Make US AI-Ready – Choose Your Track

MAKE US AI-READY
Enhanced • Prosper Systems • Kenton Johnson • 2026

Built on the U.S. Department of Labor AI Literacy initiative –
redesigned and enhanced from the ground up for three distinct experience levels.

About This Course • Find Your Track • All Three Tracks • Why This Matters

ABOUT THIS COURSE

The original Department of Labor Make America AI-Ready course was built fast – and it showed. One pace, one tone, one path for everyone from a retiree trying Google for the first time to a production engineer running automated pipelines. This redesign fixes that.

What is different here:

Three separate tracks – matched to where you actually are with AI today
Entry Day shared across all tracks – common ground, then branching paths
7 days × 10 minutes – same commitment, radically different depth
Real tasks, real stakes, real verification – not toy examples
A tiered ROI standard embedded in Track 3: 10:1 minimum, 20:1 for daily workflows, 50:1+ for full deployments – if AI is not saving you serious time, you are not using it right

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FIND YOUR TRACK – THREE QUICK QUESTIONS

Answer honestly. No score is better than another. The goal is to put you in the right room.

Question 1 – How often do you use AI tools today?

Never, or I tried once and stopped A few times a month, no real system Daily – it is part of how I work

Question 2 – What best describes your relationship to AI right now?

Curious but unsure where to start I see the potential but I am inconsistent I build with it or manage others who do

Question 3 – What do you want out of seven days?

One real task I can do with AI before next week A structured method I will actually use at work A deployment-ready framework and ROI standard

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ALL THREE TRACKS

Not sure about the quiz? Browse all three tracks and choose directly.

TRACK 1 – THE NEWCOMER

"AI Exists – And Here Is Why It Matters to You"

For: Never used AI, or barely touched it. Skeptical, intimidated, or just waiting for a reason.
By Day 7: Complete at least one real task with a free AI tool – and judge whether the result is any good.
Tone: Warm, patient, no jargon. Single tool. Real-life examples. Hallucination awareness.

Day 1: What AI is (and is not)
Day 2: Your first real prompt
Day 3: Reading AI output critically
Day 4: Everyday tasks – writing, planning, questions
Day 5: When AI gets it wrong – hallucinations and limits
Day 6: Responsible use and privacy basics
Day 7: Your first 10-minute AI habit

Open Track 1 →

TRACK 2 – THE PRACTITIONER

"From Occasional Use to Reliable Results"

For: Uses AI inconsistently. Sees potential but lacks a repeatable system.
By Day 7: A working prompt framework, a verified output standard, and a personal prompt library.
Tone: Professional, structured, work-deliverable accountability.

Day 1: Entry + where inconsistency comes from
Day 2: The six-part prompt framework
Day 3: Tool matching – right AI for the right job
Day 4: The self-improvement loop – critique and iterate
Day 5: Professional-grade verification
Day 6: Building your prompt library
Day 7: The accountability standard – results you can sign your name to

Open Track 2 →

TRACK 3 – THE OPERATOR

"From Daily Use to Production-Grade Deployment"

For: Daily AI user. Builds with it, manages teams using it, or runs automated workflows.
By Day 7: A governance-ready deployment framework and a tiered ROI measurement standard: 10:1 minimum, 20:1 daily, 50:1+ full deployment.
Tone: Technical, architectural, enterprise-accountability level.

Day 1: Entry + the operator mindset gap
Day 2: Transformer, GAN, and VAE architecture – what actually runs under the hood
Day 3: Prompt system design – chaining, templates, system prompts
Day 4: Agent workflows – n8n, Agents SDK, multi-step automation
Day 5: The three-gate verification pipeline
Day 6: AI governance policy – risk, compliance, accountability
Day 7: 90-day deployment roadmap – the tiered ROI standard (10:1 / 20:1 / 50:1+)

Open Track 3 →

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WHY THIS MATTERS

The original course – what worked and what did not

The U.S. Department of Labor launched Make America AI-Ready as a 7-day SMS-based course to give working Americans a baseline understanding of artificial intelligence. The initiative was timely and the intent was sound.

What it lacked: differentiation. A first-year warehouse worker and a senior software engineer received identical content at identical depth. The course taught AI verification – yet shipped with a broken exercise and a live tool that failed on a simple ZIP code query during the verification lesson itself. That is the best meta-lesson of the week: even well-intentioned AI training can fail its own standard.

This redesign keeps what worked – the 7-day structure, the daily commitment, the real-task orientation – and replaces what did not.
The ROI standard – what it means and where it comes from
The ROI standard embedded in Track 3 is not theoretical. It comes from a real client engagement: an 8-page list of finance options expanded to 80 pages of documented, formatted content in 30 minutes. The same task, done manually, would have taken a week of hard work. That is 80:1.

But 80:1 is not the floor – it is one data point. The tiered standard:
- 10:1 minimum. The baseline. 80 pages from 8 pages. If you cannot hit 10:1 on a task, AI is not the right tool for that task.
- 20:1 – daily workflow target. A repeatable prompt system, used every day, running at 20 units of output per unit of effort. GitHub Copilot-class productivity. This is where practitioners live.
- 50:1 – full deployment. A production system like this course website – built in one session, deployed live, serving ongoing users. When the system does the work, the ratio scales.
- 80:1 and above – exceptional. The real example above. Not every project gets there, but when architecture, prompting, and workflow all align, it happens.
When you spec a new deployment, ask: what is the realistic ROI multiple? If it is under 3:1, deprioritize. If it is over 10:1, build it now.
About this redesign – Prosper Systems, Kenton Johnson

This course was redesigned by Kenton Johnson of Prosper Systems, Denver CO, after completing the full original DOL course in March 2026. Kenton entered Day 1 at 10/10 AI confidence and finished Day 7 at 7/10 – the correct Dunning-Kruger arc. Genuine learning lowers stated confidence because it replaces assumption with knowledge of what you do not yet know.

The redesign was built in a single session using AI-assisted authoring. Combined length of all three tracks: approximately 126 printed pages when expanded. Total build time: one working session. This website itself is a 50:1+ deployment. That is the standard demonstrated.

This course is offered as a public resource. It is not affiliated with or endorsed by the U.S. Department of Labor.

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PROSPER SYSTEMS (.biz) • Kenton H Johnson (.com), Founder
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