
Measuring Time Lost to Investigations
Measure engineering time lost to production investigations by defining scope, logging start and end times, categorizing effort and tying hours to incidents.
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Articles on product strategy, engineering principles, and building software that lasts.

Measure engineering time lost to production investigations by defining scope, logging start and end times, categorizing effort and tying hours to incidents.

MVPs collect unused features through confirmation bias, stakeholder pressure and a loose definition of minimum. Define one core problem to keep scope small.

Cut the incidents that need a human by finding recurring patterns, documenting root causes, and automating diagnosis and remediation for predictable failures.

How to estimate engineering timelines honestly with ranges, spikes and scope cuts, why early estimates miss by 4x, a worked example, and the mistakes to avoid.

Engineering teams that inherit support work need a fixed triage sequence. Verify the data, reproduce, rate impact, assign an owner and escalate with next steps.

Why code review carries more weight in a small team, seven ways to run it without slowing delivery, what to check first, and when a lighter process works.

Rank concurrent production incidents by user impact and data loss risk, find shared dependencies, name an incident commander, and mitigate before diagnosing.

Early products should favor development speed. Five triggers that justify performance optimization, and how to do it without stalling feature delivery.

Diagnose production incidents faster with a fixed sequence. Verify scope, check recent changes, read the golden signals, test one hypothesis, then escalate.

Founders should start marketing once the core workflow solves one problem for one buyer. Six signals it is time, and how to split build and marketing time.

When product simplicity becomes a competitive advantage, how to build it step by step, how simple and feature-rich products compare, and when it stops working.

Which database schema design decisions to get right in week one, what can safely wait, the mistakes that surface in year two, and how to change a live schema.

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