There Was No Contract — But There Was a Signal. And the Signal Has Changed.

Jun 22
10 min read

Why the rules of the job market feel broken — and what both employers and employees are missing about what actually changed.

A post recently circulating on LinkedIn captured something that many graduates feel but rarely articulate so clearly:

"Study hard. You will get a higher salary when you grow up." "Be realistic. Lower your salary expectations." "Just because you have a degree doesn't mean anything."

The same system that told young people what to aim for is now telling them the target has moved. And the frustration is real. Years of sacrifice — foregone childhood, mounting tuition fees, relentless academic pressure — were all justified by a promise of a better future. Now, at the moment of collection, the promise appears to have expired.

But here is the harder truth: there was no promise. There was a signal. And signals are not contracts.

That distinction matters more than it might first appear — because the people who understand it are far better positioned to navigate what comes next than those who are still arguing about whether the contract was honoured.

What a signal is — and why we confused it for a guarantee

To understand why so many people feel betrayed by the job market, it helps to understand how the job market actually works — not how we were told it works, but how it has always worked beneath the surface.

Employers face a persistent challenge: how do you assess a stranger's ability to do a job they have never done for you? You look for proxies. Signals that correlate — even imperfectly — with what you actually need.

A university degree became one of the most powerful proxies the job market ever produced. Not because a degree directly taught people the skills required for work. It rarely did. But because, for much of the past half-century, degree holders were a minority. In Singapore, around the year 2000, roughly 26% of those aged 25 to 29 held a degree. That scarcity meant the process of getting in, staying in, and graduating was itself a meaningful filter — one that selected, imperfectly but usefully, for discipline, baseline intelligence, and the capacity to operate in a structured environment.

Employers outsourced their initial screening to universities. And it worked well enough that the correlation became, in many minds, a causation. Then, gradually, a guarantee.

Employees saw the same correlation and acted on it rationally. If a degree improves your chances of a better job, invest in a degree. If a better university improves those chances further, aim for a better university. If grades matter to employers, optimise for grades. An entire generation — and then another — built their plans around a signal they had every reason to trust.

The signal was real. The mistake was treating it as permanent.

Why the signal weakened — before AI even arrived

The conditions that made the degree a reliable signal began shifting well before generative AI entered the conversation.

By 2024, roughly 58% of Singaporeans aged 25 to 29 hold a degree. When the majority of candidates hold a credential, it can no longer function as a differentiator. It becomes, at best, a baseline qualifier — a threshold that gets you considered, but guarantees nothing beyond that.

At the same time, a persistent gap had been widening between what graduates knew and what organisations needed them to do from day one. Employers across Singapore and the broader region have consistently raised work-readiness as a concern — with fresh hires frequently requiring significant onboarding and on-the-job training before they could contribute meaningfully. This perception is not unique to degree holders; diploma graduates have faced similar feedback. But the economics of the degree pipeline made it a more visible tension.

The assumption embedded in the old hiring model was that organisations would absorb the cost of training fresh graduates — and for a long time, that bargain held. But as graduate salaries rose with each successive cohort, and as job tenures shortened, the cost of that learning period — measured in supervision time, slower output, and training investment — became harder for organisations to absorb quietly. The value proposition of hiring a fresh graduate had always included a hidden onboarding cost. For a long time, that cost was accepted. It is less automatically accepted today.

The degree had not become worthless. But it had become considerably less informative than it once was. And the job market — which runs on information — adjusted accordingly.

Other signals weakened too, for similar reasons.

Salary history was long used as a proxy for market-validated worth. But salary reflects negotiating power, organisational budget cycles, and timing as much as it reflects actual value delivered. Anchoring a hiring decision to someone's previous salary often perpetuates yesterday's pricing rather than assessing today's fit.

Seniority and tenure were proxies for accumulated wisdom and demonstrated reliability. But years of experience performing structured, repeatable tasks is not the same as deep expertise in judgement and problem-solving. The two were often bundled together and assumed to be equivalent. They are not.

Title was a proxy for organisational trust and capability. But titles vary so widely across organisations — and are awarded so inconsistently — that they have become increasingly poor predictors of what someone can actually do.

None of these signals became useless. But each became less reliable. And the job market was already adjusting to that before AI arrived to accelerate the process.

What AI changed — and what it did not

Generative AI did not break the job market. It exposed what was already straining beneath the surface — and it did so faster than most people or institutions were prepared for.

The tasks most affected by AI are not, as many assumed, the low-skill or purely manual ones. The tasks most vulnerable to automation are those that are structured, repeatable, and clearly defined. A significant portion of early-career work falls into exactly that category: research synthesis, first-draft writing, data summarisation, routine analysis, process documentation, and structured reporting.

These are the tasks that fresh graduates have historically performed during their first few years of employment, while building the experience and judgement needed for more complex work. Organisations accepted the cost of that learning period because the graduate's eventual contribution justified it, and because there was no cheaper alternative.

There is now a cheaper alternative — and it does not need onboarding, does not take leave, and does not require a salary review after twelve months.

This does not mean fresh graduates are without value. But it does mean the value proposition that once made hiring a fresh graduate an obvious investment now requires a more explicit business case. The burden of proof has shifted — not because employers are hostile, but because the economics have changed.

What AI cannot yet do is equally important. It cannot exercise genuine judgement in ambiguous situations. It cannot build trust across a room. It cannot be held accountable for a consequential decision. It cannot navigate organisational politics with sensitivity, or bring the kind of contextual awareness that comes from having lived and worked through real complexity. These capabilities — once bundled alongside routine task-completion in most roles — are now the primary differentiators.

The uncomfortable implication for mid-career professionals is worth stating plainly: experience built predominantly on tasks that AI can now perform is not the same as the kind of experience that remains hard to replace. The question is not how many years you have worked, but what kind of work those years reflect.

Both sides have a point — and both are missing something

The employer who says candidates are unrealistic is not wrong. Salary expectations anchored in a previous era's market conditions, for roles whose task content has materially changed, are genuinely disconnected from current hiring economics.

The graduate who says the system failed to deliver is also not entirely wrong. The signals were real, the investment was real, and the shift happened faster than any individual could have anticipated or prepared for.

But both framings lead to dead ends if left there.

The employer who simply rejects candidates without articulating what they actually need — beyond "someone who hits the ground running" — is not helping the market function. The absence of clear communication about what has changed, and what would now constitute a strong candidate, leaves graduates navigating a system with rules that nobody has clearly stated.

The graduate who holds out for a salary or role commensurate with their expectations is making a choice — not necessarily the wrong one, but one that carries real trade-offs worth understanding clearly before committing to it.

The case for holding out has some logic. A higher starting salary, in theory, compounds over time — it sets a higher baseline for future negotiations and signals market confidence. For candidates with the financial means to wait, and with a realistic read of what the market will bear, it can be a defensible strategy.

But it is a gamble, and the odds deserve honest examination. Every month spent waiting is a month without experience being built, skills being sharpened, and professional relationships being formed — all of which are the actual currency of career progression. The assumption that holding out will be rewarded relies on two things being true simultaneously: that the market will eventually meet the candidate's expectations, and that employers will not view the gap in employment as a signal of its own. Neither is guaranteed.

There is also the question of the halo effect. Being a fresh graduate carries a particular kind of appeal — potential, energy, a blank slate. That appeal has a shelf life. Each year, a new cohort enters the market. The candidate who was a promising new graduate at 23 is a harder sell at 25 with no employment history to show for the intervening time.

None of this means a candidate should take the first offer that comes along regardless of the terms. That is not the argument. But it is worth knowing that many strong careers have been built through roles that looked like detours at the time — positions below the expected salary, in industries adjacent to the original plan, that turned out to be the foundation for something better. The detour, taken with intention, is often less of a setback than it appears in the moment.

There is one more market reality worth naming plainly, because it rarely features in the local conversation about graduate employment: Singapore-based candidates are no longer competing only with each other.

Remote and hybrid work has fundamentally changed the geography of hiring for a growing number of roles — particularly in technology, finance, marketing, and knowledge work more broadly. An employer in Singapore can today hire a qualified candidate from anywhere in the region, or beyond, at a price point that reflects a very different cost of living. The salary expectation of a Singapore graduate, shaped by local housing costs, transport, and living standards, sits in a different bracket from a comparably skilled candidate based in Kuala Lumpur, Manila, or Jakarta. For roles that can be performed remotely, that comparison is increasingly live in the employer's mind — even when it is not stated explicitly in the job description.

This is not an argument that Singapore candidates should accept any price. It is an argument for understanding the full competitive landscape before anchoring expectations. The market a graduate is entering today is larger, more interconnected, and more price-sensitive than the one their predecessors entered. Recognising that is not defeatist. It is the starting point for a realistic strategy.

And it is worth acknowledging what this generation of Singaporean graduates does have that previous ones did not: a government that provides meaningful active support through SkillsFuture credits, career conversion programmes, and graduate employment assistance. Previous generations navigating economic dislocations — recessions, the aftermath of SARS, the Global Financial Crisis — did so with considerably less structural support. The transition is genuinely difficult. It is not, by historical standards, unsupported.

From a "me" story to a "you" story

This is not the first time the rules of the job market have shifted mid-game. Every generation has had its version of disruption — language policy shifts, computerisation, globalisation, financial crises, and now AI. Previous generations did not know in advance that the disruption would pass or that they would find a footing on the other side. They adapted without that certainty.

The most durable lesson from those transitions is not about any specific skill or credential. It is about how you present your value.

The old approach was a "me" story: here are my qualifications, my grades, my title, and the salary I expect. This assumed employers would recognise the signal and make the connection to value themselves. When the signals were reliable, this worked. When the signals are weak, it does not.

The more effective approach today is a "you" story: here is what I understand about what your organisation needs, here is specifically how my capabilities address those needs, and here is why hiring me at this price makes business sense for you.

This reframing is not about undervaluing yourself. It is about understanding what actually drives hiring decisions — and meeting that logic where it operates, rather than where you wish it operated.

For fresh graduates, this means honestly acknowledging the gap between credential and demonstrated capability, and offering a value proposition that reflects it: genuine willingness to learn, adaptability, and a starting point that makes the employer's investment easier to justify. For experienced professionals, it means translating tenure and titles into specific outcomes — problems solved, decisions shaped, value created — and being clear about the capabilities that remain genuinely hard to replace.

The signal has changed. The underlying question has not: can you create more value than you cost, and can you make it easy for an employer to see that?

What this means, in the end

The frustration is legitimate. The investment was real. The shift was faster than anyone should have been expected to anticipate. Empathy for this generation of graduates is not misplaced.

But frustration, however justified, does not change the market. And the market — shaped by technology, geopolitics, and global economic forces that sit well beyond the reach of any single government or employer — is not waiting for the argument to be resolved.

There was no contract. But there were signals. And now that the signals have changed, the most useful question is not who failed to honour a promise that was never made — it is what new signals are worth building, and how quickly you can start.

The job market has always rewarded people who understood what employers actually need and could demonstrate they could deliver it. That has not changed.

What has changed is that the old shortcuts to demonstrating it no longer work as reliably as they once did. Which means the work of making that case — clearly, specifically, and in terms the employer can act on — falls more squarely on the candidate than it ever has before.

That is uncomfortable. It is also an opportunity, for the candidates willing to do that work.

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If you or your organisation are looking to build the capabilities that remain genuinely valuable in this environment, reach out to us at FYT Consulting.