Write your awesome label here.
Green AI

Design agentic systems that finish the task on fewer steps, fewer tokens and less energy.

One completed task as the unit, eleven design levers, grounded in SCI for AI. From whether the agent is needed at all, through decomposition, tool surface, context, retrieval, termination, routing, failure and placement, to proving the change — plus an optional lab where you watch the number move, and a capstone on one of your own features.
10-12h
of learning
13
modules
30 questions
final assessment
80%
to pass
Certification
upon completion

Designing Green Agentic Systems

What
How
Tools
Who

How the course works

Framework-neutral

The levers apply whatever you build on. One worked implementation illustrates them; nothing depends on a particular agent framework.

One system throughout

The Northbridge support-triage agent, at 4,200 tickets a day, carries every worked example, every worked answer and the lab.

An optional lab where the numbers are live

Ten exercises against a running agent; the nine with worked fixes take the baseline from 2.925 to 0.362 gCO₂e per completed task. Every figure printed in the module is an output of the code that ships.

What this course helps with

The loop you did not need to build

Much of what an agent spends is a deterministic process wearing a loop — steps that were known in advance, rediscovered on every request. Module 2 asks for the number instead of the opinion.

Consumption that accumulates per step

Context that grows every turn, tool definitions re-read, retrieval that returns more than it needs, retries that repeat a step with its whole accumulated context. Energy, and cost, rise together.

A figure you can show

Energy and carbon per completed task, with the boundary, method and date recorded — so the reduction can be checked rather than asserted.

Who this is for

  • Architects designing agentic systems and developers building them

  • Teams putting an agent into production and answering for its cost and footprint

  • Platform engineers setting defaults for agents across several teams

  • Assumes working familiarity with LLM applications; no measurement background required

Related courses:

For how to obtain the numbers this course asks you to move, see SCI for AI Practitioner: The Measurement Lab. For fleet-level operations and placement policy, see GreenOps Practitioner. For the water dimension of a placement change, see Software Water Essentials.

What you will work with

The agent decision test

Sample real runs, count distinct sequences, cost the deterministic version, and write the benefit sentence for whatever remains.

The accumulation curve

How context, tools and retrieval compound across a run, and where compaction, projection and scoping cut in.

The lab harness

Prefill and decode reported separately, along with steps, tool calls, retrieved chunks, retries and cost per completed task. A Software Carbon Intensity (SCI) figure is calculated from stated coefficients.

What you will be able to do

  • Express an agent's footprint per completed task using Software Carbon Intensity for AI (SCI for AI)
  • Cost a fixed-logic alternative before you commit to an agent, and state when an agent earns its cost
  • Choose between single-agent, pipeline and multi-agent designs based on measurement
  • Choose between single-agent, pipeline and multi-agent designs based on measurement
  • Set stopping rules and budgets, and choose the model and reasoning depth for each step
  • Prove a reduction on the same basis as the baseline, with quality held

Course Lessons

The full course

Every module ends with an application exercise and a worked solution.

01

Why Water, and Why You

Software feels dry, but the buildings it runs in use water for cooling, the electricity it consumes was made using water, and the hardware was manufactured with it. This module shows those three connections and closes the gap between the people who can see the water and the people who change the software.
module-01

02

The Four Layers: building, electricity, hardware, and the stress conversion

This module gives the three ways software uses water their proper names, as the draft SWI specification uses them, and adds a fourth layer that converts litres into how much each litre matters. It ends with the only line of arithmetic in the course.
module-02

03

Consumption and Withdrawal: used up vs borrowed

Water figures come in two kinds, and confusing them is the most common mistake in reading them. This module teaches the distinction between water used up and water borrowed and returned, and the rule that the two are never added together.
module-03

04

Reading a Water Number

This module teaches no calculations. It teaches how to look at any water figure, whether a provider report, a news headline or a colleague’s slide, and know what it does and does not say.
module-04

05

Stress-Adjusted Water: a liter is not a liter

The same liter counts for more where water is scarce and for less where it is plentiful. This module turns that idea into arithmetic using a published factor per place, giving the conversion layer its full treatment at foundation depth.
module-05

06

Small Things That Save Water

The earlier modules built a vocabulary; this one turns it into actions small enough to take this week, organised by role. None of them needs a water meter, a budget or permission to run a project.
module-06

07

Final Assessment

A final assessment of 12 questions - 80% to pass, 30 minutes, retake available.
Final Assessment

Assessment & Certification

How you are assessed

  • A five-question knowledge check after every module, drawn at random from that module’s 15-question pool
  • A final assessment of 30 questions, drawn at random from the credential-bearing modules' pool, fresh on every attempt
  • 80% to pass, 60 minutes, retake available
  • Drawn from a pool of 121 final-assessment questions; scenario, numerical and synthesis rather than recall of figures that date

What you earn

GSF Certification
Green Agentic Systems Practitioner
  • Issued on passing the final assessment
  • Valid for 2 years, refreshed by a short update module
  • Shareable credential for your profile, CV and tender responses

Time to complete

Reading and exercises
10–12h across 13 modules
Knowledge checks
About 5 minutes per module
Final assessment
60 minutes
Typical completion
3–4 weeks at a module per session, entirely self-paced
Optional lab
40 minutes guided, plus 1–2 hours working the exercises

Join the Pilot

The GSF Academy is currently in pilot. If your organization would like to enrol learners and issue GSF certifications to your teams, tell us a little about what you need and we'll follow up to discuss access, pricing, and enrolment.

Request Access for Your Organization

*

 Your name

*

 Work Email

*

 Tell us about your organisation

Which courses are most relevant to you?

Select all

Building a Green AI Agent

Designing Green Agentic Systems

Green AI Prompting for Self & Agents

Green AI for Executives

Green AI for ML Practitioners

Green AI for Policy Makers

Green Data Practitioner

Green IT for Leaders

Green Software Developer

Green and Efficient Architect

GreenOps Practitioner

SCI for AI Practitioner: The Measurement Lab

Scaling Green AI and Software

Software Water Essentials