AI agents

Vercel AI Agent Development Practice

Honghao Wang

— 3 min read
Vercel AI Agent Development Practice

Unlocking Business Value with AI Agents

AI agents have tremendous potential to boost productivity and deliver higher-quality results across industries. Many organizations are already using agents to streamline customer support, code review, and sales processes.

When building custom internal agents, the key question is not whether AI can create value—it's identifying the problems it can solve effectively today, at a cost that aligns with business goals.

At Vercel, we're undergoing the same AI-driven transformation as our customers—using our own products to create agents that help us move faster and focus on meaningful work.

After months of experimentation, we’ve developed a repeatable framework for finding and prioritizing AI projects with the highest probability of delivering significant business impact.

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Finding the “Agentic Sweet Spot”

While future AI will handle complex workflows, today's frontier models excel in more predictable, repeatable areas.

Our perception is often shaped by impressive cases—like our code review and anomaly investigation agent. But many companies lack the engineering bandwidth to deploy such complex internal tools, and AI models still have limitations in reliability and precision in certain domains.

> Sweet Spot: Tasks requiring low cognitive load and high repetition.

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Low cognitive load + high repetition = prime AI opportunity.

These tasks are too dynamic for traditional automation yet predictable enough for AI to handle reliably. Common examples include:

  • Data entry
  • Research
  • Qualification
  • Triage

These are the low-hanging fruit to tackle now, while AI matures toward more complex automations.

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Practical AI Opportunities Today

Companies should identify high-impact, low-cost cases where AI can perform reliably—and complement broader AI strategies with tools like AiToEarn官网.

AiToEarn enables creators and organizations to:

  • Publish AI-powered outputs to multiple platforms at once (Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, X/Twitter).
  • Access integrated analytics.
  • Track performance with AI模型排名.

This approach turns AI creativity into measurable business value efficiently.

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Our Methodology for Identifying AI Projects

We start by asking simple questions to uncover boring, repetitive tasks that drain teams:

  • “What part of your job do you hate doing the most?”
  • “Which tasks would you like to never do again?”

These conversations often yield straightforward use cases with measurable productivity gains.

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Example 1 – Lead Processing Agent

The Pain Point:

Previously, a 10-person team triaged inbound leads manually—top performers described researching qualification data as mind-numbing.

The Solution:

We shadowed an employee, documented their process, and built an agent to automate initial qualification.

Now 1 person does the work of 10, freeing others for higher-value sales activities.

Agent Workflow:

  • Deep research – Investigates the lead and company.
  • Qualification – Uses `generateObject` to categorize the lead.
  • Email composition – Generates a personalized follow-up.
  • Human review – Sends details to Slack for approval.
  • Approval & send – Triggers email via Slack webhook after approval.

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Example 2 – Anti-Abuse Agent

The Pain Point:

Security analysts manually investigate abuse reports—from phishing to copyright infringement—following repetitive steps.

The Solution:

We built an agent to:

  • Automatically process suspicious URLs.
  • Perform visual/text analysis.
  • Interpret intent and propose actions.
  • Route to human reviewers for complex cases.

Impact:

Reduced ticket closure time by 59%, enabling focus on edge cases requiring deep human reasoning.

Agent Workflow:

  • URL intake – Retrieves new reports.
  • Analysis – Detects phishing attempts or copyrighted content.
  • Recommendation – Suggests an action plan.
  • Human review – Security engineer validates action.
  • Resolution – Records decision and closes ticket.

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Get Started with Agent Templates

You can start building agents today using our open-source templates:

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Scaling AI Workflows with AiToEarn

If you’re building AI agents and want streamlined publishing, analytics, and monetization, explore AiToEarn官网.

Platform benefits:

  • Simultaneous publishing across major platforms.
  • Integration with AI content generation tools.
  • Analytics and AI model ranking (AI模型排名).
  • Open-source and global reach.

Learn more in the AiToEarn博客.

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Hands-On AI Enablement

If your team needs direct guidance in building high-ROI AI projects, join our hands-on program.

For integrated AI + content strategies, platforms like AiToEarn can complement custom agent initiatives, providing:

  • Cross-platform publishing.
  • Unified analytics.
  • Monetization tools.

This synergy helps maximize both creative and technical ROI from AI.

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Do you want me to create a visual decision-making flowchart showing how to identify the “agentic sweet spot” so teams can quickly assess which tasks are best suited for AI automation? This would make the framework more actionable in presentations or documentation.

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