
AI Prompts for Code Review: How to Get Genuinely Useful Feedback From an LLM on Someone Else’s Code
Use context-rich prompts, focused roles, and structured output to get actionable AI feedback on PR diffs, security, performance, and logic.
Blog
Field notes on shipping AI-native systems with human engineering judgement: architecture, modernisation, automation, and the tradeoffs in between.

Use context-rich prompts, focused roles, and structured output to get actionable AI feedback on PR diffs, security, performance, and logic.

An 8-step AI prompt workflow that turns rough ideas into structured PRDs, user stories, edge-case checks, and prioritized features.

Use precise AI prompts to map, test, and safely fix legacy code-surface assumptions, generate characterization tests, and minimize risk.

Nine copy‑paste AI prompts to debug React, migrate components, write tests, boost performance, and improve accessibility.

Handover checklist to ensure operational independence, reduce post-handover incidents, and let teams run outsourced code day one.

Practical framework to vet frontend partners for complex state: map state domains, test architecture, performance, testing, and governance.

Week 1 onboarding for outsourced frontend teams: risk mapping, env setup, UX handoff, communication rules, and a first merged PR.

Compare augmentation vs dedicated squads for unstable frontends: risks, onboarding, retention, and cost.

A modular, JSON-based open standard slashes integration costs, speeds SaaS development, and enables modular pricing in construction.

Six-stage pipeline for extracting pharma secondary sales from PDFs/Excels, covering failures, validation, reconciliation, and monitoring.

Design Document AI pipelines with redaction, tamper‑evident logs, strict access controls, and vendor BAAs to pass compliance audits.

Practical template to stress-test Document AI vendors with real edge cases, accuracy metrics, privacy checks, and contract safeguards.