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100 AI Agents in 100 Days 2026
Rating: 4.2 out of 5(1,410 ratings)
54,362 students
Last updated 2/2026
English

What you'll learn

  • Build 100 independent, real-world AI agents that solve practical problems across multiple domains.
  • Design autonomous AI systems using decision logic, memory, monitoring, and recovery patterns.
  • Implement ethical guardrails, human-in-the-loop approvals, and safety controls for AI agents.
  • Translate business workflows into deployable AI agents for operations, marketing, HR, and finance.
  • Create production-ready AI agents that are observable, explainable, and resilient.
  • Apply structured agent architectures instead of prompt-only or ad-hoc AI solutions.
  • Build AI agents that learn and improve using feedback and controlled self-improvement loops.
  • Confidently design and deploy custom AI agents without relying on black-box tools.

Course content

10 sections201 lectures7h 55m total length
  • Certificate of Completion0:29
  • Day 1: Daily task prioritization agent2:51
  • Day 1: Daily task prioritization agent (Implementation)4:26
  • Day 2: Email summarization agent1:39

    Use an email summarization agent to reduce inbox overwhelm by distilling messages into concise summaries, identifying what the email is about, highlighting decisions, extracting action items, and flagging urgency.

  • Day 2: Email summarization agent (Implementation)1:37
  • Day 3: Calendar conflict resolver agent1:53

    Analyze your schedule with the calendar conflict resolver agent that uses structured calendar data beyond start and end times to detect conflicts and offer priority-aware, transparent resolutions.

  • Day 3: Calendar conflict resolver agent (Implementation)1:47
  • Day 4: Meeting agenda generator agent1:42

    Turn vague meeting goals into a focused agenda with topics, time boxed items, and outcomes, assign owners, to enable efficient, decision oriented meetings with clear accountability.

  • Day 4: Meeting agenda generator agent (Implementation)1:30
  • Day 5: Personal knowledge base agent1:35

    Create a personal knowledge base agent that acts as external memory, turning messy notes into a structured, meaning-based retrieval system with embedded metadata and reasoning over sources.

  • Day 5: Personal knowledge base agent (Implementation)1:40
  • Day 6: Daily goal reflection agent1:26

    Evaluate planned versus actual outcomes to convert daily work into a feedback loop that improves decision making and prioritization. Incorporate optional context and deliver concise, forward looking insights for tomorrow.

  • Day 6: Daily goal reflection agent (Implementation)1:27
  • Day 7: Smart reminder agent1:20

    The smart reminder agent uses urgency, deadlines, and task context to deliver relevant reminders, escalates for high-priority tasks, and schedules a plan across notifications, emails, and calendar nudges.

  • Day 7: Smart reminder agent (Implementation)1:17
  • Day 8: Note-to-action item agent1:21
  • Day 8: Note-to-action item agent (Implementation)1:23
  • Day 9: Time-blocking planner agent1:15
  • Day 9: Time-blocking planner agent (Implementation)1:15
  • Day 10: Habit tracking agent1:18

    Track behavior to turn habits into measurable systems, emphasizing momentum over perfection. The day ten habit tracking agent reveals streaks, consistency, and early warning signs to guide adjustments.

  • Day 10: Habit tracking agent (Implementation)1:35

Requirements

  • No prior AI or machine learning experience required — everything is built step by step.
  • Basic computer literacy (using files, folders, and running simple commands).
  • Willingness to learn by building one small, practical project per day.
  • A computer with internet access (Windows, macOS, or Linux).
  • Basic familiarity with any programming language is helpful but not required.
  • Curiosity about AI agents and automation across real-world use cases.
  • An OpenAI account or equivalent LLM access for running the agent examples.

Description

Disclaimer: This course contains the use of artificial intelligence(AI).

100 AI Agents in 100 Days is a deeply practical, project-driven course designed to take you from basic AI concepts to building production-ready autonomous AI systems—one agent at a time. Instead of focusing on abstract theory or one large capstone, this course is built around 100 independent, real-world AI agent projects, each designed to solve a specific problem you’ll actually encounter in work and business.

Every single day introduces a new, standalone AI agent. That means there are no dependencies between lessons—you can start anywhere, move at your own pace, and revisit projects whenever you want. Whether you’re interested in productivity, content creation, business operations, marketing, finance, engineering, governance, or advanced autonomous systems, this course gives you hands-on experience across the full spectrum of modern agentic AI.

You’ll begin by building practical personal productivity agents such as task prioritizers, email summarizers, habit trackers, and time-blocking planners. From there, you’ll move into writing, research, and analysis agents that generate content, summarize complex information, and extract insights from data. As the course progresses, you’ll build business-focused agents for operations, marketing, HR, legal, finance, and automation—exactly the kinds of systems organizations are actively adopting.

What truly sets this course apart is its focus on real-world readiness. You won’t just learn how to prompt a model. You’ll learn how to design agents with clear decision logic, memory, monitoring, error recovery, human-in-the-loop approvals, ethical guardrails, and governance. By the final days, you’ll be building advanced systems such as multi-agent collaboration frameworks, autonomous decision agents, self-improving agents, and a fully production-ready autonomous AI agent that brings everything together.

This course is intentionally designed to be beginner-friendly while still going deep. No prior AI or machine learning experience is required. Concepts are introduced clearly, step by step, with an emphasis on building and understanding rather than memorization. At the same time, experienced developers, founders, and technical professionals will find strong architectural patterns, system design principles, and real deployment considerations throughout.

By the end of the course, you won’t just have knowledge—you’ll have 100 completed AI agent projects, a strong agentic mindset, and the confidence to design, customize, and deploy AI agents independently. Whether your goal is to advance your career, build AI products, automate workflows, consult for clients, or simply understand where AI is truly headed, this course equips you with skills that are practical, modern, and immediately usable.

This is not a course about AI hype. It’s a course about building AI that actually works.

Who this course is for:

  • Aspiring AI engineers and developers who want hands-on experience building real AI agents.
  • Software engineers and technical professionals looking to move beyond prompts into agentic AI systems.
  • Founders and startup builders who want to automate workflows and build AI-powered products.
  • Product managers and tech leaders seeking practical understanding of autonomous AI systems.
  • Data, operations, and automation professionals who want to apply AI to real business processes.
  • Career switchers and self-learners looking for a structured, project-based path into AI agents.
  • Consultants and freelancers who want to deliver AI agent solutions to clients.
  • Students and lifelong learners interested in building production-ready AI systems, not just theory.