Topics on CTO Field Notes https://avivzaken.com/topics/ Browse CTO Field Notes by topic: engineering leadership, AI-assisted engineering, software delivery, and technical risk. Hugo en-us Fri, 11 Sep 2026 00:00:00 +0000 Technical Risk https://avivzaken.com/topics/technical-risk/ Fri, 11 Sep 2026 00:00:00 +0000 https://avivzaken.com/topics/technical-risk/ Aviv Zaken Field notes on technical risk: code review, software quality, technical debt, refactoring, and the cost of being wrong. Technical risk is shaped by the cost of being wrong and the difficulty of recovery. These field notes connect code review, software quality, technical debt, and refactoring to the same operating concern: whether a team can change a system with enough evidence, understanding, and reversibility to trust the outcome.

Not every change deserves the same control. Review depth should follow consequence. Debt is useful when its cost and repayment path are understood. Tests and evals should prove the behavior that matters, not merely produce a green check.

Technical Risk Field Notes#

Evals Are the New Tests

In April 2025 OpenAI shipped a model update whose offline evals and A/B tests all looked good. It was sycophantic enough to roll back within days. A practical guide to building the measurement layer that would have caught it - with a working eval spec and grading rubric.

Code Was Never the Bottleneck

Your engineers are producing more code and your delivery cadence has barely moved. The waiting did not disappear - it moved downstream to review and absorption, and that is where the constraint always was. Includes a review-capacity audit.

]]> Software Delivery https://avivzaken.com/topics/software-delivery/ Fri, 11 Sep 2026 00:00:00 +0000 https://avivzaken.com/topics/software-delivery/ Aviv Zaken Practical field notes on software delivery, product strategy, startup engineering, and shipping reliably under uncertainty. Reliable delivery is not raw output. It is the ability to turn uncertain work into small, testable, reversible increments while keeping the team close to real feedback. These field notes cover roadmaps as trade-offs, experiments as learning systems, feature design, refactoring, and the operating practices that let startups keep shipping without losing control of their velocity.

The shared theme is reducing the cost of learning. Smaller bets expose wrong assumptions earlier. Clear measures separate motion from progress. Continuous refactoring keeps future changes affordable.

Software Delivery Field Notes#

]]> Engineering Leadership https://avivzaken.com/topics/engineering-leadership/ Fri, 11 Sep 2026 00:00:00 +0000 https://avivzaken.com/topics/engineering-leadership/ Aviv Zaken Practical field notes on engineering leadership, team design, technical strategy, engineering metrics, and resilient delivery. Engineering leadership is the work of turning uncertainty into decisions a team can execute and own. These field notes examine how leaders design teams, choose useful signals, protect delivery, and decide where human judgment matters as AI changes the economics of producing code.

They address practical questions: How should a CTO measure whether AI improved delivery rather than output volume? How can a senior-dense team keep developing future engineers? Which weak signals deserve action before friction becomes an incident? How should leaders preserve predictability when the roadmap and the system are both changing?

Engineering Leadership Field Notes#

]]> AI-Assisted Engineering https://avivzaken.com/topics/ai-assisted-engineering/ Fri, 11 Sep 2026 00:00:00 +0000 https://avivzaken.com/topics/ai-assisted-engineering/ Aviv Zaken Field notes on AI-assisted software engineering, including review capacity, evals, engineering metrics, and team design. AI-assisted engineering makes code faster to produce, but it does not remove responsibility for what reaches production. These field notes focus on the work that becomes more important when implementation gets cheaper: reviewing generated changes, evaluating probabilistic behavior, measuring outcomes rather than activity, and maintaining enough system knowledge to own the result.

The recurring question is not whether engineers should use AI. It is how an organization can gain speed without moving the bottleneck—and the risk—into review, integration, or production.

AI-Assisted Engineering Field Notes#

Evals Are the New Tests

In April 2025 OpenAI shipped a model update whose offline evals and A/B tests all looked good. It was sycophantic enough to roll back within days. A practical guide to building the measurement layer that would have caught it - with a working eval spec and grading rubric.

Code Was Never the Bottleneck

Your engineers are producing more code and your delivery cadence has barely moved. The waiting did not disappear - it moved downstream to review and absorption, and that is where the constraint always was. Includes a review-capacity audit.

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