Technical insights on AI code quality, hallucination detection, and codebase health
The AI Slop Index is a single number — 0 to 100 — that measures how much unreviewed AI-generated code lives in your codebase. Phantom imports, hallucinated APIs, copy-paste patterns, dead code — each one adds to your score. Here's what it measures, how it's calculated, and why investors and CTOs are starting to ask for it.
Read more →Every file has a story — what it does, what depends on it, what would break. Mother Code DNA embeds that story directly in the source as structured, machine-readable comment blocks. Validated against reality on every scan, it turns tribal knowledge into version-controlled metadata that survives team turnover.
Read more →“We have some tech debt” is the most common lie in software engineering. Thuban calculates the actual cost in pounds and dollars — complexity score × engineer hours × hourly rate. See a realistic case study of a 50K LOC SaaS app carrying £40K of tech debt, and learn why boards approve remediation sprints when you give them a number.
Read more →ESLint checks syntax. SonarQube checks patterns. Neither was built for AI-generated code. Phantom imports, hallucinated packages, deprecated APIs that still parse — these are the problems that slip through every existing quality gate. Here's the gap, and why a new category of tool exists to fill it.
Read more →Before you pitch to investors, run this checklist. AI-built codebases have unique risks that traditional due diligence misses entirely — phantom imports, hallucinated APIs, committed secrets, and zero documentation. Here are the ten things you need to verify before the investor's technical advisor does it for you.
Read more →AI coding tools invent modules that don't exist. They swap function names, drop package suffixes, and reference deprecated APIs — all with complete confidence. Here's how to find phantom imports before they crash your production build, with real examples from lodash, Flask, Next.js, Supabase, and Node.js.
Read more →AI coding tools ship code 10x faster. They also ship tech debt 10x faster. We break down the formula for calculating what AI-generated tech debt actually costs your team per month — with real numbers from Thuban scans — and a practical playbook to reduce it.
Read more →We built 8 increasingly sophisticated systems to make an LLM verify its own code output. Retry logic, circuit breakers, async pipelines, persistent state. Every iteration made the delivery more reliable. None of them made the answer more accurate. Here's why external verification is the only approach that works.
Read more →We pointed Thuban at Express, Next.js, Strapi, Fastify, Ghost, Socket.io, Meteor, Sails, Keystone, and AdonisJS. 2,041 issues across 10 repos. AI hallucinations in production frameworks. Deprecated APIs that have been there for years. We also found 5 categories of our own false positives — and fixed every one before publishing. Full transparency.
Read the full audit →SonarQube charges $34/dev/month. Snyk charges $25/dev/month. Thuban charges $9/month flat for Pro, $49 for a team of 50. How? Because we don't run your code on our servers — you do. No cloud compute costs, no sales team, no enterprise theatre. Same depth, radically different economics.
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