MON · Skills diagnostics & practice · Singapore
Every skill you have is being re-priced. MON measures which parts of your work AI now does outright, which parts you'll be paid to supervise, and which parts compound — then keeps building the third kind, for as long as the ground keeps moving.
Half-life is how long before half of today's task list moves left. Illustrative model — your audit uses your own task log.
First half — your skills decay
Skills don't disappear on a schedule — they get hollowed out from the inside. The routine middle of a craft goes first, quietly, while the title stays the same. What's left is thinner and harder: framing the problem, judging output you didn't produce, carrying responsibility for a decision a model can't be accountable for.
We say this plainly because most providers won't. A half-life of 2.4 years is not a marketing number — it's the reason a certificate earned this year is worth less next year, and worth arguing about now.
Macro How it works
MON is the macro model — the three stages every kind of work moves through as AI capability grows. It doesn't change person to person; it's the ground everyone is standing on. MONSa is what happens when MON reads that model against you.
One orchestration layer, connected to task logs and practice tracks at once. It scores any kind of work against current model capability — replaced, supervised, compounds — the same three stages whether it's reading one person's week or a whole team's.
Every task, in any role, sorts into one of three stages — the general model of where AI capability actually stands.
That same model, read against your specific week, resolves to one of four named archetypes — a mirror, not a verdict.
A sequence of practice tracks built to close your specific gap, re-run each quarter as the ground moves.
MON keeps four MCP connections open at once, each one two-way — pulling from skills content, the real-world skills framework and taxonomy, and assessments, while pushing updates back out to learning path creation. Same orchestrator, whichever sources are actually plugged in.
Macro MON's scoring model
This is the macro lens — MON scores any kind of work against it, for one person's task list or a whole team's, before MONSa applies it to you.
Reconciliation, variance tables, first-pass commentary. No pathway needed here.
Checking assumptions, catching the plausible-but-wrong. The pathway makes the check faster, not the trust looser.
Deciding what to measure, owning the call. This is the column your pathway is built to grow.
Micro MONSa Skills Auditor
MONSa takes MON's macro model — replaced, supervised, compounds — and reads it against your actual week specifically. A short, memorable archetype that names your current mix, plus the pathway that follows from it.
Heavily exposed — the routine core is most of your week, and a current model can already run it unassisted.
In the supervision layer — checking, correcting and signing off work you didn't produce.
Mixed, with real edges — a routine core sitting alongside compounding work that's yours.
Mostly compounding already — accountability, undocumented context and persuasion make up the week.
The library behind the pathway
MON doesn't invent a curriculum — it routes to specific courses in this repository.
100 popular Generative AI courses, summarised and mapped to the skills they build. Browse by domain, search by skill, or follow a curated pathway.
Pathways
Sampling strategy, error signatures, when to stop trusting fluency.
Turning a vague ask into constraints and a definition of done that survives delegation.
Assembling agents and scripts around your workflow — and knowing when not to.
Baselines, sample size, and honest reporting for people who aren't researchers.
Accountability, disclosure, and the failure modes that end up somewhere formal.
Making the case for a change in how work gets done, to people judged on the result.
For organisations
MON reads across everyone's connected sources at once — which gaps repeat across the team, and where one person is the entire safety net.
Micro MON's skill archetype
Eight questions about how your week actually goes. Nothing is stored; it's free and takes about four minutes.
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Nothing here is stored or sent anywhere — MONSa is computed in your browser and disappears when you close the tab.
Match your assessed skills against 2,001 SkillsFuture reference roles to see exact competency gaps.
Compare with Target Role →Micro Grounded in real Singapore job data
2,001 real-world job roles, each scored from its own required competencies — not a self-report. Same three-stage model, real-world skills data underneath.