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Practical guides to AI-driven development, full-stack architecture, and solving production problems.
Showing 73–84 of 100 articles
Diagnose mobile horizontal scrolling without hiding the overflow
Find the element causing mobile horizontal scrolling by measuring bounds and intrinsic sizing, then fix width, wrapping, or containment at the responsible layout boundary.
Keep a modal accessible when content loads asynchronously
Keep async modals usable by preserving focus, dialog naming, keyboard access, and meaningful announcements as loading content becomes success or failure.
Design loading and error states for a page with several API calls
Design multi-request pages around independent resource states and explicit dependencies so partial failures, empty data, retries, and stale responses remain understandable.
Fix a form that submits when a toolbar button is clicked
Fix accidental form submissions by inspecting native button types, form ownership, and keyboard behavior before rewriting React handlers or validation state.
Diagnose an effect that loops only after a seemingly harmless edit
Diagnose React effect loops by tracing state writes and dependency identities, then separate event work, derived values, and external synchronization.
Prevent an older API response from overwriting a newer search result
Prevent stale search results by making only the current request eligible to update data, errors, and loading state, while cancelling obsolete work where supported.
Fix stale state in asynchronous React handlers
Fix stale React state in delayed handlers by distinguishing captured snapshots, queued updates, request inputs, and the latest values needed for asynchronous completion.
Find the reason a React component keeps rerendering
Trace React renders to state, props, context, and parent updates, then profile their actual cost before choosing state placement or memoization as a fix.
Debug an AI feature that works locally but fails in production
Debug production-only AI failures by separating application, runtime, network, provider, and configuration boundaries with a safe request-level evidence bundle.
Decide when your AI feature needs human approval
Place human approval before consequential AI actions and bind it to an exact reviewable proposal, with permission checks, expiration, and safe handling of changed state.
Design agent tools with narrow permissions and clear contracts
Design agent tools as narrow server-enforced capabilities with validated arguments, explicit ownership, bounded results, and reviewable action contracts.
Reduce AI feature costs before adding another cache
Reduce AI feature spending by measuring request volume, context size, retries, and quality before choosing prompt changes, model routing, or a carefully scoped cache.
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