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human: How do I build a multi-agent system where different specialized agents collaborate to complete complex tasks? Show an orchestrator-worker pattern.
gpt: ## Multi-Agent Orchestrator-Worker Pattern
### Architecture Overview
```
User Request
β
Orchestrator Agent
βββ Decomposes task into subtasks
βββ Ro... | Plans11/agentic-workflows-sft-100k | 1,823 |
human: My AI agent is doing unexpected things in production. How do I add observability to understand exactly what it's thinking and doing?
gpt: ## Agent Observability: Understanding What's Happening
### The Core Observability Stack
```
Agent Execution
β
Span/Trace Layer (track every step)
β
Structured Logs (... | Plans11/agentic-workflows-sft-100k | 1,994 |
human: How should an AI agent handle complex multi-step tasks that require planning ahead? Show me planning patterns beyond simple ReAct.
gpt: ## Advanced Agent Planning Patterns
### Why Simple ReAct Falls Short
ReAct works step-by-step without looking ahead. For complex tasks (writing a research report, building a s... | Plans11/agentic-workflows-sft-100k | 1,810 |
human: How do I protect my AI agent from prompt injection attacks where malicious content in the environment tries to hijack the agent?
gpt: ## Agent Security: Defending Against Prompt Injection
### The Threat Model
Prompt injection is unique to agents because agents process untrusted content (web pages, emails, file... | Plans11/agentic-workflows-sft-100k | 1,599 |
human: My agent is slow because it calls tools one at a time. How do I run multiple tool calls in parallel?
gpt: ## Parallel Tool Execution in Agents
Claude natively supports parallel tool calls in a single response β when it identifies multiple independent tools to call, it returns them all at once. You just need to ... | Plans11/agentic-workflows-sft-100k | 833 |
human: How do I implement memory for an AI agent that needs to remember context across multiple conversations and sessions?
gpt: ## Agent Memory Systems: From Simple to Production
### Memory Type Taxonomy
| Type | Duration | Use Case |
|---|---|---|
| **Working memory** | Single turn | Current conversation context |
... | Plans11/agentic-workflows-sft-100k | 1,842 |
human: How do I build an agent that can handle long-running tasks that might take hours, survive interruptions, and resume from where it stopped?
gpt: ## Resumable Long-Running Agent Tasks
### The Problem with In-Memory State
For tasks that take hours:
- Process restarts lose all progress
- Context windows fill up wi... | Plans11/agentic-workflows-sft-100k | 1,845 |
human: What are the standard benchmarks for AI agent performance and how do I create my own domain-specific benchmark?
gpt: ## AI Agent Benchmarks: Standard and Custom
### Standard Agent Benchmarks
| Benchmark | What It Tests | Key Tasks |
|---|---|---|
| **SWE-bench** | Software engineering agent | Fix real GitHub i... | Plans11/agentic-workflows-sft-100k | 1,225 |
human: Explain the ReAct (Reasoning + Acting) pattern for LLM agents and show me how to implement it from scratch in Python.
gpt: ## ReAct Pattern: Reasoning + Acting for LLM Agents
ReAct interleaves **thought** (reasoning about what to do next) with **action** (using a tool) and **observation** (processing the tool r... | Plans11/agentic-workflows-sft-100k | 1,470 |
human: How do I build a production-grade AI coding assistant that can read, understand, and modify codebases? Not just autocomplete β actual project-level reasoning.
gpt: ## Production AI Coding Assistant: Project-Level Reasoning
### Architecture for Codebase-Aware AI
A coding assistant that reasons at the project le... | Plans11/agentic-workflows-sft-100k | 1,957 |
human: How do I evaluate and test an AI agent system in production? What metrics matter and how do I catch regressions?
gpt: ## Evaluating AI Agents in Production
### The Challenge
Agents are harder to evaluate than single-turn LLMs because:
- Success depends on a multi-step trajectory, not a single output
- Tool cal... | Plans11/agentic-workflows-sft-100k | 1,959 |
human: What are the best patterns for designing LLM tools/functions? I want to avoid common mistakes that make agents fail.
gpt: ## LLM Tool Design: Patterns and Anti-Patterns
### Core Principle: Tools Should Be Idempotent and Atomic
A well-designed tool is:
- **Atomic**: does one thing well
- **Idempotent**: safe to... | Plans11/agentic-workflows-sft-100k | 1,605 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,750 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,399 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,453 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 4,036 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,897 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,611 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 3,823 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 2,617 |
user: You are an AI assistant tasked with solving command-line tasks in a Linux environment. You will be given a task description and the output from previously executed commands. Your goal is to solve the task by providing batches of shell commands.
Format your response as JSON with the following structure:
{
"ana... | Plans11/AgentTrove | 3,128 |
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