Friction between teams often arises from deeply misaligned values, not just personality clashes. A "move fast" team measured by DAUs will inevitably conflict with a "reliability" team measured by uptime SLAs. True alignment requires shared goals, not just shared projects.

Measuring engineering success with metrics like velocity and deployment frequency (DORA) incentivizes shipping code quickly, not creating customer value. This focus on output can actively discourage the deep product thinking required for true innovation.

AI coding tools dramatically accelerate development, but this speed amplifies technical debt creation exponentially. A small team can now generate a massive, fragile codebase with inconsistent patterns and sparse documentation, creating maintenance burdens previously seen only in large, legacy organizations.

When knowingly incurring tech debt to meet a deadline, trust between product and engineering is key. Don't just hope to fix it later; establish a formal agreement for an 'N+1 fast follow-up' release. This ensures time is explicitly scheduled to address the shortcuts taken.

Teams often focus on perfectly implementing frameworks like OKRs or Discovery, creating a false sense of achievement. This "alibi progress" prioritizes methodology correctness over creating value in a specific context, leading to lots of outputs but no outcomes.

To prevent engineers from focusing internally on technical purity (e.g., unnecessary refactoring), leaders must consistently frame all work in terms of its value to the customer. Even tech debt should be justified by its external impact, such as improving security or enabling future features.

The popular tech mantra is incomplete. Moving fast is valuable only when paired with rapid learning from what breaks. Without a structured process for analyzing failures, 'moving fast' devolves into directionless, costly activity that burns out talent and capital without making progress, like a Tasmanian devil.

To inject responsibility into a speed-obsessed culture, frame the conversation around specific risks. Create documented assumptions about what might break and, crucially, identify who bears the impact if things go wrong. This forces a deliberate consideration of consequences.

A project's success equals its technical quality multiplied by team acceptance. Technologists often fail by engineering perfect solutions that nobody buys into or owns. An 80%-correct solution fiercely defended by the team will always outperform a "perfect" one that is ignored.