What makes a specialist AI agent truly strong
The central question is where to invest effort when building an AI agent that needs deep skill in one field. The possible answers include better prompt and , more field-specific material through , , , , ongoing training, and stronger tool connections. The practical examples are an agent that acts like an expert financial analyst or a strong legal researcher.
The issue is not just choosing a better model. It is deciding how knowledge, memory, tools, training, and the agent’s workflow should work together in a real .
Key points
- The item compares prompt design, context, , memory, , , ongoing training, and tool .
- The target use cases are high-skill agents, such as financial analysis and legal research.
- The main decision is where builders should spend effort first.
- For cost control, the important tradeoff is whether to add more context, retrieve better data, use tools, or train the model.