Insights
Product, design, AI, and engineering perspectives from our team.
Designing Technical Assessment Frameworks for AI/ML Hiring
Hiring in-house AI and ML engineers requires a different interview loop to general software hiring — and a different lens to evaluating AI vendors. This guide sets out how data and engineering leaders can structure interview loops and take-home assessments to test ML judgement, not just code.
Engineering Documentation That Survives Team Turnover
As engineering teams scale, critical system knowledge often lives in one person's head. This guide covers how architecture decision records, runbooks, and onboarding documentation reduce single points of failure and keep knowledge inside the organisation.
Engineering Leadership Succession Planning During a CTO Exit
A CTO exit puts delivery velocity, architectural continuity, and team retention at risk if handled as a recruitment problem alone. Here's how to structure interim leadership, preserve institutional knowledge, and protect momentum during the transition.
Quantifying Technical Debt: A Business Case Your Board Approves
Boards fund reduced risk, protected revenue, and faster time to market — not "code quality." This article shows how to translate technical debt into cost of delay, risk exposure, and opportunity cost, with a board-ready register template.
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.
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.
DORA Metrics for Mid-Market Engineering Teams
DORA metrics are the clearest read on engineering delivery performance, but most guidance is written for large platform teams. Here's how a 10-50 person engineering team can instrument DORA cheaply, benchmark realistically, and account for AI-assisted development shifting the baseline.
Technology Roadmap Planning: Aligning Tech with Business Goals
A technology roadmap bridges business strategy and engineering execution. Learn how to build roadmaps that translate business objectives into technical initiatives with clear success metrics.