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2.5 weeks · Live and AI-guided · All recorded

Lead Agentic AI with MIT CSAIL in this 2.5 week intensive

Agentic AI stalls on the design, not the build. In 2.5 weeks, apply the MIT CSAIL design method to your own biggest problem, test your decisions in a working simulation, and leave with a method you can use again.

You leave with

Agent Design Blueprint Working simulation Readiness review Agentic AI Design Fellow membership

Co-led by

Prof. Daniel Jackson

Prof. Daniel Jackson

MIT CSAIL

Eagon Meng

Eagon Meng

MIT CSAIL

A technology collaboration: the Software Design Group at MIT CSAIL and NGL, a new technology start-up.

View the full outline

Full curriculum, weekly schedule, project examples, outputs, faculty, and time commitment.

Opens immediately after submission.

Starts

Tuesday September 15

Runs

2.5 weeks

Live

Tue & Thu, 12 PM ET

all recorded

Guided work

6–9 hrs a week

with Paski, your AI tutor

Fee

$1,695 $2,095

Save $400 · ends Thursday, September 10

9–12 hrs a week in total · no engineering background required

You bring

One real business problem

You apply

MIT CSAIL Concept Design

You produce

Blueprint + simulation

You become

An Agentic AI Fellow

Agentic AI Fellow membership is the Fellows Forum: weekly builder office hours with Dirk and Ivana, a monthly session with Daniel and Eagon, and the growing concept catalog.

Why this capability is rare

Building agents is getting easier. Knowing how they should work is becoming the advantage.

Agentic AI has made execution faster. It has not made the underlying decisions easier. The differentiator is no longer who can build. It is who can design.

The situation

You’re not behind on AI. You’re accountable for it.

Five things leaders in your seat say out loud. They sound like five different problems.

01

“What I asked for is never what I get.”

02

“I approved a demo I couldn’t interrogate.”

03

“I delegated the work and accidentally delegated the decisions.”

04

“We have pilots everywhere and nothing in the portfolio.”

05

“The AI bill keeps climbing and nobody can tell me why.”

They are one problem. Nobody wrote down what the thing was supposed to do, precisely enough for anyone, or anything, to build it right. This intensive is where you write it down.

View the full outline

Make it concrete

“Build an onboarding agent” is an ambition, not yet a design.

“Use an agent to handle customer onboarding.”

Before anyone builds it, the business has to decide how the service behaves. Five questions, and none of them are the engineer’s to answer.

01

What does it own?

Collect information, verify it, create an account, or only recommend the next action?

02

What can it decide?

Can it waive a requirement, reject a customer or approve an exception?

03

Which rules and boundaries apply?

04

What happens off the happy path?

05

When does a person take over?

The outline works all five through on a real example, and shows you what a complete answer looks like.

How the work goes

Define it. Design it. Test it.

You already bring

Business judgment and ownership

You understand the work, the people and the consequences. But you may not yet have a method for making every important decision visible.

During the intensive

You make the design testable

Use the MIT CSAIL concept design method to model how the agent should behave, then test that behavior in a working simulation.

Purpose Authority State Decisions Rules Exceptions Human handoffs

You leave able to

Decide, test and direct the work

You can interrogate how an agent should behave, explain your decisions, and define what you are prepared to build.

What happens next

Whoever builds it works from an accepted design, not a collection of hidden assumptions. The consequential decisions have already been made visible and tested.

Prof. Daniel Jackson

Organizations have always been able to run on implicit knowledge, because people fill the gaps without being asked. Agents cannot do that. You have to describe the business explicitly, in one language people, machines and agents can share.

Prof. Daniel Jackson

Associate director, MIT CSAIL · created concept design

The design in hand in two and a half weeks

The outline gives you the five units, what you build in each, and the one thing you’ll need to bring.

View the full outline

Proof, not notes

You leave with evidence that you can lead the work.

The artifact is the evidence. You do not leave claiming to understand agentic AI. You leave having designed and tested how one real system should work.

01

Agent Design Blueprint

One document a person can read and an agent can work from, covering your system’s purpose, authority, rules, handoffs and exceptions.

02

Working simulation

Run the design on your own normal, ambiguous and failure cases before committing to a build.

03

Readiness review

A shared reference executives, domain experts and the people who build can interrogate, approve and build from.

Your first design is guided. The method is yours to run again. You leave with the prompts, sources and method to approach the next project yourself, plus the readiness review and the Fellows Forum.

This is not an attendance certificate. There is no certificate. It is the design itself, plus the tested behavior behind it, in a form your organization can act on.

Written once, read by both. The same document your executives approve or the document your agents are built from, so nothing is lost in translation between them.

Become the person who decides what your agents do.

Two and a half weeks, led by Prof. Daniel Jackson, who invented the method, with Eagon Meng and the applied faculty.

View the full outline

Faculty

The method’s inventor, the researcher extending it, and the people who deploy it

Daniel invented concept design; Eagon is evolving it with him. Dirk and Ivana teach the sessions where the design meets a real organization.

Prof. Daniel Jackson

Prof. Daniel Jackson

associate director, MIT CSAIL · author of The Essence of Software

One of the most cited researchers in software design, Daniel created concept design as a rigorous way to describe what systems do, in language every stakeholder can read. His methods are used inside companies from Autodesk to global enterprises aligning teams, products, and now agents.

Eagon Meng

Eagon Meng

PhD candidate, MIT CSAIL Software Design Group

Eagon’s research turns concept designs into running systems: the translation layer between human intent, agent behavior, and executable code. He builds the tooling that makes a concept specification something you can hand to an agent and trust what comes back.

Teaching in the intensive · weekly office hours in the Forum

Dirk Hofmann

Dirk Hofmann

co-founder and CEO, DAIN Studios Germany · Harvard Data Science Review board member

Co-founded DAIN Studios; before that led global data and AI work at Siemens, Nokia and Deutsche Telekom.

Ivana Ovcaric

Ivana Ovcaric

principal data and AI strategist, DAIN Studios

A decade leading AI strategy and implementation across telco, media, banking and manufacturing.

All four stay behind you

Daniel, Eagon, Dirk and Ivana all teach in the intensive. Afterwards, Dirk and Ivana run weekly builder office hours and Daniel and Eagon host a monthly session in the Forum · included in the fee. You keep access to the growing catalog of vetted concepts, and can submit your own.

View the full outline

Who this is for

Your business expertise is what qualifies you.

You do not write code. You decide what the system may do on your behalf.

You bring

  • Domain knowledge and business judgment
  • Accountability for a real outcome
  • Familiarity with decisions and exceptions
  • The ability to explain how the work actually happens

We teach you

  • How to model the behavior precisely
  • How to allocate authority between people and agents
  • How to expose hidden assumptions and failure cases
  • How to test the design before the build starts

Business judgment is the prerequisite. No code, no technical vocabulary, no engineering background.

What this is not

Not prompting. Not requirements writing. System design. No survey of models, no tool tour, nothing that expires with the next release cycle.

Not a seminar or a strategy exercise. Those end at understanding. This ends with artifacts in hand, and the method keeps running inside your organization afterwards.

The September Cohort starts September 15

$1,695 at full tuition, and the Agentic AI Fellows Forum is included.

View the full outline

Questions

Asked often

No. It’s a technology collaboration between the Software Design Group at MIT CSAIL and NGL, a new technology start-up: a transfer of the concept design method into your organization, with the reviewed portfolio as the evidence it worked. Executive education certifies attendance. This produces work.

No, deliberately. A certificate is a claim about a person; this is a review of the work. You leave with your concept catalog, the simulation, the kit, and a letter from MIT CSAIL stating that the work meets the standards of their method and that it is yours.

One pain point or one opportunity you care about. It can sit inside a product, a team or a whole function, and it does not need to be decided yet · bring two or three possibilities and the first live session helps you choose. Everything is applied to the one you pick, so there are no toy examples.

Strategy work ends at understanding: you leave knowing why agentic AI design is hard, with a list of mitigations. This ends with artifacts in hand: a concept catalog your organization can align on, materials whoever builds it, or your agents, can work from as written, and a simulation that runs. If you already know the “why,” this is the “what, exactly.”

Something gets built, and you are not the one typing it. You define the concepts; Paski, your AI tutor, generates the translations and a working simulation from them, and your job is to check what comes back against what you meant. If you want to write the code yourself, this is not it.

See what you’d actually be doing

The outline gives you the five units, what you build in each, who leads them, and the one thing you’ll need to bring.

View the full outline

September Cohort starts September 15 · $1,695 · no engineering background required

Starts September 15

$1,695 · 2.5 weeks

View outline