Skill UI

This comprehensive guide provides a blueprint for building high-converting, interactive professional portfolios. It covers everything from portfolio architecture (single-page vs. multi-page) and effective project showcase design to optimizing developer-specific content. Learn how to make your first impression count in the critical 30 seconds, transforming a simple collection of work into a powerful career narrative.

Guides developers through native iOS app creation using Swift 6, SwiftUI, UIKit, Combine, Core Data, networking, and App Store deployment best practices, ensuring architecture, performance, and security align with Apple ecosystem expectations.

Guides developers through diagnosing and fixing Juicebox API errors, covering authentication, configuration conflicts, resource lookups, and how to collect diagnostic info when integrations fail.

Guides frontend developers through keyboard navigation testing, offering best-practice advice, code snippets, and automated validation for accessibility, frameworks, and performance.

A quick reference for developers to manage common mistakes when integrating Kling AI, covering troubleshooting steps, best practices, async patterns, secure credential usage, and cost controls for more reliable implementations.

Knowledge Distillation is a crucial technique used to compress large, high-performing Language Models (Teacher) into smaller, more efficient Student models. This allows developers to deploy powerful AI capabilities (like those of GPT-4) on resource-constrained devices while significantly reducing inference costs. The method uses advanced techniques such as soft targets, temperature scaling, and Reverse KL Divergence (MiniLLM) to transfer knowledge effectively.

Guides Kotlin developers with idiomatic coroutine, Flow, Compose, Ktor, and multiplatform implementations, ensuring null safety, structured concurrency, and type-safe DSLs when building apps across Android, server, and shared modules.

Guides developers to assemble LangChain LCEL chains and prompt templates for sequential, parallel, and branching LLM workflows with type-safe parsers and reusable components.

Guides developers through identifying, diagnosing, and fixing the most frequent Langfuse SDK errors—from auth failures to missing traces—by offering command snippets, trace handling tips, and environment checks for reliable integrations.

Guides deliberate skill development during AI-assisted coding by offering optional 10–15 minute exercises after architecture work, schema changes, or “why” questions so developers stay engaged and understand decisions.

Guides developers through diagnosing Lindy AI SDK incidents, covering authentication, rate limits, agent, and tool failures, plus checklists and resources for integration troubleshooting.

Guides Lindy AI developers through API and agent action rate limit handling, covering request throttling, agent budgets, webhook controls, and error recovery to keep integrations stable.