Instruction: Create a coding assistant. Scenario 0: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 0: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 1: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 1: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 2: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 2: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 3: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 3: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 4: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 4: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 5: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 5: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 6: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 6: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 7: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 7: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 8: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 8: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 9: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 9: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 10: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 10: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 11: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 11: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 12: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 12: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 13: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 13: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 14: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 14: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 15: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 15: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 16: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 16: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 17: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 17: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 18: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 18: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 19: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 19: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 20: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 20: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 21: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 21: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 22: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 22: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 23: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 23: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 24: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 24: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 25: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 25: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 26: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 26: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 27: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 27: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 28: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 28: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 29: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 29: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 30: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 30: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 31: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 31: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 32: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 32: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 33: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 33: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 34: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 34: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 35: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 35: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 36: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 36: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 37: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 37: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 38: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 38: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 39: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 39: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 40: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 40: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 41: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 41: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 42: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 42: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 43: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 43: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 44: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 44: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 45: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 45: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 46: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 46: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 47: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 47: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 48: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 48: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 49: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 49: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 50: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 50: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 51: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 51: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 52: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 52: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 53: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 53: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 54: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 54: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 55: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 55: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 56: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 56: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 57: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 57: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 58: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 58: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 59: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 59: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 60: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 60: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 61: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 61: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 62: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 62: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 63: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 63: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 64: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 64: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 65: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 65: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 66: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 66: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 67: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 67: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 68: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 68: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 69: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 69: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 70: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 70: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 71: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 71: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 72: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 72: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 73: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 73: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 74: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 74: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 75: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 75: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 76: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 76: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 77: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 77: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 78: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 78: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 79: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 79: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 80: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 80: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 81: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 81: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 82: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 82: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 83: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 83: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 84: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 84: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 85: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 85: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 86: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 86: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 87: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 87: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 88: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 88: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 89: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 89: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 90: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 90: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 91: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 91: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 92: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 92: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 93: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 93: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 94: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 94: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 95: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 95: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 96: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 96: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 97: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 97: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 98: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 98: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 99: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 99: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 100: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 100: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 101: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 101: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 102: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 102: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 103: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 103: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 104: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 104: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 105: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 105: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 106: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 106: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 107: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 107: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 108: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 108: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 109: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 109: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 110: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 110: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 111: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 111: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 112: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 112: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 113: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 113: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 114: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 114: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 115: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 115: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 116: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 116: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 117: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 117: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 118: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 118: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 119: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 119: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 120: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 120: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 121: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 121: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 122: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 122: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 123: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 123: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 124: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 124: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 125: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 125: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 126: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 126: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 127: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 127: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 128: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 128: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 129: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 129: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 130: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 130: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 131: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 131: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 132: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 132: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 133: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 133: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 134: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 134: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 135: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 135: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 136: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 136: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 137: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 137: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 138: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 138: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 139: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 139: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 140: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 140: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 141: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 141: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 142: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 142: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 143: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 143: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 144: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 144: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a chatbot platform. Scenario 145: Provide a practical implementation plan.

Output: Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a chatbot platform. Scenario 145: Provide a practical implementation plan.

### Input:

### Response:
Use message queues, vector search, session storage, analytics, and model serving infrastructure. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 146: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 146: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 147: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 147: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 148: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 148: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 149: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 149: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 150: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 150: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Integrate local LLMs. Scenario 151: Provide a practical implementation plan.

Output: Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Integrate local LLMs. Scenario 151: Provide a practical implementation plan.

### Input:

### Response:
Use Ollama or llama.cpp, manage context windows, and optimize inference performance. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 152: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 152: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy a MERN application. Scenario 153: Provide a practical implementation plan.

Output: Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy a MERN application. Scenario 153: Provide a practical implementation plan.

### Input:

### Response:
Host frontend separately, deploy backend services, configure databases, secrets, monitoring, and backups. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 154: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 154: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 155: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 155: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: API returns 500 errors. Scenario 156: Provide a practical implementation plan.

Output: Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
API returns 500 errors. Scenario 156: Provide a practical implementation plan.

### Input:

### Response:
Check logs, validate inputs, inspect database connectivity, and improve exception handling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Build an AI project manager. Scenario 157: Provide a practical implementation plan.

Output: Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Build an AI project manager. Scenario 157: Provide a practical implementation plan.

### Input:

### Response:
Create a full-stack application with planning, task tracking, AI suggestions, analytics, and collaboration tools. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: React app re-renders infinitely. Scenario 158: Provide a practical implementation plan.

Output: Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
React app re-renders infinitely. Scenario 158: Provide a practical implementation plan.

### Input:

### Response:
Inspect state updates, useEffect dependencies, memoization, and component hierarchy. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Create a coding assistant. Scenario 159: Provide a practical implementation plan.

Output: Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Create a coding assistant. Scenario 159: Provide a practical implementation plan.

### Input:

### Response:
Use Electron, Monaco Editor, local LLM integration, chat memory, and project indexing. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Design a scalable SaaS. Scenario 160: Provide a practical implementation plan.

Output: Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Design a scalable SaaS. Scenario 160: Provide a practical implementation plan.

### Input:

### Response:
Use microservices, API gateway, PostgreSQL, Redis, monitoring, CI/CD, and container orchestration. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Deploy an AI application. Scenario 161: Provide a practical implementation plan.

Output: Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Deploy an AI application. Scenario 161: Provide a practical implementation plan.

### Input:

### Response:
Containerize services, configure GPUs if needed, add logging, metrics, and autoscaling. Include milestones, technology choices, risks, testing strategy, and scaling considerations.


Instruction: Add AI chat to an app. Scenario 162: Provide a practical implementation plan.

Output: Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.

Prompt:
### Instruction:
Add AI chat to an app. Scenario 162: Provide a practical implementation plan.

### Input:

### Response:
Implement conversation memory, prompt templates, model routing, and streaming responses. Include milestones, technology choices, risks, testing strategy, and scaling considerations.