Results for “lightning-platform”

Builds a custom LWC lookup component with typeahead search via Apex SOSL/SOQL, debounce, keyboard navigation, and pill UI for cases where standard pickers fall short.

Guides secure design and review of Lightning Web Components, covering DOM safety, Apex data exposure, and Lightning Web Security.

Enforce quality, security, and accessibility standards for Salesforce Lightning Web Components, Aura components, and Visualforce pages.

Guides Lightning Web Component developers in setting up lightning-datatable with stable row identity, typed columns, row actions, inline edit, and bounded infinite loading.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.

Optimizes Lightning Web Components for slow initial load, heavy rerenders, large-list rendering, payload reduction, and lazy instantiation choices such as lwc:if, tabs, or dynamic components.

Builds memory-safe, performant Lightning Web Components with correct lifecycle hook usage, covering build, review, and troubleshooting workflows.

Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.

Routes to 82 Lightning Web Components skill packages covering reactivity, wire adapters, component communication, accessibility, performance, security, and Jest testing. Finds and opens the exact skill package for LWC-related requests.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Creates a new Jetson target-platform profile YAML by selecting a reference devkit and optional custom carrier, then updates the active target pointer.

Switch the active Jetson target-platform pointer to an existing profile YAML. Use before customize/build/flash to change target; not for authoring profiles — use jetson-init-target instead.

Spark by Lightspark: statechain-derived L2 with FROST threshold signatures, leaf architecture, Lightning compatibility. Beta launched April 2025; managed by Spark Operators (SOs). USE WHEN: integrating with Spark, evaluating Spark vs Ark vs Lightning, designing leaf-based UTXO trees.

Render long lists (1k+ rows) efficiently in Salesforce LWC using lightning-datatable infinite loading or an IntersectionObserver sentinel, with keyset pagination and accessibility guidance.

Guides designing or reviewing Lightning Web Components for keyboard access, semantic labeling, and focus management, prioritizing base components over custom ARIA.

Build cross-platform Flutter apps with proven patterns for widgets, state management (Riverpod/Bloc), GoRouter navigation, performance optimization, and testing.

Develops and debugs Apex code, builds Lightning Web Components, optimizes SOQL queries, and manages Salesforce DX deployments with CI/CD pipelines.

Builds Lightning Web Components for record-page quick actions, covering screen actions with modals and headless actions with no UI, including lifecycle, recordId injection, and post-action UX.

Strata by Alpen Labs: ZK rollup on Bitcoin, BitVM-based bridge, EVM-compatible execution. Emerging Bitcoin L2 in 2025-2026. USE WHEN: evaluating Strata for deployment, comparing with Citrea.