Insights
Product, design, AI, and engineering perspectives from our team.
AI Product Strategy Consulting Guide for Australian Companies
A comprehensive guide to AI product strategy consulting for Australian mid-market companies. Explore frameworks, methodologies, and selection criteria to help CTOs make informed decisions about AI adoption.
The AI Hype Cycle: What's Real and What Matters for Business
The AI market promises transformation but most projects fail due to unrealistic expectations. This guide examines which AI capabilities work in production versus research, helping business leaders make investment decisions based on technical reality rather than hype.
Computer Vision for Business: Beyond Facial Recognition
Computer vision transforms how Australian businesses inspect quality, count inventory, digitise documents, and monitor safety through AI automation. From manufacturing to mining, practical computer vision applications deliver measurable ROI beyond facial recognition headlines.
Software Acquisition Due Diligence: A Technical Assessment Framework
Software acquisitions require systematic technical assessment to understand the real value and risk beneath polished demos. Technical due diligence reveals architecture quality, technical debt, team capability, and scalability constraints that affect integration success and long-term value creation.
AI-Powered Code Generation: What It Can and Can't Do
AI coding tools like GitHub Copilot promise faster development but introduce new security and quality risks. Here's what engineering leaders need to know about safe adoption.
Production AI Agents: Architecture and Deployment Lessons
Production AI agents require careful orchestration, robust failure handling, and strategic human oversight. The gap between proof-of-concept and production-ready agents is significant — here's what actually works.
AI and Intellectual Property: Who Owns What When AI Generates Content?
AI-generated content creates complex ownership questions that traditional Australian IP law wasn't designed to handle. Understanding these challenges is critical for protecting investments and avoiding disputes.
SOC 2 Compliance for AI-Powered Applications: A Technical Guide
SOC 2 compliance for AI applications requires addressing traditional security controls alongside AI-specific risks like model governance and training data handling. This technical guide covers the key implementation strategies for building compliant AI systems.
Securing API Endpoints for AI Applications: OWASP Best Practices
AI APIs require layered security addressing traditional vulnerabilities and AI-specific threats like prompt injection and model extraction. Learn OWASP best practices for protecting endpoints from data breaches and service disruption.