Beyond Static Prompts

Design Agentic AI Workflows

Choose a pattern, configure your agent, set governance rules, estimate costs, test your workflow, and export a ready-to-use config.

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Pattern Context Agent Governance Cost Test Export

Choose a Workflow Pattern

Select an agentic architecture that fits your use case. Each pattern defines how your AI agent reasons, acts, and iterates.

Start from a Template Pre-built workflows for common use cases — Customer Support, Content Creation, Data Analysis, and more.
Neuro-Symbolic AI combines neural networks (pattern recognition) with symbolic reasoning (logic rules). Modern agentic patterns leverage this hybrid approach — the LLM "thinks" while structured tools and guardrails provide deterministic logic.

Configure Context Engineering

Define how your agent perceives and manages information. Context engineering is the foundation of reliable AI systems.

Context Engineering is the art of structuring what information an AI agent sees, when it sees it, and how it's formatted. Unlike static prompting, context engineering dynamically manages the agent's "working memory" across multiple turns and tool calls. Proper context engineering can reduce hallucinations by up to 90%.
Vector DB
Web Search
External API
Documents
SQL/NoSQL DB
Code Repository

Define Agent Role & Tools

Specify what your agent does, which tools it can access, and how it reasons through tasks.

Temporal Reasoning enables agents to understand time-dependent relationships — "what happened before", "what's happening now", and "what should happen next." This is critical for multi-step workflows where action order matters, such as data pipelines, approval chains, or iterative analysis loops.
Web Search
Code Execution
File I/O
API Call
Calculator
DB Query
Image Gen
Email

Set Governance & Guardrails

Define safety boundaries, compliance rules, and quality validation. Prompt governance is essential for production AI systems.

Prompt Governance is the organizational framework for managing, versioning, and auditing AI prompts at scale. It includes access control (who can edit prompts), version tracking (what changed and when), compliance mapping (which regulations apply), and quality gates (automated checks before deployment). Without governance, prompt drift can cause unpredictable behavior and compliance violations.
Hallucination Detection Verify claims against source data before outputting
PII Redaction Auto-detect and mask personal identifiable information
Content Safety Filter Block harmful, biased, or inappropriate outputs
Output Validation Schema Enforce structured output format with JSON Schema
GDPR
HIPAA
SOX
ISO 27001
EU AI Act
None
90% Cost Reduction Tip: Use smaller models (GPT-4o-mini, Claude Haiku) for reasoning steps and reserve powerful models (GPT-4o, Claude Opus) only for final validation. Implement caching for repeated queries and set strict token budgets per agent step. Most agentic workflows waste tokens on verbose intermediate reasoning that can be compressed.

Cost Estimator & Optimization

Estimate your workflow's real-world costs before deploying. Avoid surprise API bills.

Daily Cost
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Monthly Cost
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Yearly Cost
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potential savings below

Cost Breakdown

Test & Preview Your Workflow

Run simulated tests against your workflow configuration. Identify issues before deploying to production.

Sandbox Testing simulates your workflow execution using mock data and validates the configuration structure, guardrail compatibility, tool availability, and expected token usage. No actual API calls are made — this is a dry-run validation.

Test Queries

Simulated dry-run — no API calls made

Test Results

CMD Panel — Prompt Trickster 🧪 Mock Mode

Test your agent in mock mode. Responses are simulated — not connected to a real AI model.

Prompt Trickster — Agent Terminal
MOCK
// Prompt Trickster v1.0 — PromptHaven Agent Framework
// Type your query below or click "Run Demo" to see an example.
~\PromptTrickster> 
Python 3.8+ • Single file • Requires: pip install openai
Mock Mode Active — This terminal generates simulated responses to show how your agent would work. It is not connected to a real AI model.
To run your agent on your own machine or server, download the Prompt Trickster file below.
An API key is required for real usage (e.g. OpenAI API Key)

Your Workflow is Ready

Review the visual flow, save a version, then copy the config in your preferred format.

Version History

No saved versions yet. Click "Save Version" to create one.

Connect Your Agent

Export your agent config directly to no-code platforms. Connect to Google Sheets, Slack, email and more — no coding required.

Zapier
Connect to 6,000+ apps via webhook. Trigger actions in Google Sheets, Slack, HubSpot and more.
Export Webhook Config
Make (Integromat)
Build visual scenarios with HTTP modules. Advanced routing, filters and data mapping built-in.
Export Scenario Blueprint
n8n
Self-hosted workflow automation. Import the JSON directly into your n8n instance — ready to run.
Export Workflow JSON
Popular Connections
Google Sheets
Write data to rows
Slack
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Gmail
Send emails
Notion
Create pages
Airtable
Add records
Discord
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    API Key Required

    This site runs in Mock (simulation) mode — responses are artificially generated. To run the Prompt Trickster file on your own machine, you'll need an API key.