestration, routing, gateway, human-in-the-loop, and checkpointing, runs in CI with zero API keys and zero network.

#Agentic AI#Testing#Engineering#CI/CD#Multi-Agent Systems#APIs
Pratik Dhanave · ·6 min read

An Eval Regression Gate in CI

Treat agent output quality like a test. A baseline file plus a gate that fails the build on regression turns "the agents got worse" into a red X.

Agent systems rot because nobody catches quality regressions until users do. A committed baseline plus a gate that fails the build turns the agents got worse into a red X and a reviewable diff in the pull request.

#Agentic AI#Evaluation#Testing#CI/CD

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.