Public Launches AI‑Powered “Agents” to Automate Trading, Cash Management, and Risk Controls

Public, the brokerage that branded itself as the world’s first “Agentic Brokerage,” announced on March 31 2026 that it is rolling out a new suite of AI‑driven tools called Agents. The feature lets users define trading intent in plain language, then hands off the execution to an autonomous system that monitors market conditions and acts on the investor’s predefined rules. The rollout is currently limited to a select group of members, with a public waitlist opened at https://public.com/ai‑agents.

A new layer of automation in brokerage services

For most of the modern era, placing a trade has required a manual step—whether dialing a broker, clicking a button on a web portal, or tapping a mobile app. Public’s Agents aim to replace that manual interaction with a conversational interface that captures the investor’s strategic intent and translates it into executable actions. By shifting the user experience from “click‑to‑trade” to “describe‑what‑you‑want‑to‑do,” the company hopes to reduce the time investors spend glued to market screens and increase the precision of strategy implementation.

The launch follows Public’s earlier move in 2023 to integrate AI into its platform, a step that positioned the firm as an early adopter of generative‑AI capabilities in retail investing. Agents represent the next logical evolution: a fully automated, intent‑driven workflow that can operate continuously, reacting to market data in real time without further user intervention.

How the Agents work: intent‑based workflow and real‑time execution

Public’s description of the Agents workflow emphasizes a conversational loop between the investor and the AI. Users start by stating a high‑level objective—such as “generate $5,000 per month in covered‑call premiums” or “sweep excess cash into a direct index when my checking balance exceeds $20,000.” The AI then asks clarifying questions to flesh out the parameters, timing, and risk thresholds. Once the investor confirms the logic, the Agent is activated and begins monitoring the market on the user’s behalf.

Key aspects of the system include:

• Real‑time market monitoring – Agents stay connected to live price feeds and can trigger actions the instant predefined conditions are met.
• Granular condition setting – Users can specify exact price moves, time windows, and portfolio exposure limits.
• Follow‑up prompts – The AI can request additional details before committing to a rule, ensuring that the final workflow matches the investor’s intent.
• One‑click activation – After the dialogue concludes, the Agent is launched with a single confirmation, after which it operates autonomously.

Sample use cases illustrate flexibility

Public supplied three illustrative prompts to demonstrate the breadth of strategies that Agents can support:

• Generate covered‑call income – “Help me generate $5,000 per month in covered‑call premiums across my portfolio.”
• Momentum‑based options play – “If SPY drops more than 1 % in the first 30 minutes of trading, buy same‑day call and put options.”
• Cash‑sweep automation – “If my checking account balance exceeds $20,000, sweep the excess into my direct index.”

These examples show that Agents can be tailored for income generation, tactical options trading, and cash‑management automation—all without the user having to monitor price movements or manually place orders.

Transparency, security, and compliance considerations

Public stresses that every action taken by an Agent is logged in a detailed audit trail. Investors can review the full history of trades, see the exact trigger conditions that fired, and pause or terminate any Agent at will. This level of visibility is intended to address common concerns around black‑box AI decisions in financial services.

Security is another focal point. Public notes that Agents operate entirely within its “financial‑grade infrastructure,” meaning they never execute code on external servers or the open internet. All processing occurs inside a secured, authenticated environment that complies with industry standards for data protection and transaction integrity. The company’s architecture is designed to prevent rogue behavior, ensuring that an Agent cannot act outside the bounds defined by the user.

Strategic positioning and market implications

By introducing autonomous agents, Public is positioning itself at the intersection of AI, brokerage services, and workflow automation. The move could have several ripple effects:

• Competitive differentiation – Few brokerages currently offer a conversational, intent‑driven automation layer. If Public can scale the feature beyond its initial cohort, it may force incumbents to accelerate similar AI initiatives.
• Operational efficiency for investors – Automating routine monitoring and execution tasks can free up capital managers and retail investors alike, potentially leading to higher portfolio turnover efficiency and better risk adherence.
• Regulatory scrutiny – Automated trading tools have historically attracted attention from regulators concerned about market manipulation and systemic risk. Public’s emphasis on transparency and internal execution may help mitigate such concerns, but ongoing dialogue with bodies like the SEC will be essential as the feature matures.
• Data‑driven product development – The interaction logs generated by Agents could provide Public with rich, anonymized data on investor behavior, informing future product enhancements and personalized services.

Industry context: AI adoption in fintech

The broader fintech landscape has seen a surge in AI‑driven solutions over the past few years, from robo‑advisors that allocate assets based on risk profiles to AI‑enhanced fraud detection systems. However, most of these tools operate in a batch or periodic mode, rather than executing trades in real time based on live market conditions.

Public’s Agents blur that line, combining the conversational UI of generative AI with the low‑latency execution capabilities of a brokerage. This hybrid approach aligns with a growing trend toward “embedded finance,” where financial functions are woven directly into user workflows rather than existing as standalone services. If successful, the Agents model could inspire new categories of AI‑powered financial agents that operate across banking, payments, and lending ecosystems.

What this means for investors and competitors

For investors, the immediate benefit is a reduction in the manual effort required to implement complex strategies. A user who previously needed to track SPY price movements, calculate option premiums, and place orders manually can now delegate those steps to an Agent, intervening only when the AI seeks clarification. The transparency features also provide a safety net, allowing investors to audit and adjust the automation as market conditions evolve.

Competitors may view Public’s launch as a signal that the market is ready for deeper AI integration. Traditional broker‑dealers, as well as fintech platforms that focus on API‑first solutions, could explore similar intent‑based automation layers to retain client engagement. The key differentiator will likely be the quality of the conversational AI, the robustness of the execution engine, and the degree of regulatory compliance built into the product.

Looking ahead

Public’s Agents are currently available to a limited group of members, with a broader rollout anticipated as the company refines the technology and gathers user feedback. The firm has opened a waitlist for interested investors at https://public.com/ai‑agents, indicating that demand for autonomous trading tools may already be outpacing supply.

As AI continues to mature and regulatory frameworks adapt, the line between advisory and execution functions may blur further. Public’s initiative suggests that the next frontier for fintech is not just smarter advice, but truly autonomous action—performed at machine speed, governed by human intent, and audited with full transparency.

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