Insights
Product, design, AI, and engineering perspectives from our team.
SRE for Scale-Ups: Reducing Incidents Without a Team
Reliability incidents rising as you scale don't require a dedicated SRE team to fix — they require the right practices. Here's how CTOs can adopt error budgets, incident response, and on-call rotations with existing engineers.
Board-Level AI Literacy: A Director's Guide
Board-level AI literacy doesn't require directors to understand machine learning — it requires knowing what questions to ask. This guide sets out a practical framework for AI oversight grounded in existing directors' duties.
Data Mesh vs Centralised Data Platforms for Mid-Market Growth
Choosing between data mesh and a centralised data platform is an organisational decision as much as a technical one. This guide walks Australian scale-up leaders through team structure, governance overhead, and when each pattern fits.
AI for Insurance and Insurtech: A Practical Guide
A practical look at where AI genuinely fits in insurance and insurtech — underwriting support, claims triage, and fraud detection — and the data quality and explainability obligations Australian insurers need to get right first.
Building an Experimentation Platform for Product Teams
Moving from ad hoc A/B tests to a real experimentation platform means getting event tracking, statistical rigour, and feature-flagging right — together. Here's what that infrastructure actually requires.
Building an A/B Testing Platform for Product Teams
An experimentation platform stands on three pillars — event tracking, statistical rigour, and feature-flagging infrastructure. This article breaks down why ad hoc A/B testing breaks at scale and how to decide whether to build, buy, or combine.
FinOps for Engineering Leaders: Controlling Cloud Spend
Cloud spend rarely spikes overnight — it creeps until the AWS or Azure bill becomes a board-level issue. Here's a practical framework for Australian engineering leaders to structure account governance, attribute spend, and decide between SaaS tooling and embedded support.
Platform Engineering for Scale-Ups Without a Dedicated Team
Growing engineering teams don't need a dedicated platform team to get the benefits of platform engineering. This guide covers internal developer platform (IDP) patterns and golden paths that reduce cognitive load without a big hiring investment.
LLM Cost Optimisation: Cutting Spend Without Cutting Quality
Cutting LLM spend doesn't have to mean cutting quality. This guide covers the practical engineering levers — model tiering, prompt caching, batching, prompt budgets, and observability — with a worked example showing how they compound.