AI That Takes Action: Understanding & Working With AI Agents

For teams starting to use AI agents that take actions, not just answer questions.

Format
Live online or in person
Length
30 minutes to full day
Topic
Learning & Professional Development
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About this session

Most employees first encounter AI through an assistant: ask a question, receive an answer, decide what to do next. AI agents change that pattern.

Instead of requiring a person to specify every step, an agent can be given a goal, access to selected tools and rules about what it may do, then determine some of the intermediate actions required to move the work forward.

For example, an agent might review an approved information source, identify items requiring attention, prepare a summary, update a permitted workspace and return exceptions to a person. Another might research a defined set of sources, compare results and prepare a brief.

The important change is not that the AI has become a person. It is that the system has been given enough goal, context, tools and action authority to continue through multiple steps without a person specifying every one.

That capability creates both opportunity and risk. An incorrect AI answer is one thing; an incorrect AI answer that triggers an external action can have a larger consequence.

Participants therefore learn to think about agents in terms of goals, permissions, actions, observability and stopping conditions — not simply intelligence.

The session then turns agent literacy into practical working skill. Participants learn how to identify appropriate bounded use cases, define what an agent is allowed to do, establish checkpoints and escalation and review what happened after the agent acted.

The goal is not maximum autonomy. It is understanding when agentic AI can reduce coordination effort while keeping organizational accountability, visibility and human judgment intact.

What your people take away

  • Explain the practical difference between AI assistants, fixed workflows and AI agents
  • Understand how goals, tools, permissions, context and feedback shape what an agent can do
  • Identify workplace tasks suitable for bounded agentic support and recognize poor agent use cases
  • Define clear goals, success criteria, action boundaries, stop conditions and human handoffs
  • Monitor agent activity and review both the final output and the actions taken to produce it
  • Start with appropriately bounded pilots and increase autonomy only when evidence supports doing so

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  • What each length covers, 30 minutes to full day
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What each length covers

30 minutes

30 Minutes — Key Points: Understand What Makes AI Agentic

A focused 30-minute session on three key points from Understand What Makes AI Agentic: from response to action, goal + tools + permissions and observe, act, observe again.

  • From response to action
  • Goal + tools + permissions
  • Observe, act, observe again

Covers 3 of 4 points in Understand What Makes AI Agentic.

60 minutes

Understand AI That Can Take Action

A focused introduction to AI agents. Participants distinguish assistants, workflows and agents, examine how agents use tools and permissions and design one bounded agent use case with clear human controls.

  • AI assistants vs. agents
  • Agentic AI
  • Goals
  • Tools
  • Permissions
  • Agent loops
  • Bounded autonomy
  • Agent suitability
  • Stop conditions
  • Human checkpoints
  • AI Agent Canvas
  • Live Q&A

Covers 1 of 4 parts: Understand What Makes AI Agentic.

90 minutes

How to Work With an AI Agent

The extended session follows the complete agent lifecycle from understanding goals and tools through use-case selection, permissions, handoffs, monitoring, exceptions and safe increases in autonomy.

  • Agent vs. assistant
  • Agent vs. workflow
  • Goals
  • Planning
  • Tools
  • Permissions
  • Memory and state
  • Agent loops
  • Use-case selection
  • Reversibility
  • Success criteria
  • Stop conditions
  • Human handoffs
  • Checkpoints
  • Monitoring
  • Agent testing
  • Autonomy
  • Live Q&A

Covers 2 of 4 parts: Understand What Makes AI Agentic and Choose Work an Agent Should Actually Do.

3 hours

Covers 3 of 4 parts: Understand What Makes AI Agentic, Choose Work an Agent Should Actually Do and Set the Goal, Boundaries & Human Handoffs.

Full day

AI Agents at Work Application Lab

A hands-on full-day workshop covering all four modules. Participants examine realistic agent use cases, define goals and permissions, design human handoffs and test how an agent should behave across normal and exception scenarios.

  • Module 1 — Understand What Makes AI Agentic
  • Module 2 — Choose Work an Agent Should Actually Do
  • Module 3 — Set the Goal, Boundaries & Human Handoffs
  • Module 4 — Supervise the Agent Without Doing the Work Twice
  • Assistant / Workflow / Agent Sort
  • Agent Goal Builder
  • Tool & Permission Map
  • Agent Loop Exercise
  • Agent Suitability Review
  • Consequence & Reversibility Check
  • Success Criteria Builder
  • Stop Condition Design
  • Human Handoff Planner
  • Checkpoint Design
  • Agent Activity Review
  • Normal-Case Test
  • Edge-Case Test
  • Autonomy Decision Review
  • Live Q&A

Covers all 4 parts.

Also available as a 4-week or 8-week program, for change that lasts. Ask us about it.

What’s covered

Understand What Makes AI Agentic

Every length
  • From response to actionParticipants compare an AI assistant that responds to a prompt with an agent that can continue through multiple steps toward a defined goal.
  • Goal + tools + permissionsAn agent needs more than a model.
  • Observe, act, observe againParticipants learn the basic agent loop: assess the current situation, choose an action, use a tool or produce an intermediate result, observe what happened and decide what should happen next.
  • Autonomy is a spectrumSome systems may only recommend the next action.

Choose Work an Agent Should Actually Do

90 minutes and longer
  • Look for bounded goalsGood early agent use cases have a clear outcome, known operating environment and enough structure for success or failure to be recognized.
  • Look for multi-step coordinationAgents may add value where a person currently has to move repeatedly between information, tools and routine intermediate steps.
  • Consider reversibility & consequenceA draft workspace update is easier to reverse than an external financial commitment.
  • Know the poor agent use casesParticipants identify situations dominated by ambiguous goals, sensitive human judgment, unpredictable edge cases, weak source information or high-consequence decisions.

Set the Goal, Boundaries & Human Handoffs

3 hours and longer
  • Define success clearlyParticipants specify what outcome the agent is expected to produce and what evidence would indicate that the task is complete.
  • Limit tools, information & actionsParticipants identify the minimum information, systems and action rights the agent requires in order to complete the task.
  • Create stop & escalation conditionsParticipants define circumstances where the agent should stop, request information or hand the task to a person.
  • Use checkpoints where consequences increaseParticipants identify actions that may need human confirmation before execution.

Supervise the Agent Without Doing the Work Twice

Full day only
  • Make the agent's work observableParticipants examine the importance of being able to see relevant actions, tool use, outputs, exceptions and escalation rather than receiving only a polished final answer.
  • Review actions as well as outputsAn apparently correct final output can conceal an inappropriate action, weak source or unnecessary system change.
  • Test normal & abnormal casesParticipants test agents against expected cases as well as missing information, tool failure, ambiguous requests, unusual inputs and other edge conditions.
  • Increase autonomy with evidenceParticipants start with limited action rights, review actual performance and expand scope only when the evidence supports doing so.
Live Q&ATime for your people’s questions, answered by the expert.
60 minutes and longer

Tools and materials

  • Assistant / Workflow / Agent Guide
  • Agent Anatomy Map
  • Agentic Capability Spectrum
  • Agent Goal Builder
  • Agent Loop Mapper
  • Agent Use-Case Finder
  • Agent Suitability Matrix
  • Consequence & Reversibility Check
  • Tool & Permission Map
  • Minimum Access Review
  • Stop & Escalation Planner
  • Human Handoff Planner
  • Agent Activity Review
  • Agent Test Pack
  • Workplace AI Agent Playbook

Who it’s for

  • Employees who understand basic generative AI and want to understand the next shift toward agentic systems
  • Managers preparing for AI agents to enter team workflows
  • Operations and transformation professionals evaluating agent use cases
  • HR, finance, sales, customer, marketing and corporate-function teams encountering AI agents in workplace platforms
  • Technology-adjacent business professionals who need agent literacy without becoming developers
  • Organizations preparing employees for a future in which AI can increasingly act across approved workplace tools and systems

How booking works

  1. Book online. Create a free Workbliss profile, then pay with session credits, by card or by invoice.
  2. Pick a date. Choose a date at least 14 days ahead, or book now and set the date later.
  3. Choose your expert. Within 3 working days, we send you profiles of the experts available for your date.
  4. We deliver it. Your expert is briefed on your people and goals, then runs the session live online or at your site.

Questions about AI That Takes Action: Understanding & Working With AI Agents

How long is AI That Takes Action: Understanding & Working With AI Agents?

AI That Takes Action: Understanding & Working With AI Agents runs as 30 minutes, 60 minutes, 90 minutes, 3 hours or full day. You choose the length when you book. A 30-minute session covers three key points from Understand What Makes AI Agentic: from response to action, goal + tools + permissions and observe, act, observe again. A 60-minute session covers Understand What Makes AI Agentic in full, with a live Q&A. A 90-minute session adds Choose Work an Agent Should Actually Do. A 3-hour session adds Set the Goal, Boundaries & Human Handoffs. A full-day session adds Supervise the Agent Without Doing the Work Twice. It is also available as a 4-week or 8-week program.

Can AI That Takes Action: Understanding & Working With AI Agents be delivered online or in person?

Yes, both. It runs live online, so every office can join at the same time, or in person at your site, in any country.

How do we book AI That Takes Action: Understanding & Working With AI Agents?

Create a free Workbliss profile with your work email, then open AI That Takes Action: Understanding & Working With AI Agents to see the price for each length and book it. You can pay with session credits, by card or by invoice, and choose a date at least 14 days ahead, or set it later.

Who leads the session?

A vetted Workbliss expert, briefed on your people, culture and goals before the session. After you book, we send you profiles of the experts available for your date within 3 working days, so you can choose who leads it.

Can it be tailored to our company?

Yes. Every session is shaped around your goals, your people and the benefits you already offer, and delivered by experts in your people’s languages.

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