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Articles on product strategy, engineering principles, and building software that lasts.
Unplanned, repetitive operational tasks, known as production toil, negatively impact engineering team retention. This happens when engineers spend disproportionate time on maintenance over new feature development. Recognizing and addressing systemic toil is critical for maintaining team morale and stability.
Integrating AI into products frequently adds complexity without clear value. This occurs when core problems are not correctly identified or when the operational burden of AI models is underestimated. Careful validation and cost analysis are crucial.
Incident response prioritizes rapid service recovery. Incident investigation focuses on understanding system failures. Both are critical but distinct phases of incident management.
Deploying machine learning models introduces complexities that are not present in traditional software. These hidden costs manifest in infrastructure, maintenance, and data management, impacting long-term operational budgets.
Knowing when to escalate a production incident is critical for efficient resolution. Escalation occurs when an engineer's investigation capabilities are exhausted, incident scope expands, or predefined time limits are reached. This process minimizes downtime and leverages broader expertise effectively.
Data inconsistencies in production environments indicate a deviation from expected data states. These issues cause incorrect application behavior and reporting. Effective investigation requires a structured approach to identify the source and scope of discrepancies.
Products frequently attempt to solve tertiary problems before validating the primary user need. This occurs due to founder bias, insufficient problem validation, and a focus on feature lists over true pain points. Prioritizing core constraints ensures product relevance and resource efficiency.
Reproducing production issues is often impossible due to unique environmental factors or data. Effective investigation relies on deep analysis of available system data. Understand the underlying causes and implement targeted monitoring.
A technical co-founder is necessary when the core product is technology-dependent and external development introduces unacceptable risks or costs. It is not necessary when the product is primarily business-model driven or existing no-code/low-code tools sufficiently meet initial development needs.
Context switching during production incident investigations directly degrades diagnostic efficiency. It fragments engineer attention, prolongs resolution times, and delays system restoration. Understanding these costs is crucial for improving incident response processes.
Expanding a Minimum Viable Product (MVP) beyond its core function significantly impacts development timelines and resource allocation. Each additional feature introduces compounding costs related to design, implementation, testing, and maintenance, undermining the MVP's foundational purpose.
Not all production issues warrant prevention engineering. Prioritize those with demonstrably high impact and recurrence. This approach maximizes return on engineering investment.
Better Software is a product engineering company, part of Better. We build software for owners and founders who already understand the problem.
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