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Architecture

Make architecture decisions across the whole estate, with the carbon, energy, water and waste trade-offs visible.

Eleven modules across six layers: hardware and devices, infrastructure, platforms, data and AI foundations, applications, and governance and observability. The course also covers assessment and measurement, and ends with a capstone Green Architecture Blueprint.
8h 15m
of learning
11
modules
30 question
final assessment
80%
to pass
Certification
on completion

Green and Efficient Architect

What
How
Tools
Who

How the course works

Six layers, one estate

Silicon to screen, with governance and measurement running across all of them, so AI sits in context.

Worked answers in every exercise

Refresh payback, region placement, cluster utilization, lifecycle policy, routing and payload, each with a solution to check against.

A capstone that assembles the modules

The Blueprint is built from the artefacts produced in the earlier exercises.

What this course helps with

Know which layer the impact is on

Region, refresh cycle, utilization, retention, routing and payload sit at different layers, and effort spent on the wrong one returns little.

Name the dimension a decision displaces

New devices reduce in-use energy and add embodied carbon; a cleaner grid may be water-stressed. The course makes the trade explicit.

Produce a blueprint that traces

Every decision linked to a rated hotspot and a measurement row, rather than a list of good practices.

Who this is for

  • Solution, enterprise, cloud and platform architects

  • Senior engineers moving into architecture roles

  • Technical leads responsible for estate-wide decisions

  • Architecture experience assumed; no sustainability background required

Related courses:

Pair with SCI for AI Practitioner if you also need to produce the underlying measurements.

What you will work with

The refresh calculation

Embodied cost of replacement against annual in-use saving, and the conditions that override the result.

The region decision

Carbon, water, latency, data sovereignty and cost weighed together, with the trade stated.

The Blueprint template

Assessment, measurement plan, reduction register and governance wiring, each traceable to an exercise.

What you will be able to do

  • Place any architecture decision on the six-layer model and name the dimension it displaces
  • Baseline an estate, and rank its hotspots with defensible evidence
  • Calculate a Software Carbon Intensity (SCI) score with an explicit boundary and functional unit
  • Work the hardware, infrastructure and platform decisions: refresh, region, utilization and scheduling
  • Work the data, AI and application decisions: storage, model routing, payload and feature retirement
  • Assemble a Green Architecture Blueprint in which every claim traces to its evidence

Course Lessons

The full course

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

01

The Prompt Footprint

Introduces the five-dimensional view: cost, carbon, energy, water, embodied hardware. Establishes SCI for AI as the standards anchor. Positions the regulatory landscape (CSRD, EU AI Act, procurement disclosure) as the why now for Footprint literacy.
Before You Begin
Modules

02

The Specification Lever

How prompt intent quality drives Footprint. The GSF Intent Framework introduced. Trade-offs: over-specification wastes tokens, under-specification wastes retries. Worked examples across capability tiers.
Modules

03

The Structure Lever

Prompt organization: system messages, few-shot examples, output constraints, formatting instructions. Where structure earns its tokens and where it doesn't.
Modules

04

The Reasoning Depth Lever

When to invoke chain-of-thought, tree-of-thought, extended reasoning modes; when not to. The GSF Reasoning Budget: task-class taxonomy for reasoning depth decisions.
Modules

05

The Model Selection Lever

The most consequential single decision in inference efficiency. Capability tiers and routing decisions. The GSF Model Fit Test protocol. Same task across tiers, measured.
Halfway Check-in
Modules

06

The Orchestration Lever

Where agents leak resource: tool selection, chain depth, redundant retrieval, missing caching. Token budgets as a first-class design constraint. Case study from the supply-chain agent paper (70–90% workflow-level savings).
Modules

07

Measuring the Prompt Footprint

Hands-on demonstrations with EcoLogits, CodeCarbon, AI Energy Score. Producing numbers a CSRD auditor can read. The measurement chain from token count to gCO₂eq.
Modules

08

Procurement & Disclosure

What to ask your LLM vendor. What CSRD and the EU AI Act will require. The GSF Procurement question bank organized by Footprint dimension.
Modules

09

Course Completion

50 questions, 120 minutes. Pass Marks: 85%
Final Assessment
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Assessment & Certification

How you are assessed

  • A short knowledge check after every module, drawn at random from that module’s pool
  • A final assessment of 30 scenario-judgement questions from a pool of 171
  • 80% to pass, 60 minutes, retake available
  • Questions test judgement in situations you will meet — not recall of figures that date

What you earn

GSF Certification
Green Software & AI Architect
  • 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
8h 15m across 11 modules
Knowledge checks
About 5 minutes per module
Final assessment
60 minutes
Typical completion
2–3 weeks at a module per session, entirely self-paced

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 what you need, and we'll follow up to discuss access, pricing, and enrolment.

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