"Technical credibility is the foundation of everything else. A Tech Lead who loses technical depth loses the ability to influence, make good decisions, and mentor others."
Making architectural decisions that balance current needs with future flexibility, considering product context. The effective Tech Lead designs architecture that supports the next 2-3 product horizons without over-engineering for horizon 5. Presents architectural decisions as options with explicit trade-offs (cost, time, flexibility, risk) rather than a single option as 'the correct one'. Documents important architectural decisions (ADRs) with context, considered options, and rationale, avoiding creating tribal knowledge. Distinguishes between essential complexity (inherent to the problem) and accidental (self-inflicted by previous decisions), helping the team focus on what really matters.
System architecture evolves with the product without frequent massive rewrites. Other engineers can understand and extend the architecture without depending on the Tech Lead. Architectural decisions are evaluated retrospectively and learned from.
Maintaining system technical health long-term, managing technical debt strategically. This goes beyond simply 'doing refactoring' and includes maintaining a visible inventory of technical debt with estimated impact on velocity, risk, and cost. The effective Tech Lead negotiates time to reduce technical debt by linking it to concrete business objectives (delivery velocity, reliability, operational costs), rather than asking for generic time for 'technical improvements'. Takes technical debt consciously when it accelerates learning or delivery, documenting it and planning its payment, but avoids accumulating debt without tracking it. Technical sustainability requires balancing between delivery velocity and long-term health, making conscious decisions about when to take debt and when to pay it.
Ensuring the system works correctly, is observable, and problems are detected and resolved quickly. The effective Tech Lead implements observability (logs, metrics, traces) that allows understanding system behavior in production, not just detecting when something fails. Defines and monitors SLOs (Service Level Objectives) aligned with user and business expectations, rather than technical metrics that no one looks at. Performs blameless post-mortems after incidents, focusing on systemic improvements rather than finding culprits. Instruments features to measure adoption and behavior before considering work 'finished', and analyzes support data, error logs, and usage patterns to proactively identify unreported problems.
Developing
Behaviors not present or inconsistent; requires significant guidance
Practicing
Behaviors present but with significant gaps; requires regular coaching
Competent
Consistent behaviors in normal situations; occasionally needs support
Proficient
Consistent behaviors even in complex situations; can guide others
Expert
Reference for others; adapts approach to new contexts; improves team practices