Charley Moore is a San Francisco–based technology executive and entrepreneur with a career spanning legal services innovation and artificial intelligence applications. Best known as the founder and longtime chief executive officer of Rocket Lawyer, Charley Moore built a legal technology platform designed to make legal services more accessible through document automation, subscription plans, and attorney networks. After retiring from Rocket Lawyer in 2025, he founded Invictus AI, an artificial intelligence company focused on designing autonomous AI agents and agent-driven workflow solutions.
Across both ventures, Moore’s work has centered on simplifying complex, multi-step processes for individuals and organizations. This focus aligns directly with how AI agents are being used today to reduce friction in tasks that involve multiple systems, conditional decisions, and repeated manual input. By applying agentic technologies to real-world workflows, Moore’s experience reflects broader trends in how AI agents can help people move from goals to outcomes more efficiently, especially in environments where time, accuracy, and coordination matter.
How AI Agents Help People Complete Complex Tasks Faster
Many digital tools promise efficiency, but people still lose time when a task involves multiple steps, scattered information, or conditional requirements. Booking a trip, filing a license application, or completing a contract often involves inputs from different platforms and dependencies that traditional tools are not built to manage. AI agents now offer a different approach; they complete tasks rather than walking users through each step.
An AI agent is a system that uses available tools to move from a goal to a result with limited supervision. Unlike a chatbot or assistant that offers prompts, an agent takes action by opening tabs, filling out fields, gathering inputs, and continuing until the task is complete. Instead of repeating a fixed sequence, an agent evaluates progress, adapts when inputs change, and chooses the next step based on what remains unfinished. That flexibility helps most when a workflow branches or requires conditional decisions.
AI agents are also changing how people interact with software, not just what gets done, but how it begins. Rather than navigating menus, clicking through forms, or juggling tabs, users can assign a task once and let the agent handle the tools and order of operations. OpenAI describes agents that can navigate websites and carry out workflows from start to finish, so a person can state an outcome and let the agent coordinate the steps that normally require repeated clicking and switching between screens.
Consider a case like filling out a small business license application. The agent can pull details from documents the user provides, populate fields, and pause to ask for review when entries are unclear or carry legal or financial consequences. That pattern keeps the person responsible for the final submission while reducing the amount of manual re-entry along the way.
While agents can handle a wide range of tasks, they perform best in situations that are low-stakes but high-frequency. Submitting internal requests, formatting reports, checking availability, or generating draft documents are all examples of repeatable actions that take time without requiring deep judgment. OpenAI and Salesforce describe practical day-to-day value when agents automate this work and reduce time lost to fragmented workflows and constant context switching.
For people handling many responsibilities at once, agents help reduce both time spent and cognitive drag. People can hand off tasks that often eat up attention, such as coordinating documents, comparing vendors, or formatting submissions, in a single step. This frees up time for more critical work and lowers the chance that small tasks get dropped due to fatigue or context switching.
Even when an agent handles most of a task, the user stays in control. OpenAI’s agent model emphasizes permission requests before consequential actions and the ability to interrupt or take over at any time. Invictus AI emphasizes privacy and user control of data, while IBM and Salesforce highlight governance practices like decision logging, access controls, and clear signals that show when an agent acts and when a person must approve or intervene. Anthropic’s safety framing reinforces why developers and product teams continue to invest in safeguards as agent capabilities expand.
As AI agents become more capable and accessible, their role may shift from specialty tool to baseline expectation. Just as search engines changed how people locate information, agents could reshape how people initiate and complete work. The next phase is not just about adoption, but about building trust in delegation, where users know what they are handing off and why the result can come back faster and with fewer interruptions.
About Charley Moore
Charley Moore is a technology entrepreneur and executive based in San Francisco. He is the founder of Invictus AI, where he focuses on building autonomous AI agents and agent-driven workflow solutions. Previously, Moore founded and led Rocket Lawyer for nearly two decades, helping expand access to legal services through technology. He holds a law degree from the University of California, Berkeley, and a bachelor of science in history from the United States Naval Academy.
