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We created autonomous AI Agents that monitor the stock market for you while you go about your day.<p>How it works: Tell our AI Assistant what you want to monitor, and it creates a project for our team of autonomous AI Agents. You'll get notifications (email + app) when significant events matching your criteria are detected. For short-term projects, you'll be notified when your analysis is ready.<p>Behind the scenes: When you give the AI Assistant a request to monitor an entity (like a stock or group of stocks), an AI Project Manager plans the project and breaks the project down into manageable tasks. These tasks run asynchronously - some recurring (hourly/daily/weekly/monthly/quarterly/yearly), others one-time.<p>Example prompts you can try: Long-term monitoring: - "Monitor Apple stock and notify me of any important events and red flags" - "Monitor Apple, Google, Microsoft, and Meta stock. Notify me if any of them start trending toward being undervalued"<p>Short-term analysis: - "Create a project to analyze the last 30 earnings calls for Tesla, spot trends, and how the business has evolved over time"<p>You can track the progress of all tasks as the AI Agents work in the background.<p>Try it here: <a href="https://decodeinvesting.com/chat" rel="nofollow">https://decodeinvesting.com/chat</a><p>This is still an early version - we're actively improving it based on feedback. Would love to hear what you think and what features you'd want to see next!<p>Previously shared our AI-powered Stock Market Research Analyst: <a href="https://news.ycombinator.com/item?id=41156478">https://news.ycombinator.com/item?id=41156478</a>
Humwork A2P Marketplace connects AI agents with verified human experts when autonomous workflows hit a wall. The platform is designed for coding agents, research agents, and operations agents that need fast human fallback on tasks they cannot resolve alone, passing context through MCP so the handoff feels native instead of manual. That makes it useful for teams deploying AI agents in production who want stronger completion rates across software engineering, design, strategy, and other knowledge work. Humwork positions itself as an always-available human layer rather than a general freelancer marketplace, with rapid matching and direct expert intervention inside agent workflows. What makes it unique is the agent-to-person model itself: it extends AI systems with on-demand human judgment instead of pretending every hard edge can be solved by automation alone.
Plaid is a financial data connectivity platform that lets apps securely link bank accounts, transactions, balances, identity data, and payment information. AI products can use Plaid to power personalized finance assistants, cash-flow analysis, budgeting guidance, underwriting workflows, and account-aware automation without building direct bank integrations from scratch. Fintech teams, personal finance apps, lenders, and AI builders working with consumer financial context can use Plaid as the data layer behind smarter financial experiences. The platform is strongest when a product needs reliable account connectivity, permissions, and compliance-friendly infrastructure. What makes Plaid stand out is its broad financial network and developer-ready APIs, which turn fragmented banking data into structured inputs that AI systems can reason over.
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Describe any recurring workflow — support triage, lead qualification, research ops, QA, reporting, or back-office reviews — and get a concrete AI agent deployment plan. The output maps the workflow into agent responsibilities, human approval points, tool access, permission scopes, failure modes, observability needs, and rollout phases. It is designed for teams that want to move from vague agent ideas to something production-ready without skipping governance.
Career & productivityUse this prompt to turn a large, messy goal into an AI execution plan that can run for days or weeks without collapsing into vague ambition. It is designed for builders, operators, researchers, and technical leads who want to use AI for multi-step work that requires decomposition, checkpoints, evidence, and human review instead of one-shot output. The prompt converts a goal into milestones, work packets, verification loops, escalation rules, memory requirements, and stop conditions so the system can keep making progress without drifting off course. It is especially useful when frontier models are getting better at endurance, delegation, and background execution, but the real bottleneck is still task design. The result is a practical operating plan for reliable long-horizon AI work, not a hypey promise about autonomy.
Career & productivityDefine your habits and get a beautiful interactive HTML habit tracker with daily check-off, streak counting, weekly heatmap visualization, and progress stats. Saves state in browser localStorage so it persists between sessions. No apps to install.
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