Introduction to AI Agents
Driving Business Value
Want to accelerate your AI adoption?
Module 1: What is an AI Agent?
1.1 How Can Businesses Adopt AI?
It is possible to automate almost anything a human does on a computer using AI, which is simultaneously fantastic and extremely daunting. To help businesses address that challenge more effectively, we often use the following framework.

Fifty One Degrees supports businesses with projects on each of these layers.
Product or Service
The core product or service the business provides to its customers. At this layer, we often build mission-critical software applications that use AI from code, that can transform the way a business operates.
Teams
Within the business there are often many teams which undertake the work. Here, we often build AI agents using platforms, to automate tasks for teams.
Individual Contributors (ICs)
Every team member that works for the business. For the IC layer we implement LLM providers fully, whilst also supporting businesses with training, policies, adoption, communication and more.
1.2 What is an AI Agent?
Beyond Simple Automation
An AI agent is an automated teammate that transforms how we tackle complex tasks.
  • Unlike traditional automation (rigid scripts), AI agents:
  • Understand goals
  • Formulate strategic plans
  • Intelligently select and use tools
  • Act autonomously
Key Distinction:
  • A chatbot answers questions (based on patterns).
  • An AI agent acts with purpose and intention.
Think of it as a shift from reactive to proactive technology, working independently to achieve your business objectives.

Key Insight: AI agents reason, plan, and execute multi-step workflows autonomously, they don't just respond.
1.3 How Do AI Agents Work?
An AI agent operates in a simple yet powerful cycle, coordinating multiple components for intelligent automation. Understanding this cycle helps you design effective agent workflows.
1
Trigger
The starting signal that activates the agent. This could be a new email, a Slack message, a scheduled time, or an event in your CRM.
2
Tools & Integrations
The diverse applications the agent connects to and controls. This includes website scraping, databases, Google Workspace, Slack, CRM systems, and other APIs.
3
Logic
The Large Language Model (LLM) at the core. It interprets the goal, analyzes context, plans, and makes intelligent decisions on which tools to use and when.
4
Actions
The specific tasks the agent executes using its tools. Examples include reading documents, drafting replies, updating records, posting updates, or generating reports.
1.4 What Are The Benefits of Each Approach?
From Code
Build agents with custom code for ultimate control.
  • Maximum flexibility and customization
  • Ideal for complex enterprise workflows
  • Requires development resources
  • Best for mission-critical applications
Perfect for: Teams with dedicated developers building unique, critical systems.
Low-Code Platforms
Empower teams to build agents quickly, no extensive coding needed.
  • Rapid development and iteration
  • Pre-built integrations and templates
  • Balance of power and usability
Perfect for: Quick departmental deployments and specific workflows.
Examples: Relevance AI, n8n, CrewAI
AI Platform Browsers
Automate web tasks by observing human actions with specialized browsers.
  • No coding or integration required
  • Immediate deployment capability
  • Focus on web-based workflows
Perfect for: Automating repetitive web tasks without technical overhead.
Examples: OpenAI Atlas, Perplexity Comet, Strawberry Browser
Module 2: AI Agents in Action
2.1 Why AI Agents for Talent Acquirers?
When you registered, we asked a simple question: "Which tasks use up most of your time?"
The results were clear. Your biggest time-drains are:
  1. Sourcing & Research: Including market mapping, finding new talent, and initial candidate outreach.
  1. Screening & CV Review: Sifting through high volumes of applications and reviewing CVs for basic suitability.
  1. Scheduling: The endless back-and-forth of arranging and rescheduling interviews and meetings.
  1. Reporting & Documentation: Writing interview summaries, tracking metrics, and filling out placement sheets.
  1. Candidate Communication: Replying to every candidate and providing timely, consistent feedback.
These aren't just admin tasks; they are the critical-but-repetitive bottlenecks that pull you away from high-value work like building relationships and strategic planning.

Key Takeaway: Business Value
Automate the mundane, focus on the value-add
2.2 How to Prioritise: A Smart Framework
Don't try to automate everything at once. Start smart.
1. Start with Quick Wins What: Simple, repetitive, low-risk tasks.
  • Examples: CV Screening, Initial Scheduling, Note Summarisation.
  • Benefit: Fast results, builds confidence, low risk.
2. Build Towards Strategic Automation What: Complex tasks requiring memory or judgment.
  • Examples: Proactive Sourcing, Ongoing Candidate Comms.
  • Benefit: Massive scalability, high long-term value.

Key Considerations for Prioritisation
  • Human-in-the-Loop (HITL): Keeping a human review step is essential. It not only ensures quality and reduces risk, but it also significantly speeds up the build time.
  • Task vs. Communication: Automating simple, repetitive tasks (like screening) is straightforward. Automating sophisticated, two-way communication (like ongoing candidate emails) is significantly more complex.
  • Prioritisation Framework: Analyse every task for Impact vs. Sophistication & Risk model. Start with tasks that are High Impact and Low Sophistication/Risk—these are your quick wins.
2.3 Deep Dive: Today's CV Screener Demo
This simple agent is designed to tackle your #2 bottleneck: CV sifting.
How This Single Agent Works
  1. Trigger: You upload CVs and your key Screening Criteria.
  1. Logic: The agent analyzes each CV against your customised rules.
  1. Action: It outputs a Google Sheet with each Name, Verdict (Pass/Reject/Re-route), and the results against your rules.
Possible future evolution?
  • Access: Connect the agent to Slack to improve access.
  • Scheduling: Following your approval, email the "Pass" candidates with a diary link for scheduling.
The Big Picture: From One Agent to an AI "Team"
This demo is just one building block. The real power is combining agents into a system:
  • Agent 1 (Sourcing): Scans profiles 24/7.
  • Agent 2 (CV Screener): Creates the shortlist (Today's Demo).
  • Agent 3 (Scheduler): Emails "Pass" candidates your booking link.
  • Agent 4 (Summariser): Transcribes your interview notes.
  • Agent 5 (Feedback): Drafts rejection/feedback emails for your approval.
Key Takeaway: You can automate the process, freeing you to focus on the people.
Module 3: Live Demo
3.1 The Foundations: Best Practices
Before we dive into the live demos, let's cover some foundational best practices for building successful AI agent projects. These tips come from real-world experience and will help you avoid common issues and speed up your development.
Craft Your Prompts in a repository
Keep your prompts and agent configurations in a central and secure place, such as Google Docs or Notion. This ensures a single source of truth for your team.
  • Track changes & collaborate
  • Maintain prompt libraries
  • Document what works (and what doesn't)
Build Prompts Iteratively
Start small: create a minimal agent for one core task. Test it, get feedback, then gradually add complexity.
  • Begin with core functionality
  • Test each addition independently
  • Build confidence progressively
Use LLM "Chaining"
Use a powerful LLM (like Gemini or GPT-4) as the "brain" to generate structured prompts. Then, direct specialized tools to execute specific tasks.
  • Separate thinking from execution
  • Leverage specialized tool strengths
  • Enable complex workflows
3.2 Live Demo - CV Screening
Want to accelerate your AI adoption?
Thank You & Questions
  • I hope this session sparked some ideas for leveraging AI agents in your work.
  • Now, let's open the floor for your questions and feedback.