Designing and Building AI Products, Services, and Agentic Solutions
Empower yourself to turn AI opportunities into business-ready solutions
What Is MIT xPRO’s Designing and Building AI Products, Services, and Agentic Solutions Program?
The MIT xPRO Designing and Building AI Products, Services, and Agentic Solutions program is a 10-week online program that builds the skills professionals and entrepreneurs need to take an AI-based product from concept to pitch. As a participant, you will work through core technology and business design principles that hold across domains and functions. The program will conclude with each participant, including you, developing an AI-based product proposal suitable for their organizations’ internal stakeholders or investors.
Across the curriculum, you will progress through each stage of AI product design while building a working grasp of machine learning and deep learning fundamentals. Through live sessions and case studies with MIT faculty member Dr. Brian Subirana, the program will also address the emerging agentic AI landscape, including frameworks such as the Model Context Protocol (MCP).
What Can You Expect to Learn in the Designing and Building AI Products, Services, and Agentic Solutions Program?
Key Takeaways
By the end of the program, you will be able to:
Evaluate the stages of the AI design process model
Categorize different AI and machine learning algorithms (e.g., convolutional, deep, and different types of transformers)
Design, build, and use Agentic AI systems that orchestrate business activities
Apply the tools and techniques of generative and Agentic AI at the employee and organizational levels
Develop specifications for AI solutions using RAG, chain-of-thought reasoning, tools, and Agentic AI capabilities
Explain how humans and computers interact in AI systems
Describe how different types of superminds address various problems
Predict AI opportunities in digital business processes
Build a business case for initiating an AI application, including deciding what to build in-house versus outsourcing
What Does This MIT xPRO Program Curriculum Include?
The MIT xPRO Designing and Building AI Products, Services, and Agentic Solutions program curriculum unfolds across 10 weeks, beginning with the fundamentals of AI design and advancing through machine learning, deep learning, generative AI, and human–computer interaction before arriving at applied AI product design. Real-world case studies and mini-lessons are built into every module, pairing core concepts with technical and product design skills.
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Module 1: The AI Design Process: Designing Products and Solutions across AI and Agentic Technologies
Learn how prompting influences transformer-based and agentic AI systems
Differentiate the roles of orchestration, transformer-based large language models (LLMs), traditional machine learning, and agentic AI in AI systems
Define an AI opportunity by identifying a business or user pain point, intended intelligent behavior, and desired business outcomes
Match the stages of the AI design process to the key decisions involved in designing AI products and services
Evaluate key risks and implementation considerations associated with AI systems, including bias, guardrails, hallucinations, and maintenance considerations
Develop an AI design foundation using the four-stage AI design process for a proposed AI solution
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Module 2: From Models to Applications Part 1: Machine Learning Methods
Differentiate between machine learning methods
Run machine learning algorithms in Python
Implement deep learning techniques in Python
Assess whether a linear classifier is suitable for a business decision
Select appropriate machine learning and deep learning methods for different problem types
Assess the machine learning method fit for an industry pain point
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Module 3: From Models to Applications Part 2: Generative AI, Transformers, GANs and RAGs
Run a simple generative adversarial network (GAN) in Python
Analyze a simple GAN in Python
Extract token embeddings for natural language processing tasks
Differentiate between the core components of generative AI systems
Compare generative AI capabilities and limitations across business applications
Apply the RAG pipeline design process to a real-world use case
Demonstrate how AI can solve healthcare problems
Evaluate how transformer architectures create value across organizational use cases
Recommend an appropriate generative AI approach to address an organizational pain point based on capabilities, limitations, and contextual requirements
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Module 4: From Models to Applications Part 3: Agentic AI, MCP and Multimodal AI
Apply a transformer limitation framework to a domain-specific organizational task
Design a multimodal AI architecture
Build an MCP server specification for a domain-specific organizational task
Design an always-on agentic AI system using scheduling, channels, and skills
Apply a capability framework and transformer extensions, including chain of thought, tools, MCP, and agentic AI, to a domain-specific organizational pain point
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Module 5: Designing Physical AI and Human–Computer Interfaces
Explore assumptions about what AI can and cannot do across on-screen and physical examples
Identify AI systems’ failures when producing physically functional products
Define possible solutions that close the gap between visual plausibility and real-world functionality of physical AI
Predict changes initiated by physical AI systems that act in the real world
Evaluate safety, trust, responsibility, and human oversight needs for AI systems that act autonomously in the physical world
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Module 6: AI-Enabled Apps and Media Applications
Explain why and how embedded AI changes the way products, services, and business interactions must be designed
Locate examples, resources, or practices that show how AI is being embedded inside or near an industry
Analyze how AI-powered visualization can reveal a whole information landscape, break silos, and surface opportunities or trends
Synthesize seemingly unrelated AI examples into transferable patterns that can reframe a professional, personal, or industry pain point
Evaluate how embedded AI approaches address pain points in personal and professional endeavors as well as across industries
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Module 7: Human-Machine Collaboration and Superminds
Discuss how people and computers can work together
Analyze how group intelligence can include computers
Compare the five types of superminds
Discuss the five basic types of cognitive processes and how superminds can be used to enhance them
Assess the value of computers in prediction markets
Appraise the value of computer integration in community superminds
Evaluate various superminds to address a business function
Evaluate the collective intelligence of a group
Justify the use of superminds to address a business problem
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Module 8: Deploying, Scaling, and Operating AI Systems
Analyze AI use cases using business outcomes, data requirements, and workforce considerations
Map the major steps and KPIs for a selected process
Classify process steps by AI deployment fit using data, technology, and workforce
Prioritize AI opportunities using business value and execution risk
Classify AI deployment opportunities by workforce impact
Assess implementation readiness for a prioritized AI opportunity
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Module 9: AI Business Cases and Value Realization
Develop a business case for an AI implementation
Apply the double diamond framework to design a measurable AI pilot
Develop a measurable AI Implementation Plan for a selected organizational pain point
Diagnose implementation challenges using AI case studies and readiness criteria
Analyze the disruptive potential of generative or agentic AI using Christensen’s theory of disruption
Who Is This MIT xPRO Program For?
The Designing and Building AI Products, Services, and Agentic Solutions program is developed for technical product leaders, technology professionals and consultants, and entrepreneurs looking to explore AI technology fundamentals and tools in depth, along with the design processes for AI-powered products.
Technical product managers and leaders spearheading machine learning- and AI-based products in their organizations | Create measurable value for the organization by applying the latest AI technologies in practice |
Technology professionals who build technology solutions for their organizations | Learn to design and build AI-powered solutions using machine learning algorithms |
Technology consultants | Build the capabilities needed for the analysis, design, and development of technology solutions for customers |
AI startup founders working on AI-driven applications | Obtain a proven framework for building sustainable solutions with AI, along with a global network of peers |
UI/UX leaders and designers | Gain the skills needed to shape and manage user experience within AI-based applications |
Technology and AI enthusiasts, including aspiring AI product makers, technology professionals, and curious learners | Keep up-to-date on the advances made in generative AI (including RAG, chain of thought, and tool integration), AI-first product design, and human-centered AI systems |
Note: Participants are required to possess working knowledge of calculus, linear algebra, statistics, and probability. Basic Python experience will also be beneficial.
What Do You Gain from This MIT xPRO Program?
Program Highlights
AI Foundations
Follow an end-to-end learning journey spanning AI, machine learning, deep learning, generative AI, RAG, MCP, and agentic systems through deployment strategy and value realization
Capstone Project
Progressively apply each module to an industry or organizational pain point, and develop a workplace-ready AI Implementation Plan
Emerging Technologies
Explore emerging areas such as physical AI, embedded AI, intelligent human-computer interaction, personal agents, and human-machine superminds
Flexible Learning
Use multiple learning pathways, including Excel, web-based environments, and Python, to explore AI concepts and applications
MIT Faculty Insights
Learn from MIT faculty perspectives, research examples, and Media Lab demonstrations, connecting foundational concepts with emerging applications
Applied Learning
Evaluate AI limitations, design RAG requirements, develop MCP specifications, map agentic workflows, prioritize AI opportunities, and build an evidence-based business case through hands-on activities
Business Readiness
Apply a business-outcome-first approach addressing key performance indicators (KPIs), data readiness, workforce impact, human oversight, implementation risk, build-versus-buy decisions, and scale-or-stop criteria
Attend Live Sessions on AI Product Design
Session 1: The Agentic AI Landscape — Present and Future
Look at how the agentic AI landscape is shifting and how leading organizations are positioning themselves for lasting advantage on the road toward artificial general intelligence. The session covers recent industry developments, likely priorities for the coming 12 months, and longer-term scenarios worth watching. You will also work with a practical scorecard for evaluating closed- and open-source AI options and learn when a blended approach makes the most sense.
Session 2: Emerging Standards for Agentic AI — Model Context Protocol and Beyond
Discover why standards are becoming essential as agentic AI applications scale. You will build a detailed understanding of the MCP and look at other emerging standards that enable trustworthy, interoperable, and autonomous agent behavior.
Session 3: Case Study — Building an Agentic Platform from the Ground Up
Work through a real-world agentic customer service case study, covering the business drivers, system architecture, and tools needed to build and deploy an AI agent. The session also walks you through representative design patterns and implementation elements and then broadens out to additional use cases that illustrate the wider potential of agentic platforms.
Note: Live session content is subject to change. The above topics are addressed through faculty-led sessions and complement the core module instruction.
MIT xPRO Program Faculty
Brian Subirana
Former Director, MIT Auto-ID lab
Brian Subirana has taught at MIT Sloan School of Management and the MIT School of Engineering and also serves on the faculty at Harvard University. His research focuses on Int...
Andrew Lippman
Senior Research Scientist, MIT; Associate Director, MIT Media Lab
Andrew Lippman heads the Viral Communications research group at MIT Media Lab. His work spans digital video and entertainment, graphical interfaces, networking, and blockchain...
Stefanie Mueller
X-Career Development Assistant Professor, MIT Electrical Engineering and Computer Science, joint with Mechanical Engineering
Stefanie Mueller heads the Human–Computer Interaction Community of Research (HCI CoR) at MIT CSAIL. Her research develops novel hardware and software systems that advance pers...
Duane Boning
Clarence J. Lebel Professor, Electrical Engineering and Computer Science
Duane Boning is affiliated with the MIT Microsystems Technology Laboratories, where he serves as associate director for computation and computer-aided design, and is an engine...
Bruce Lawler
Managing Director, MIT Machine Intelligence for Manufacturing and Operations (MIMO)
Bruce Lawler is a technology entrepreneur and executive leader who has developed applications across platforms, including mobile, SaaS, AI, and video distribution networks. He...
Thomas W. Malone
Patrick J. McGovern Professor of Management, MIT Sloan Founding Director, MIT Center for Collective Intelligence
Thomas W. Malone is professor of information technology and professor of work and organizational studies at MIT. Over the course of his research, Malone has correctly anticipa...
Meet the Guest Speaker
Gauri Agarwal
Chief Technology Officer and Co-Founder, Koyal AI
Gauri Agarwal is the chief technology officer and co-founder of Koyal AI, a gen AI startup that turns scripts, audio, and dialogue into cinematic films. At Koyal, she helps le...
Program Credential: Certificate of Completion from MIT xPRO
Upon successfully completing the Designing and Building AI Products, Services, and Agentic Solutions program, you will earn a verified MIT xPRO certificate along with six CEUs. CEUs are a standardized measure of structured professional learning, widely recognized across industries for continuing education and career development purposes.
This program is graded as a pass or fail; you must obtain 70% to pass and receive the certificate of completion.
Note: After successful completion of program, your verified digital certificate will be emailed, at no additional cost, in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of MIT.
Receive an executive certificate with this learning journey
AI Strategy and Product Innovation
Lead AI Innovation from Strategy Implementation to Product Development
Experience a comprehensive learning journey with MIT xPRO, combining two popular executive programs to enhance your expertise in the new world of AI. This integrated approach blends cutting-edge AI insights with strategic leadership frameworks, equipping professionals to develop AI-driven products, implement AI solutions at scale, and lead transformation within their organizations.
Registration for this program is done through Emeritus. You can contact us at learner.success@emeritus.org
Financing Options
Climb Credit*
We offer financing options with our partner, Climb Credit*. Click here to learn more.
Flexible Payment Options For All
Flexible payment options allow you to pay the program fee in installments. Click here to see payment schedule.
Frequently Asked Questions
1
The Program
What is the Designing and Building AI Products, Services, and Agentic Solutions program?
The Designing and Building AI Products, Services, and Agentic Solutions program is a 10-week online MIT xPRO program designed to help professionals move from AI possibilities to purposeful action. It combines artificial intelligence, machine learning, generative AI, RAG, MCP, agentic AI, physical AI, embedded AI, and human–machine collaboration.
You will:
Evaluate AI systems and opportunities based on business and user needs
Design intelligent products, services, and workflows
Develop a workplace-ready AI Implementation Plan
Is this an agentic AI course or a broader AI program?
The AI product road map program takes an end-to-end approach to AI product management and business solution design, exploring agentic AI among several emerging capabilities. You will understand AI ethics for products and examine how different AI approaches can be matched to business challenges and used to design intelligent solutions.
The curriculum covers:
Agentic AI systems, orchestration, tools, and MCP
AI workflows and always-on agentic systems
Human oversight, guardrails, and implementation considerations
What will I learn about AI agents?
You will explore how AI agents can be designed and incorporated into intelligent workflows and business solutions. The curriculum of this building AI agents program focuses on understanding agent capabilities, orchestration, tools, and the role of human judgment.
You will:
Design agentic workflows using scheduling, channels, and skills
Explore tool use, MCP, and orchestration
Consider human intervention, guardrails, maintenance, and oversight
Does the program cover RAG system design and retrieval augmented generation?
RAG is a key part of the curriculum, with learners applying retrieval-augmented generation to real-world use cases of gen AI. The RAG system design program focuses on understanding when RAG is appropriate and how it can extend the capabilities of transformer-based AI.
Through this retrieval-augmented generation program, you will:
Apply a RAG pipeline to a real-world use case
Explore RAG system design in a business context
Evaluate the capabilities and limitations of different approaches
Does the program cover Model Context Protocol and AI orchestration?
Model Context Protocol is explored as part of the program's treatment of AI tools, orchestration, and agentic AI systems. Through this AI product strategy training, you will develop the AI product road map, examine how AI can connect with external capabilities, and design an MCP server specification.
You will work with:
Multi-agent orchestration concepts and AI orchestration
Integrating external tools through MCP
Designing agentic workflows around specific business needs
Is the MIT xPRO Designing and Building AI Products, Services, and Agentic Solutions program worth it?
The MIT xPRO Designing and Building AI Products, Services, and Agentic Solutions program equips professionals with practical frameworks and capabilities to evaluate AI opportunities, design intelligent products and solutions, assess implementation readiness, and connect AI to meaningful business value. The program is best suited for professionals seeking structured, MIT xPRO-backed development to move from AI possibilities to purposeful action and apply AI effectively within their organizations.
2
The Learning Experience
What practical skills will I develop?
The program develops practical skills across AI evaluation, solution design, technical exploration, and implementation planning. Hands-on activities help connect technical concepts with real business and organizational challenges.
You will develop skills in:
Prompt engineering and AI orchestration
RAG system design and MCP specification
Building AI agents and designing AI workflows
AI agent development training
Business case development and implementation planning
Does the program include hands-on projects?
Hands-on learning is integrated throughout the program, giving you opportunities to apply AI concepts rather than only study them. Activities span technical experimentation, AI solution design, and business applications.
Examples include:
Python-based machine learning and deep learning exercises
Advanced prompting techniques, tokenization, embeddings, and GANs
Designing RAG systems, MCP specifications, and agentic systems
Will I work with real-world applications of AI?
The curriculum connects AI technologies to real-world applications across different industries and organizational contexts. You will examine how AI capabilities can address specific pain points and create value.
Applications include:
Healthcare AI and manufacturing use cases
Physical AI and embedded AI
AI solutions applied to an industry or organizational pain point
Does the program teach responsible AI and human-centered AI?
Responsible and human-centered considerations are integrated into the design and implementation of AI solutions. You will consider the technical, human, and organizational implications of deploying intelligent systems.
You will explore:
Responsible AI design practices, including bias, hallucinations, and guardrails
Human-centered AI, trust, safety, and human oversight
Workforce impact and human–machine collaboration
Please note that this program does not grant any AI product manager certification.
What is the capstone experience, and will I complete a real-world project as part of this MIT AI course?
The progressive capstone centers on an industry or organizational pain point and culminates in a workplace-ready AI Implementation Plan. You will bring together technical, human, operational, and strategic perspectives to determine what it takes to move an AI opportunity toward implementation.
The capstone will help you:
Assess AI capability fit, including gen AI and agentic AI
Evaluate deployment options, costs, workforce readiness, and business value
Develop a measurable implementation plan with stakeholder actions and clear scale-or-stop criteria
Does the AI in design course teach prompt engineering and chain-of-thought prompting?
The program explores how prompting influences transformer-based and agentic AI systems, with applications relevant to product leaders and professionals working with AI solutions.
You will:
Build skills in prompt engineering for product manager decision making
Explore chain-of-thought prompting and AI system behavior
Apply prompting concepts to AI workflows and solution design
3
Certification
What are the requirements to earn the certificate?
Each program includes an estimated learner effort per week, so you can gauge what will be required before you enroll. This is referenced at the top of the program landing page under the Duration section, as well as in the program brochure, which you can obtain by submitting the short form at the top of this web page. All programs are designed to fit into your working life.
This program is scored as a pass or no-pass; participants must complete the required activities to pass and obtain the certificate of completion. Some programs include a final project submission or other assignments to obtain passing status. This information will be noted in the program brochure. Please email us if you need further clarification on any specific program requirements.
What type of certificate will I receive?
Upon successful completion of the program, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, resume, and/or display it on your LinkedIn profile.The digital certificate will be sent approximately two weeks after the program, once grading is complete.
Can I get the hard copy of the certificate?
No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.
Do I receive alumni status after completing this program?
No, there is no alumni status granted for this program. In some cases, there are credits that count toward a higher level of certification. This information will be clearly noted in the program brochure.
How long will I have access to the learning materials?
You will have access to the online learning platform and all the videos and program materials for 24 months following the program start date. Access to the learning platform is restricted to registered participants per the terms of agreement.
Does this MIT xPRO artificial intelligence program provide an AI certification?
The Designing and Building AI Products, Services, and Agentic Solutions program is a certificate program, and it does not provide any AI certifications. However, earning a certificate from MIT xPRO in AI product and solution design demonstrates both strategic insight and technical proficiency. It will help display your ability to lead AI product initiatives and apply advanced AI concepts to solve business challenges.
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Technical Requirements
What equipment or technical requirements are there for this program?
Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts.
Do I need to be online to access the program content?
Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access program content from a desktop, laptop, tablet, or mobile device.
Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you may view them later.
5
Payment Process
Can I still register if the registration deadline has passed?
Yes, you can register up until seven days past the published start date of the program without missing any of the core program material or learnings.
What is the program fee, and what forms of payment do you accept?
The program fee is noted at the top of this program web page and usually referenced in the program brochure as well.
Flexible payment options are available (see details below as well as at the top of this program web page next to FEE).
Tuition assistance is available for participants who qualify. Please email learner.success@emeritus.org.
What if I don’t have a credit card? Is there another method of payment accepted?
Yes, you can do the bank remittance in the program currency via wire transfer or debit card. Please contact your program advisor, or email us for details.
I was not able to use the discount code provided. Can you help?
Yes! Please email us with the details of the program you are interested in, and we will assist you.
How can I obtain an invoice for payment?
Please email us your invoicing requirements and the specific program you’re interested in enrolling in.
Is there an option to make flexible payments for this program?
Yes, the flexible payment option allows a participant to pay the program fee in installments. This option is made available on the payment page and should be selected before submitting the payment.
How can I obtain a W9 form?
Please connect with us via email for assistance.
Who will be collecting the payment for the program?
Emeritus collects all program payments, provides learner enrollment and program support, and manages learning platform services.
Are there any restrictions on the types of funding that can be used to pay for the program?
Program fees for Emeritus programs with MIT xPRO may not be paid for with (a) funds from the GI Bill, the Post-9/11 Educational Assistance Act of 2008, or similar types of military education funding benefits or (b) Title IV financial aid funds.
6
Refund Policy
What is the program refund and deferral policy?
For the program refund and deferral policy, please click the link here.
7
Accessibility
How does Emeritus support accessibility for learners?
Emeritus is committed to making high-quality education accessible and affordable to individuals, companies, and governments around the world. If you have questions about accessibility or would like to discuss available support options before enrolling, please contact accessibility@emeritus.org. For more information about our accessibility practices, please review our Accessibility Policy here.
Didn't find what you were looking for? Write to us at learner.success@emeritus.org or Schedule a call with one of our Academic Advisors or call us at +1 401 443 9591 (US) / + 44 189 236 2347 (UK) / +65 3129 7174 (SG)