Key takeaways
- Agentic AI is defined by action towards a goal, not by the content it writes.
- Its basic loop is reason, act, observe, then repeat until the goal is met or it stops.
- Most agentic systems are built on generative models, which they use inside that loop.
- Once AI can act, approvals, limits and logs matter more than with a chatbot.
How agentic AI works
Agentic AI works by repeating a loop of reasoning, acting and observing. The system breaks a goal into a next step, calls a tool to carry it out, reads what came back and uses that to decide the following step.
Research on this pattern, known as ReAct, showed that interleaving reasoning steps with actions such as searches helps a language model base its answers on fetched information and leaves a trace a person can follow. Many agentic systems today follow some version of the loop, with tools for search, email, calendars, files and business systems.
Agentic AI vs generative AI
Generative AI produces content in response to a prompt, while agentic AI uses that ability inside a loop that takes actions towards a goal. Ask a generative model for a prospecting email and it writes one. Ask an agentic system to run a prospecting task and it may search for companies, add records, draft emails and report back.
The two are not rivals. An agentic system usually has a generative model at its centre, choosing steps and writing text, with tools and rules around it.
AI agents vs agentic AI
An AI agent is a single system that acts on someone's behalf; agentic AI is the broader approach and the quality of acting with some independence. A product can be more or less agentic depending on how many steps it takes alone and what it may do without asking.
In sales, the detail of what an agent does day to day belongs to the AI sales agent; this page covers the general idea.
Agentic workflows in go-to-market
An agentic workflow strings several actions together towards one outcome. An illustrative go-to-market request: find ten companies that fit our ideal customer profile, add the right people to the CRM and draft a first email to each.
Done well, the system searches, filters, writes records and drafts, and a person approves the CRM writes and the sends. Done badly, it adds the wrong people, writes generic emails and sends them before anyone looks. The difference lies mostly in the limits and approvals around the loop, not in the model.
Why oversight matters once AI can act
Oversight matters more for agentic AI because its mistakes become actions: an email sent, a record overwritten, a meeting booked. An error early in a chain can carry through every later step.
Teams manage this with approvals for actions that reach the outside world, limits on what the system may touch, and logs of what it did. Hard rules help here, such as never contacting an opted-out address. Research that pairs neural models with explicit symbolic rules sees such rules as one way to keep a learned system inside limits a person can read and check.
Where Pebbles Ai fits
- CapabilityAI workspaceThe Marketing and Strategy assistants carry out multi-step go-to-market work in chat, and an assistant can delegate work to another from inside the chat.
- FoundationIntegrationsSends, CRM writes and MCP calls follow the execution mode you pick: Manual asks for approval first, Plan queues them and Auto runs them. Template send and calendar delete ask every time, whatever the mode.
Common questions
What is an example of agentic AI?
A system asked to book a meeting that checks calendars, finds a free slot, drafts the invitation and sends it once a person approves, adjusting if a guest declines.
Is agentic AI the same as automation?
No. Traditional automation follows fixed steps set in advance, while agentic AI chooses its next step based on what it finds along the way.
What are the main risks of agentic AI?
Actions taken on wrong information, errors that compound across steps and work that is hard to trace afterwards. Approvals, limits and logs reduce these risks.
About this page. Written by the Pebbles Ai team for people who run sales, marketing and growth. Last updated .
