From General AI to Task-Based AI Agents: How to Build One and Unlock Results

1. Introduction

General-purpose AI tools like ChatGPT, Gemini, and Claude have become popular for their versatility, but their effectiveness in specific, structured tasks in advertising strategy is limited. These tools operate without pre-established expertise or guidance, leading to inefficiencies and inconsistent results.

This paper explores the advantages of using task-based AI agents tailored to specific advertising strategy needs. Unlike general AI, task-based AI agents combine structured domain knowledge and task-specific interaction frameworks to deliver consistent, high-quality results for tasks such as insights generation, persona building, and brand platform creation.

2. Shortcomings of General AI for Advertising Strategy

General AI tools, while versatile, are not specifically designed to handle the nuanced and structured tasks and needs of advertising strategy. Their generic capabilities often lead to inefficiencies, misaligned outputs, and inconsistent results. Here are the main shortcomings of relying on general AI for advertising tasks:

?? Lack of Context Retention

General AI requires users to repeatedly reintroduce task definitions and goals for every interaction. For example, when generating insights, users must explain foundational concepts like what an insight is and its relevance each time. This repetition slows down workflows and increases the risk of outputs that miss the mark.

?? Absence of Role Specialization

Operating with a broad knowledge base, general AI tools lack the depth of expertise required for advertising strategy. Without predefined frameworks or specialized instructions, these tools often produce generic outputs that fail to address specific needs or align with industry best practices.

?? Inconsistent Results

The performance of general AI is heavily reliant on the user’s ability to provide precise and comprehensive prompts. As a result, outputs can vary greatly in quality, leading to unreliable results that undermine strategic advertising efforts.

3. Task-Based AI Agents as a Solution

A task-based AI agent is designed for a specific role or function. It is pre-loaded with domain-specific knowledge and programmed to follow structured interaction guidelines. In the context of advertising strategy, these agents act as expert tools, providing consistent and effective outputs tailored to the user’s needs. Key benefits include:

? Efficiency

Task-based AI agents eliminate the need for repeated task explanations, saving time and effort. Once trained, they retain essential knowledge and interaction protocols, streamlining processes.

?? Consistency

By using pre-defined frameworks and examples, task-based AI agents produce outputs that align with industry best practices, ensuring reliable and high-quality results.

?? Guided Interactions

Task-based AI agents are programmed to guide users through structured workflows. For example, when generating insights, the agent may prompt the user to provide critical details such as the brand, target audience, and campaign objectives.

4. Applications of Task-Based AI Agents in Advertising Strategy

4.1 Insights Generation

Description

A task-based AI agent for insights generation helps identify actionable insights tailored to the brand’s goals and audience. It categorizes insights for clarity and strategic application.

Pre-loaded Knowledge

The agent is trained with:

• ?? Definitions of advertising insights and their components.
• ?? Examples of best and worst practices.
• ?? Categories of insights (e.g., tension-based, cultural, functional).

Outputs

The agent delivers categorized insights aligned with the provided brand, objective, and audience, written following best practices in terms of wording.

4.2 Persona Building

Description

A task-based AI agent for persona building assists in creating detailed and actionable personas while enabling interactive conversations to deepen audience understanding.

Pre-loaded Knowledge

The agent is trained with:

• ?? Persona profiles for structured audience understanding.
• ?? Empathy mapping to identify emotional and behavioral drivers.
• ?? Customer journey mapping to track interactions and touchpoints.

Outputs

The agent provides detailed persona profiles based on structured inputs and interactive workflows that explore audience lifestyle and product interactions.

4.3 Brand Platform Creation

Description

A task-based AI agent for brand platform creation structures the brand’s vision, mission, values, and positioning into a cohesive strategy that aligns with target audience expectations.

Pre-loaded Knowledge

The agent is trained with:

• ?? Definitions and templates for brand vision, values, and positioning.
• ?? Examples of successful and ineffective brand platforms.
• ?? Common mistakes to avoid in brand strategy.

Outputs

The agent delivers a cohesive brand platform that reflects strategic goals and audience needs and organizes outputs with clear differentiation and consistent messaging.

5. How to Build a Task-Based AI Agent for Advertising Strategy

5.1 Define the Purpose

The first step is to clearly define the purpose of the task-based AI agent. Determine the specific advertising strategy task it will address, such as generating insights, building personas, or developing brand platforms. This clarity is essential for structuring its knowledge base and interaction design.

5.2 Collect and Organize Knowledge

Gather all relevant domain-specific knowledge the agent will need to perform its task effectively.

For example, for insights generation, collect examples of insights from successful campaigns, categorizing them by type (e.g., tension-based, cultural). Organize these examples in a structured format, such as an Excel sheet with fields for brand name, campaign goal, and insight description.

5.3 Define the Interaction Process

Design the agent’s interaction process to align with the specific task. This involves identifying the required inputs and structuring the sequence of interactions. For example:

• ? Inputs: Define the minimum information the agent needs to generate meaningful outputs. For insights, this could be the brand, goal, and target audience.
• ? Process: Establish the sequence of steps the agent should follow. For example, it should first ask for the brand and target audience, then prompt for the campaign goal, and finally generate insights based on predefined rules and best practices.
• ?? Outputs: You can instruct the agent to organize outputs in a specific way. Moreover, by providing relevant examples in the knowledge base, the agent can tailor its outputs to be super specific and well-written.

5.4 Write Instructions for the Agent

You can use tools like ChatGPT to assist in writing these instructions. Explain to ChatGPT what you aim to achieve with your task-based AI agent and the role it needs to play. ChatGPT can then help you structure these instructions, define interaction flows, and refine the overall approach.

I use a framework for developing clear instructions for the agent, which includes:

• ?? Role Definition: Specify the agent’s role, such as “Act as an advertising strategy expert specializing in insights generation.”
• ?? Rules: Outline the sequence of interactions and guidelines for generating outputs.
• ?? Do’s and Don’ts: Include specific actions to perform or avoid, such as ensuring insights are actionable and avoiding overly generic statements.

5.5 Set Up the Agent

Use a platform like OpenAI’s GPT to create the task-based AI agent. Follow these steps to set up your agent:

1. ?? Configure the Agent: Go directly to the configuration section in the platform. Copy and paste your instructions from ChatGPT and attach structured knowledge base material, ensuring you use simple and accessible formats like .txt.
2. ?? Create a Name and Profile Picture: Choose a name that reflects the agent’s purpose and assign a profile picture for easy identification.
3. ?? Set Up a Starter Conversation: Define a starting message or interaction flow to introduce the agent’s purpose and guide users on how to interact with it.
4. ?? Initial Testing: Conduct basic tests to ensure the configuration and attachments function correctly.

5.6 Refine and Test the Agent

Testing and refinement are critical to ensure your task-based AI agent performs effectively:

1. ? Test the Agent Yourself: Begin by using the agent in various scenarios. Identify any issues, such as unclear outputs, misaligned interactions, or gaps in knowledge.
2. ?? Refine Instructions and Retest: Adjust the instructions or examples immediately to address identified issues. Retest after every change to confirm improvements.
3. ?? Iterate Until It Works: Continue testing and refining until the agent consistently delivers high-quality results.
4. ?? Share After Internal Validation: Once the agent meets your expectations and works seamlessly for your use, start sharing it with others for broader testing and feedback.

6. Best Practices for Creating a Task-Based AI Agent

Before using a platform to program your task-based AI agent, it’s essential to design and prepare thoroughly. These best practices will help ensure success:

?? Design the Workflow and Examples

Clearly map the interaction flow, define how inputs lead to outputs, and prepare structured, high-quality examples as references to align with the agent's purpose.

?? Use ChatGPT to Assist in Instruction Creation

Leverage ChatGPT to brainstorm, refine, and iteratively improve instructions, ensuring they are conversational and aligned with best practices.

?? Test Extensively

Simulate various scenarios, identify gaps, and continuously refine the agent until it consistently delivers high-quality, actionable outputs.

7. Conclusion

Switching from general AI to task-based AI agents for advertising strategy is nothing short of a revolution.

It’s like moving from using a generic toolbox to having a customized set of precision instruments crafted specifically for your trade. Just as specialized tools enable professionals to achieve more with less effort, task-based AI agents unlock levels of efficiency and precision that general AI simply cannot match.

For those who have already found value in using general AI, this leap to task-based AI agents can be transformative. You’ll be amazed by how much more tailored, efficient, and impactful your work can become when guided by an agent designed explicitly for your needs.

For those who are interested, here you can find my specialized GPT for generating advertising insights.