Summary
Replit CEO and co-founder Amjad Masad believes AI agents could fundamentally change how companies operate, with automated systems taking on routine tasks while employees focus more on judgment, planning, and creative decisions.
Speaking at TechCrunch Disrupt in San Francisco, Masad described a future in which businesses operate like “self-driving companies.” In this model, AI agents handle much of the repetitive work involved in business processes, while humans remain responsible for important decisions and determining what needs to be built.
His comments reflect Replit’s own experience integrating AI agents into its operations, particularly in software development and customer support.
What Is a Self-Driving Company?
A self-driving company is Masad’s vision of an organization where AI agents carry out a significant portion of routine operational work with less direct human involvement.
The concept does not mean that a business operates entirely without people. Instead, AI systems handle tasks that can be automated, collect relevant information, and help move work through different stages of a process.
Employees can then spend more time deciding which problems deserve attention, designing solutions, and evaluating the results produced by AI.
According to Masad, improvements in AI agents have changed how Replit works internally. He said the company has increasingly relied on agents to perform tasks that previously required more manual effort.
He also warned that many people around the world may not yet realize how quickly these changes could affect their jobs and workplaces.
How Replit Uses AI Agents in Its Operations
Masad shared an example from Replit’s customer support process to explain how AI agents can work alongside employees.
When a support request arrives, an AI agent initially examines the issue and gathers relevant information. It can review GitHub issues, inspect the codebase, and look at related tasks in Linear, helping establish the context behind the reported problem.
By the time the request reaches a human support employee, much of the preliminary investigation has already been completed.
The employee can use that information to determine the appropriate next step. If a software fix is needed, the employee can initiate another agent to help prepare a code patch.
This process allows AI agents to perform much of the initial analysis and technical work while people remain involved in evaluating the issue and deciding how to proceed.
The approach illustrates how businesses can integrate AI into existing workflows instead of treating it as a separate tool used only when employees need assistance.
Why Human Judgment Still Matters
Although Masad expects AI agents to handle more work, he does not believe human involvement will disappear.
He emphasized that people still need to exercise judgment and have a sense of what makes a solution appropriate or valuable. AI agents can gather information, generate code, and carry out assigned tasks, but human employees remain important when deciding what should be done and assessing whether the result meets expectations.
In Replit’s support workflow, for example, agents can investigate a reported problem and help implement a fix. A person still needs to evaluate the situation and determine the right course of action.
This distinction is important as AI tools become more capable. Automating a task does not necessarily mean that the broader business decision associated with it can be automated safely or effectively.
For companies adopting AI agents, the challenge will be to determine which tasks can be delegated and which require human review or approval.
Employees Could Spend More Time on Planning and Creativity
Masad said the growing use of AI at Replit has changed how employees spend their working hours.
Rather than concentrating primarily on executing individual tasks, the team is spending more time discussing what to build, planning software architecture, and deciding how to approach problems.
He described seeing more discussions and whiteboard sessions across the company as AI agents take on a larger share of the implementation work.
This shift could change the skills businesses value in their employees. Technical execution will remain important, but defining problems, prioritizing projects, reviewing AI-generated work, and making sound decisions may become increasingly significant.
For software teams, this could mean spending less time on repetitive coding activities and more time on system design, product strategy, and understanding user requirements.
However, the extent of these changes will depend on how reliably AI agents perform, how companies organize their workflows, and the complexity of the tasks involved.
AI Agents Could Change the Meaning of Productivity
AI adoption is often discussed in terms of reducing costs or completing work faster. Masad presented a broader perspective, suggesting that AI could also change the nature of employees’ daily work.
In conversations with other businesses, he said the focus has increasingly been on how AI can make employees more productive and improve their experience at work.
AI agents may be able to take over repetitive or time-consuming activities, giving employees more opportunities to work on complex problems and creative projects.
For example, a software developer could spend less time gathering information about a bug and more time evaluating different solutions. A support team could use automated analysis to understand customer issues more quickly, while employees focus on resolving difficult cases.
Whether these changes make work more satisfying will depend on how organizations implement the technology. Businesses will need to consider training, accountability, workload expectations, and the impact on employees as responsibilities change.
What Does This Mean for Businesses?
Replit’s experience offers an example of how organizations could begin incorporating AI agents into their daily operations.
Rather than attempting to automate an entire company at once, businesses can identify specific workflows where agents can collect information, perform initial analysis, prepare outputs, or assist with implementation.
Customer support, software development, internal research, and repetitive administrative processes may offer opportunities for this approach.
Companies should also establish clear boundaries for agent access, review AI-generated results, and ensure that employees can intervene when a task requires additional judgment.
A practical starting point is to select a well-defined process, measure how effectively AI agents perform it, and compare the results with the existing workflow. This can help organizations identify where automation provides genuine value and where human involvement remains essential.
Will AI Agents Replace Human Workers?
Masad’s vision suggests that AI agents may change the responsibilities associated with many jobs rather than simply removing every task currently performed by employees.
When agents handle more routine work, people may need to focus on problem definition, decision-making, coordination, and reviewing automated results. Some roles could change substantially, while others may see only limited changes depending on their responsibilities.
At the same time, automation can reduce the need for certain tasks and could affect demand for some types of work. The impact will vary by industry, company, and occupation.
The self-driving company concept therefore raises an important question for employers and workers: how can organizations use AI to improve productivity while helping people adapt to changing responsibilities?
Masad’s comments outline one possible direction, but the broader employment impact remains uncertain.
Conclusion
Replit CEO Amjad Masad’s vision of the self-driving company highlights a potential shift in how businesses organize work around AI agents.
In this model, AI systems take on routine investigation, implementation, and other operational tasks, while people focus on judgment, planning, architecture, and creative problem-solving.
Replit’s customer support workflow provides a practical example of this approach, with agents gathering information and helping prepare fixes before employees make decisions about the next steps.
As AI agents become more capable, businesses will need to decide how to integrate them responsibly into existing processes. The future of work may involve greater collaboration between people and AI, but its success will depend on reliable automation, appropriate oversight, and the ability of employees to adapt to new ways of working.