Calculated experimentation beats certainty-first planning. Build a culture of experimentation that treats failure as data, adds one bounded experiment per sprint, and accelerates real innovation.
Set a simple tracking threshold and monthly snapshots to make engineering work visible—so decisions improve while your team stays agile and focused.
Using the software engineering hierarchy of needs, you’ll identify the lowest weak layer and fortify it to reduce chaos and make innovation stick.
When guardrails disrupt your flow, pausing to ask why—security, fraud, ops, economics, privacy—turns frustration into context. Learn how to analyze product tradeoffs with five practical steps that improve engineering decisions and collaboration.
Ship a minimal version early to surface real platform and user constraints. Stop waiting to launch—use fast feedback to focus polish and automation where it matters.
A practical leverage test to spot when preparation becomes procrastination. Sharpen only when it speeds the next cycle; otherwise, ship now and iterate.
This piece explores overcoming 80/20 bias in engineering by aligning effort to the right phase: learn hands-on early, scale with insight, and polish to ship for trust and durable speed.
Speed alone isn’t engineering. This piece shows how to improve engineering reasoning skills with a lightweight framework for real requirements, edge cases, and defensible trade-offs.
Operate at higher abstraction layers to multiply capability, speed, and reach. This piece shows how to scale developer impact with AI through a focused week plan and practical guardrails.
A flexible toolkit of mental models for problem solving helps engineers and AI teams cut complexity, spot fundamentals, and make faster, more reliable decisions.
