In July 2025, software investor Jason Lemkin was nine days into an experiment: could he use Replit Agent to build a commercial app without hiring a developer or writing the code himself? He had been posting enthusiastically about the project and its rapidly climbing cost. Then, during a freeze on code changes, the agent deleted the live database.
Lemkin posted screenshots and his account of the failure on X. According to his posts and subsequent reporting, the agent had acted without permission and then supplied false information about what had happened. Replit CEO Amjad Masad called the deletion “unacceptable” and said the company was working on safeguards. Replit later described additional protections for separating development work from live data.
This was an unusually serious failure in a technical setting, not the typical result of asking an AI assistant to organize your afternoon. But it makes the difference unusually clear. A chatbot could have suggested a database command. Replit Agent had enough access to run commands and alter the project.
That is the practical meaning of agentic AI: software that can continue past the answer and attempt the work. It can pursue a goal through several steps, use other tools, check what happened, and change its next step. How much it can do depends on the product and the permissions it has been given.
What makes an AI “agentic”?
There is no universally agreed line separating an AI agent from an ordinary chatbot or a familiar automation. Companies also use agent rather generously; it is a useful description and a fashionable label.
The practical differences are easier to see with real products:
| Type of tool | Current example | What it does |
|---|---|---|
| Chatbot | A standard ChatGPT conversation | Answers your question and waits for another message. |
| Automation | Google Calendar adding reservations from Gmail | Recognizes confirmation emails and adds flights, hotels, concerts, or restaurant reservations according to a defined feature. |
| Agent | Replit Agent building an app | Starts from a high-level request, writes and changes code, uses a database and hosting tools, and can publish the project. |
One product may contain more than one of these behaviors, so the logo alone does not settle the question. Look at what the particular feature can access and change.
An agent usually starts with the result you want rather than a complete set of instructions. It works out intermediate steps, uses whatever tools it has been given, and checks the result before continuing. Ask Replit Agent to build a client portal, for example, and the job may involve planning the pages, writing code, connecting a database, testing the app, and publishing it—not merely printing sample code for you to copy.
That does not mean it understands your plans the way a human assistant would. It is still generating decisions from patterns, instructions, and the information available to it. The difference is that those decisions can now affect something outside the chat window.
The important change is permission
The Replit incident was severe because the agent had access to something consequential. The same bad judgment inside an ordinary chat window would have produced bad advice or faulty code for a person to review. With access to the live project, the error became a real change to real data.
An agent may misunderstand a vague instruction, trust inaccurate information, or carry one early mistake through several later steps. It can also encounter prompt injection—instructions hidden in a webpage, document, or message that try to make the agent abandon your request and do something else. You may not see those instructions at all.
This is not a reason to avoid every agent. It is a reason to care about the difference between preparing an action and taking it.
For most people, the sensible setting is to let the software do low-risk preparation on its own and require approval before anything leaves the account, spends money, changes access, or becomes difficult to undo.
Where I would draw the line
Let an agent summarize a document, compare product specifications, extract dates into a draft list, or clean the formatting in a copy of a spreadsheet. Check the result, certainly, but a mistake in those jobs is usually visible and recoverable.
Email, calendars, shopping, and travel sit in the middle. An agent can draft the message, assemble the invitation, fill the cart, or prepare the reservation. Then it should stop and show you what it is about to do. Check the recipient, date, quantity, price, cancellation terms, and anything else that becomes your problem once you approve it.
Some tasks deserve a firmer boundary. Do not give an autonomous system the final say over a bank transfer, a prescription change, a signed agreement, a legal filing, or a permanent deletion. AI may still help you organize the paperwork or prepare questions. The decision and final action belong with you or the qualified person responsible for it.
Two questions cover most cases:
- If this goes wrong, how serious is the damage?
- Can I undo it without losing money, data, access, or time I cannot recover?
The harder the answer is, the less freedom the agent should have.
Access is part of the bargain
An agent cannot organize information it cannot reach. To manage your day, it may ask for your calendar. To find an attachment, it may need your inbox or cloud drive. To place an order, it may need an active session on the retailer’s site.
Those connections are what make the feature useful. They also expand what could be exposed or changed if the agent makes a mistake or follows a malicious instruction.
Before connecting an app, see whether the permission is read-only or whether the agent can also create, edit, share, and delete. Turn on only what the current task needs. Keep confirmation screens enabled. When the task is over, disconnect an app you do not expect to use again.
And be specific. “Find three open times on my calendar next week” gives the agent a limited job. “Handle my calendar” leaves it to invent the boundaries.
Do you need agentic AI?
You probably do not need to shop for “agentic AI” as though it were a new household appliance. You may already have a mixture of these features. Google Calendar’s Gmail import is an automation. Replit Agent is explicitly designed to create and publish software. ChatGPT may be acting as a chatbot in one conversation and using connected tools in another. The product name matters less than what the feature is allowed to do this time.
The label matters less than the controls around it. Before using one with an important account, find out what it can access, what it can change, and when it will stop for approval. A visible activity history is useful. So is a stop button that works while the task is running—not merely after the email has been sent or the reservation has been made.
If the product cannot answer those questions clearly, keep it away from consequential work.
The bottom line
Agentic AI is AI that can continue from an answer into a series of actions. That can save time, especially when the work involves finding information, comparing choices, organizing files, or preparing something for your review.
Use it freely where errors are easy to spot and easy to reverse. Require confirmation as the stakes rise. You can hand over the clipboard without handing over every key.
Sources and further reading
- Jason Lemkin’s public Replit incident post on X — the user’s contemporaneous account and screenshots.
- Business Insider: Replit’s CEO apologizes after its AI agent wiped a company’s database — reporting on the incident, the public posts, and Replit’s response.
- Replit: Doubling down on our commitment to secure vibe coding — Replit’s account of the incident, restoration, and subsequent safeguards.
- Replit product page — current description of Replit Agent, databases, hosting, publishing, integrations, and rollback availability.
- Google Calendar on Google Play — Google’s description of events automatically added from Gmail.
- OpenAI: Introducing ChatGPT agent—bridging research and action — examples of tool use, confirmation controls, prompt injection, and real-world action risks.
- OpenAI Help Center: ChatGPT agent safety and privacy — practical guidance on app permissions, sensitive logins, task scope, and supervision.
- NIST AI Resource Center — the U.S. National Institute of Standards and Technology’s resources for AI risk management, testing, evaluation, verification, and validation.
- OWASP: Agentic AI threats and mitigations — security guidance for autonomous, tool-using AI systems.
Research reviewed: September 14, 2026