Source
https://www.aihero.dev/cohorts/build-deepsearch-in-typescript
Category
File Size
3.4 GB
Publisher
aihero
Updated
August 20, 2025
Description
Generic chat responses might work for demos, but professional applications need appropriate outputs that align with specific requirements. In a professional environment code is (ideally) tested, metrics are collected, analytics are displayed somewhere. AI development can follow these established patterns.
You will hit roadblocks when trying to:
- Implement essential backend infrastructure (databases, caching, auth) specifically for AI-driven applications.
- Debug and understand the “black box” of AI agent decisions, especially when multiple tools are involved.
- Ensure chat persistence, reliable routing, and real-time UI updates for a seamless user experience.
- Objectively measure AI performance moving beyond subjective “vibe checks” for improvements.
- Manage complex agent logic without creating brittle, monolithic prompts that are hard to maintain and optimize.
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