Nick

Develop Angular v20+ applications using Signals for reactive state and Standalone Components. Supports gradual migration from NgModules, Zoneless configuration, server-side rendering, hydration, and performance optimization with development testing before production use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a new Angular v20+ application
• Implement reactive state with Signals
• Gradually migrate NgModules to Standalone Components

Design REST or GraphQL APIs by defining who will use them, what data they expose, and how requests behave. Establish error formats, versioning, pagination, and authentication, then review examples for consistency before implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new REST or GraphQL API
• Reviewing API specifications before implementation
• Establishing shared API design standards

Guide Angular development, code review, and refactoring with prioritized performance rules. Review rendering efficiency, loading time, and bundle size—the amount of code delivered to browsers—alongside data fetching and server-rendered page setup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Writing Angular components with performance in mind
• Reviewing code for performance bottlenecks
• Reducing bundle size and loading time

Design scheduled AI workflows for document ingestion, batch processing, and model training using Prefect, Airflow, or Dagster. Compare orchestration tools and plan task dependencies, retries, caching, and monitoring through implementation fragments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Schedule document ingestion and RAG index refreshes
• Design batch workflows for LLM requests
• Connect model training with quality evaluation

Generate realistic photo-style images with Google AI Studio for social posts and educational materials. Adjust aspect ratios, lighting, settings, and subtle imperfections to create a natural smartphone-photo look suited to each use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Natural lifestyle images for social posts
• Photo-style illustrations for courses and tutorials
• Portrait or landscape images for different platforms

Design AI agents that use tools, plan tasks, retain relevant context, and recover from failures. Choose execution patterns, permission boundaries, memory handling, and runtime limits, and assess whether coordinating multiple agents is justified for the task.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing an execution loop for a tool-using agent
• Designing memory and recovery for long-running tasks
• Setting tool permissions, runtime limits, and cost caps

Find autonomous AI agents, frameworks, and tools through AgentFolio. Compare their capabilities, intended users, integrations, and deployment options to shortlist existing products or gather examples and ideas before designing an agent of your own.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding existing agents before building your own
• Shortlisting agent vendors for evaluation
• Researching competitors and market gaps

Review GitHub Actions workflows that run AI agents, tracing how external input reaches prompts and tools. Produce findings with evidence, severity, impact, and remediation guidance through static analysis, which examines configuration without running attacks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing AI agent integrations in GitHub Actions
• Tracing issue and PR text into agent prompts
• Reviewing sandbox settings and tool permissions

Compare prompt revisions on a fixed set of test cases to identify regressions, meaning behavior that gets worse after a change. Record model settings, case-level evidence, missing results, costs, and evaluation limits for a reviewable decision.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing original and revised prompts
• Checking required JSON fields after prompt changes
• Reviewing tool selection and task completion

Plan AI application development by selecting relevant phases and companion skills. The workflow covers language model integration, retrieval from documents, agents, machine learning pipelines, monitoring, and security, with prompts and quality checklists.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan AI features and language model integration
• Organize RAG retrieval design and implementation
• Map agent roles, tools, and memory

Review articles and product pages to help AI search systems find and cite their content. Assess competitor citations, improve standalone answers and source attribution, and plan ongoing checks of brand mentions and cited pages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Audit brand and competitor citations in AI answers
• Revise articles and product pages for clearer answers
• Review sources, author details, and update dates

Plan AI features for products, covering language model integration, RAG architecture that retrieves information for answers, prompt design, user experiences people can trust, and cost optimization. Use it to guide development decisions for production use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan language model integration in a product
• Consider RAG architecture for reference-based answers
• Review prompt design and AI user experience

Design layered protections for AI agents against malicious instructions, tool misuse, and data leakage. Provides guidance and code examples for input checks, isolated tool execution, permission limits, and audit logging to help review and strengthen agent security.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review defenses against malicious instructions
• Isolate tool execution and restrict permissions
• Assess data leakage risks between tenants

Plan and build AI agents through selected stages of design, implementation, tool integration, memory, and evaluation. The workflow points to specialized skills for single agents, coordinated agent teams, and stateful workflows using CrewAI or LangGraph.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing an autonomous AI agent
• Building a team of agents with distinct roles
• Creating stateful workflows with LangGraph

Turn articles, notes, or scripts into solo podcast MP3s using the paid Beatra service. The referenced package supports a consistent host voice, natural pacing, and pronunciation control, with cost approval and audio review steps.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning an article into a solo podcast
• Creating a narrated episode from notes
• Producing an MP3 from a finished script

Improve workflows involving multiple AI agents by measuring bottlenecks, adjusting workload distribution, and managing model costs. This design guide helps compare changes against a measured baseline while checking quality, latency, and resource use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding bottlenecks in workflows involving multiple agents
• Reviewing task distribution and parallel execution
• Reducing model costs within quality thresholds

Generate, compose, and edit product images, posters, illustrations, and social graphics through the paid Beatra service. The workflow covers reviewing upload files and estimated costs before each paid call, then checking results and actual charges.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating product images
• Designing posters and social graphics
• Editing reference images and making photo variations

Search AI and machine learning jobs through AI Dev Jobs MCP, a connection agents use to access job data. Inspect employers and requirements, match roles to skills and preferences, and review available salary and market statistics.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding remote machine learning jobs
• Discovering companies hiring for AI roles
• Matching jobs to skills and work preferences

Design and implement LLM applications, AI agents, and RAG systems that retrieve documents to support answers. Cover model selection, search quality, testing, monitoring, safety measures, and cost controls for applications intended for production use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building an AI assistant that answers from company documents
• Improving search with keyword and vector retrieval
• Designing AI agents with multiple specialized roles

Inventory local skills within a requested scope, rank candidates against a task, and prepare a coordination plan showing their order and data flow. Project assignments help prioritize relevant skills without automatically launching agents or executing skills.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inventory locally installed skills
• Compare skills suited to a task
• Plan a workflow using several skills

Create consistent records for evaluating AI agents, including task success, invalid tool calls, token use, and actual costs. Produce CSV tables, database definitions, and JSON validation schemas to support reproducible comparisons and checks for performance declines.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recording agent evaluation results in a shared format
• Comparing a candidate agent with a baseline
• Tracking actual cost per solved task

Hand a scoped coding task to Aider while the coordinating agent reviews changes, runs project checks, and commits the result. Covers task briefs, execution tracking, and follow-up edits, but the executable helper is not bundled.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Delegating a scoped code change to Aider
• Reviewing changes and tests before committing
• Requesting follow-up edits after a review

Create and edit Agent QA tests, test suites, and hooks, then validate their structure and tool-generated IDs before running them. Use MCP, an agent tool connection, or the CLI within a configured workspace.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create and validate a checkout test for staging
• Update an existing test suite
• Check YAML definitions and IDs

Build AI agents that make phone calls and send or receive SMS through the AgentPhone API. Manage phone numbers, configure voice agents and event notifications, and inspect call transcripts and account usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create an AI voice agent with a phone number
• Send and receive SMS through AgentPhone
• Review call transcripts and account usage