Purpose-Built Enterprise AI Agents: What Actually Works

Why wasn't 2025 the year of the agents? 🙅

Cuz enterprise companies were trying to copy-and-paste human roles with general purpose agents that weren't ready. 

But you know what won the agentic race? 

Narrow, purpose-built agents. You know.... those built off large swaths of data to do one very specific thing well. 

As a VP of Engineering at LinkedIn, Prashanthi Padmanabhan knows a thing or three about building agents with purpose. 

And she joins Everyday AI to spill the enterprise AI agent secrets. 

Purpose-Built Enterprise AI Agents: What Actually Works -- An Everyday AI Chat with Jordan Wilson and Prashanthi Padmanabhan

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Topics Covered in This Episode:

1. Purpose-Built Enterprise AI Agents Overview
2. General vs. Narrow AI Agent Use Cases
3. AI Agent Integration in LinkedIn Recruiter
4. Collaborative Human-in-the-Loop Agent Design
5. AI Agent Workflow Reverse Engineering
6. Building Trust in Agentic AI Implementation
7. Iterative Development with Customer Feedback
8. Measuring AI Agent Impact and Efficiency
9. Domain-Specific, Context-Driven AI Agents
10. Scalability Challenges for Enterprise AI Agents

Timestamps:

00:00 "AI Agents: Hype Vs. Reality"

05:21 "Optimizing Recruitment with AI Agents"

09:20 "Building Effective Recruiting Tools"

13:00 "Scoping Purposeful AI Solutions"

14:46 "Unlocking Talent with AI"

18:38 "Boost Business with AI Expertise"

20:27 "Purpose-Built Recruitment Intelligence"

25:56 "Boosting InMail Acceptance Efficiency"

28:52 "Building Effective Enterprise Agents"

29:51 "Building Trust Through User Experience"

Keywords:

AI agents, enterprise AI agents, purpose-built agents, narrow AI agents, general AI agents, AI assistant, recruiting AI agent, LinkedIn hiring assistant, LLMs, agentic technology, human-in-the-loop, recruiter automation, workflow automation, enterprise workflows, candidate sourcing, resume parsing, talent matching, AI-powered recruiting, hiring manager, conversa

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Start Here ▶️

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