Engineering insights from the CodeDig team.
An inside look at how CodeDig assigns a risk score to every pull request — combining blast radius, code complexity, security findings, and historical patterns into a single actionable signal.
Read more →Linters, formatters, and static analysis tools tell you what is wrong with the code. They do not tell you what could go wrong when it ships. Here is why impact context is the missing layer in code quality.
Read more →When reviewers approve changes without understanding impact, the cost shows up in incident response, rework cycles, and eroded deployment confidence. Here is how blast radius context changes the economics of code review.
Read more →Most security scanning happens after the merge — when the cost of fixing is highest. Here is how shifting security analysis to pull request time changes the economics of vulnerability remediation.
Read more →PR gates, risk scoring, blast radius checks, and security scanning form an engineering governance stack that scales across teams. Here is how to build one — and where CodeDig fits in.
Read more →The diff shows you what changed — but it hides who depends on that change. Here is why blast radius is the missing signal in every PR review, and how teams can start catching risks before they merge.
Read more →A walkthrough of how CodeDig works as a GitHub App — from one-click installation to real-time PR analysis, Check Runs, and security scanning with zero configuration.
Read more →A technical look at how CodeDig calculates the blast radius of a pull request — from symbol resolution and dependency graph traversal to impact scoring.
Read more →Traditional code analysis tools run after the merge. We built CodeDig to give engineering teams actionable risk intelligence at the exact moment they need it — during the pull request review.
Read more →Today we are launching CodeDig — a developer tool that analyzes every pull request for risk, security vulnerabilities, and architectural impact before it reaches production.
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