Long-form essays from the engineers shipping AI inside payers, hospitals, energy operators and proptech platforms. Written for technology leaders who care more about what runs in production than what trended last week.
When team scale justifies the complexity tax of micro-frontends, and when it does not. An honest look at what you gain, what you pay, and how to decide.
Scaling a SaaS product past its first architecture, in the order that actually works. What breaks first, why the database usually goes before the app, and how to fix it in sequence.
Shipping AI features changes how PMs and engineers work: feasibility that is probabilistic, evaluation instead of pass or fail, and iteration on behavior. The process changes that stick.
How to implement product analytics your team actually trusts: a tracking plan, clean event data, and the governance that turns events into decisions instead of dashboards nobody believes.
Accessibility as an engineering discipline: how to meet WCAG by building it in from the start instead of a costly retrofit, with testing and culture that keep it.
Frontend performance is a revenue lever, not a nicety. How to set performance budgets, monitor real users, and build a culture that keeps the frontend fast.
How to run a design system as product infrastructure across brands and teams, with governance that keeps consistency without becoming a bottleneck that slows every team.
Product discovery for technical products means gathering evidence before the roadmap and killing bad ideas cheaply, so engineering builds what is validated, not what is assumed.
What a serious architecture review covers before you scale: scope, scalability, failure modes, security, and decisions recorded, so problems surface on paper not in production.
AI-generated code fails differently than human code. The defect patterns to watch, the review heuristics that catch them, and how to audit AI output at scale.
When AI writes much of the code, output stops signaling productivity. How to measure developer productivity by outcomes, flow, quality, and experience instead.
What DORA metrics actually predict and what they miss, and how to use deployment frequency, lead time, change failure rate, and recovery time without gaming them.
Why long-lived branches kill velocity and how trunk-based development keeps teams integrating continuously, with feature flags, fast review, and strong tests.
Why feature flags are release infrastructure, not if-statements: decoupling deploy from release, controlled rollout, and the discipline that keeps flags from becoming debt.
How to choose between monorepo and polyrepo at scale, weighing build times, ownership, and the AI-tool context that now depends on how your code is organized.
How to engineer real-time product features that scale, from polling to streams: transport choices, fan-out, consistency, and graceful fallback under load.
GraphQL vs REST vs RPC for product APIs, chosen by who consumes your API rather than by fashion. A practical decision framework by consumer type.
How to version APIs without breaking customers or your own agents: compatibility rules, deprecation with notice, and a strategy that ages well as consumers multiply.
A practical comparison of multi-tenant isolation models: shared, siloed, and hybrid, plus noisy neighbors, per-tenant cost, and choosing by real requirements.
Why the modular monolith is the right architecture for most scale-ups: clear module boundaries and one deployable, without the operational tax of microservices.
How domain-driven design and bounded contexts create software boundaries that survive org changes, so scaling teams stop fighting a tangled shared model.
When event-driven architecture beats request-response APIs, explained through real operational workloads: decoupling, delivery guarantees, and where it does not fit.
Why API-first design is now a precondition for AI agents consuming your product, and how to build contract-first APIs that both humans and machines can use.
How to modernize an aging mobile app without breaking the experience: assess honestly, migrate incrementally, roll out gradually, and keep users through the change.
One long-form essay every other Wednesday. Written by the engineers shipping production AI for our clients, not by a content team. No promotional emails. Unsubscribe in one click.
