Guides
CTO Guides
Long-form guides for people running engineering organisations. Each one answers a decision rather than a topic, and each is written to be argued with.
Build vs Buy When Building Just Got Cheap
AI collapsed the cost of producing a feature and left the cost of owning it untouched. Why vibe coding, AI slop and seat-price pressure push the same decision the wrong way.
Read the guide →CTO Interview Guide: Questions & Prep
Complete CTO interview guide: common questions with sample answers, board presentation prep, salary negotiation, and red flags to watch for. 4-6 round process.
Read the guide →CTO vs VP Engineering: Role, Scope & Career Differences
CTO vs VP Engineering comparison: responsibilities, compensation ($450K-$650K vs $375K-$550K), career paths, org chart placement, and when to hire each.
Read the guide →Engineering OKRs That Work: Examples & Pitfalls
Real engineering OKR examples with measurable key results, plus the anti-patterns that make most engineering OKRs useless. From deployment frequency to developer experience.
Read the guide →Engineering Revenue Attribution: How CTOs Prove Tech Team ROI
How CTOs prove engineering ROI: revenue attribution models, measurement frameworks, and turning tech work into board-level financial impact.
Read the guide →How to Become a CTO: The Career Path
The complete career path from software developer to CTO: stages, timelines, skills at each level, and what the role actually involves in 2026. 12-18 year typical journey.
Read the guide →Beyond OKRs: Engineering Goal-Setting Frameworks
OKRs are over-applied. When they fail and what works better: North Star Metrics, Shape Up, continuous DORA improvement, and bet-based frameworks for engineering teams.
Read the guide →From Cost Center to Profit Center: The CTO's Playbook
Reframe engineering from cost center to profit center: the three moves that change the board conversation, plus the measurement infrastructure.
Read the guide →Technical Debt in the AI Era: A CTO Strategy
AI coding tools create 30-40% more defects on average. How CTOs should manage technical debt from AI-generated code: measurement, prevention, and remediation strategies.
Read the guide →Technical Debt Prioritization: The Framework CTOs Actually Use
How CTOs prioritize technical debt paydown. The RICE-D framework, impact mapping, and practical strategies for balancing debt work against feature development.
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