u/EchidnaFromMel

What actually separates high performers at work from everyone else?

What actually separates high performers at work from everyone else?

A lot of workplace advice still treats “high performance” as working longer hours, replying faster, being visible in every meeting, or always saying yes.

I don’t think that’s what consistently separates the strongest people.

The behaviours I see matter more are things like:

  • Leading before you have the title — taking ownership without waiting for formal authority
  • Finishing important work — not confusing activity with progress
  • Confidence + humility — having a view, but changing it when the evidence changes
  • Making other people better — sharing context instead of hoarding it
  • Knowing when to say no — protecting high-value work from unrealistic priorities
  • Being trusted without constant supervision
  • Listening before responding
  • Surfacing problems early, rather than waiting until there is a crisis
  • Improving the system, not just repeatedly solving the same problem

The last one is probably the most underrated.

A good employee can solve a difficult problem.

A very strong employee solves it and leaves behind a process, tool, rule or piece of knowledge that makes the same problem less likely to happen again.

And there are also a few things I increasingly think are not signs of high performance:

Working the longest hours.
Being permanently available.
Dominating meetings.
Saying yes to everything.
Making yourself indispensable because nobody else understands your work.

The better test might simply be:

Can this person consistently deliver, exercise good judgement without constant supervision, strengthen the people around them, and leave the organisation better than they found it?

What would you add to the list — and which “high performer” behaviour do companies tend to reward even though they probably shouldn’t?

u/EchidnaFromMel — 5 hours ago

What meetings does a leadership team actually need?

More meetings do not automatically create better management. The useful question is whether each recurring meeting has a distinct job.

A practical system might include:

  • Weekly execution: what’s moving, what’s blocked, who owns the next action
  • Monthly 1:1s: wellbeing, motivation, development and issues dashboards miss
  • Monthly all-hands: direction, progress, setbacks and what comes next
  • Quarterly strategy review: step outside day-to-day execution and challenge assumptions
  • Annual culture touchpoint: strengthen relationships and belonging
  • Decision meetings: resolve one consequential question and leave with a clear decision
  • Post-mortems: turn wins and failures into learning

The principle I like most: if two meetings cover the same material, combine them. If a meeting produces no decision, learning, coordination or human connection, question why it exists.

What recurring meeting would you remove first?

u/EchidnaFromMel — 1 day ago

What actually makes a great sales hire in 2026? Persuasion, ambition and resilience

A lot of sales hiring still overweights the person who interviews well.

But the strongest performers usually need three things together:

  • Persuasive — can build trust and move people
  • Ambitious — keeps pushing the pipeline forward
  • Resilient — handles rejection without losing momentum

Miss one and the failure mode changes: persuasive without enough ambition can plateau; ambition without persuasion can create lots of activity but little conversion.

The part I think hiring processes underrate most is resilience — it’s much harder to see in a polished interview than confidence or communication.

If you hire salespeople, which of the three is hardest to assess properly?

u/EchidnaFromMel — 2 days ago

US hiring today: Product Manager +71, Software Engineer +59, Financial Analyst +40, Data Scientist +16

A quick snapshot of four US job markets from today’s live postings:

  • Product Manager: 8,693 roles · +71
  • Software Engineer: 8,274 · +59
  • Financial Analyst: 5,522 · +40
  • Data Scientist: 3,442 · +16

A few things stand out: New York leads Product Manager, Financial Analyst and Data Scientist demand, while San Jose remains the strongest Software Engineer market with 1,001 open roles.

The interesting signal is that growth isn’t limited to engineering — product and finance are also adding roles today.

Are you seeing the same pattern in your job search?

u/EchidnaFromMel — 4 days ago
▲ 5 r/workopiajobs+1 crossposts

OpenAI vs Anthropic hiring in 2026: what are they actually hiring for?

I compared the hiring data for OpenAI and Anthropic, and the biggest difference isn’t the number of jobs — it’s how differently the two companies are building their teams.

OpenAI

  • 1,152 jobs tracked
  • 116 currently active
  • 76% of roles are remote
  • 81% of recent postings are US-based
  • 5.8% fall into AI/ML-related buckets
  • Program Manager currently leads the hiring mix

Anthropic

  • 1,975 jobs tracked
  • 108 currently active
  • 90.1% of roles are on-site
  • 56% of recent postings are US-based
  • 5.1% fall into AI/ML-related buckets
  • Staff Engineer leads the current hiring mix

The contrast that surprised me most:

OpenAI looks much more remote and US-concentrated, while Anthropic is considerably more on-site and geographically distributed.

And at both companies, only ~5–6% of the roles fall directly into AI/ML buckets.

The teams being built around the models are much broader than the model teams themselves.

For people following AI hiring: which difference between OpenAI and Anthropic stands out most to you?

u/Dependent-Pick8591 — 6 days ago

How is the Singapore job market right now? Live job openings by role, updated daily

Last updated: August 18, 2026

I'm keeping this thread as a running snapshot of the Singapore job market rather than starting a new post every day.

Across the full dataset I'm tracking 297,565 active job postings, +1,166 since yesterday.

Some of the largest job pools right now

  • Administrative Assistant — 4,628 · —
  • Sales Representative — 4,050 · -1
  • Sales Manager — 3,583 · +1
  • Project Engineer — 3,155 · —
  • Project Manager — 3,031 · +3
  • Business Development Manager — 2,638 · +2
  • Operations Manager — 2,624 · —
  • Intern — 2,397 · +19

Professional and specialist roles

  • Software Engineer — 2,109 · +1
  • Business Analyst — 1,550 · —
  • AI Engineer — 1,443 · —
  • Product Manager — 1,378 · +3
  • Senior Software Engineer — 1,029 · +1
  • Data Engineer — 975 · —
  • Financial Analyst — 708 · -2
  • Data Scientist — 572 · +1

What moved today

Intern added 19 roles today, the strongest single-board move in the Singapore set. The broader market moved more strongly (+1,166 overall) than the named role boards account for, so the change is spread well beyond the roles listed here. Machine Learning Engineer fell the furthest at -4, one of 27 boards down today.

The national total is the complete live Singapore inventory. The role boards above are indexed snapshots of named job titles — they cover only part of that inventory, they overlap each other, and they should not be added up.

Financial Analyst here is the narrow board only — it does not roll in Finance Manager or Financial Advisor.

I'll keep the latest numbers here and add a dated snapshot in the comments each day so the history stays in one place.

workopia.io
u/EchidnaFromMel — 8 days ago

If you’re in marketing and want to move into data, Data Analyst may not actually be your easiest first move

I tried mapping a fairly common career switch:

Marketing Coordinator → Data Analyst

The interesting part was that the direct jump wasn’t necessarily the only — or easiest — route.

A typical marketing coordinator already has some of the foundation:

Excel, Google Analytics, reporting, dashboards, funnel/customer data, and sometimes basic SQL.

The gap is usually more specific: Power BI, stronger data visualization, deeper SQL/data analysis, and some Python.

When I mapped those skills against actual openings, three paths emerged:

Direct: Marketing → Data Analyst
Closest analytics bridge: Marketing → BI Analyst
Broader practical bridge: Marketing → Business Analyst

The third one is easy to overlook. Business Analyst roles can make use of the process, stakeholder and commercial skills someone from marketing already has, while still moving them toward more analytical work.

So rather than thinking:

“How do I become a Data Analyst?”

it may be more useful to ask:

“What is the shortest credible bridge between what I already do and where I want to end up?”

For this example, I’d probably build Power BI + data visualization first, then rewrite existing campaign/reporting work as evidence of analytical work rather than starting from zero.

I mapped the example against current openings in the image.

Would be interested to hear from anyone who actually made marketing → data/BI/BA. Which route did you take?

u/EchidnaFromMel — 9 days ago

London has 623 Product Manager openings vs 345 Software Engineer and 198 Data Scientist roles

A quick snapshot of London’s job market today:

  • Product Manager — 623 live roles, +5 today
  • Software Engineer — 345, +1
  • Data Scientist — 198, +2

The part that caught my attention: product management openings are nearly 2x software engineering and more than 3x data science in this dataset.

There are also some genuinely new roles appearing today — including product positions at Lloyds, bp, Worldpay and EY, while AIG added a GenAI Data Scientist role.

This is based on currently active roles from company career pages, refreshed daily — so I’m going to keep watching whether this gap persists or is just a point-in-time London effect.

Curious if people searching in London are seeing the same thing: does PM feel noticeably more active than engineering/data right now?

u/EchidnaFromMel — 9 days ago

Sydney has 2.2× as many software engineering openings as Melbourne. For data science, the gap is much smaller.

Today’s snapshot from Australian company career pages:

Software Engineer

  • Sydney: 151 live roles
  • Melbourne: 69

Data Scientist

  • Sydney: 60 live roles
  • Melbourne: 44

The contrast is interesting.

Sydney has more than twice as many software engineering openings as Melbourne, but only ~36% more data science roles.

And neither data science market is particularly large: just 104 live roles across the two cities in this snapshot.

A few names in the listings: Canva, Xero, Accenture, Riot Games, Shield AI, Coles and Transport for NSW.

These are currently live roles pulled from company career pages, not scraped reposts. Refreshed daily.

u/EchidnaFromMel — 9 days ago

Sydney vs Melbourne: where the software engineering and data science jobs are

A quick snapshot of two of Australia’s largest tech markets:

Sydney
• 151 Software Engineer roles
• 60 Data Scientist roles

Melbourne
• 67 Software Engineer roles
• 44 Data Scientist roles

Sydney is currently more than 2× Melbourne for software engineering, while the gap in data science is much narrower.

All are live roles from company career pages, refreshed daily.

u/EchidnaFromMel — 10 days ago

475 new graduate & entry-level roles added today — across 9 markets

A fairly active day for early-career hiring.

Across the 9 markets we track here, 475 new graduate & entry-level roles were added today.

US +222
Germany +99
France +44
Singapore +35
Australia +25
UK +19
Spain +17
Netherlands +12
Canada +2

The interesting part is how broad the hiring is — from software and quantitative roles to apprenticeships, audit, sales, engineering and operations.

These are live roles from company career pages, refreshed daily.

Full lists: workopia.io/graduates

u/EchidnaFromMel — 10 days ago

Backend Engineer → Product Manager: the direct switch is possible, but only <1% of PM openings are at your level

Second case in our career-switch series.

Starting point: Backend Engineer, 1 year experience, Seattle.

The obvious destination is Product Manager. The problem isn’t technical fluency — it’s proving product judgment, customer discovery and cross-functional leadership.

Based on current openings, three realistic routes emerged:

→ Product Manager: direct, but a stretch
→ Business Analyst: closer bridge
→ Data Engineer: safest technical bridge

The interesting part of career switching is often not “Can I become X?”

It’s “What is the shortest credible path from where I am today?”

u/EchidnaFromMel — 10 days ago

+1,074 graduate & entry-level jobs added across 10 countries — here’s where hiring is moving

1,074 new graduate and entry-level roles were added across the 10 markets we track in the latest daily update.

The three regional snapshots below cover North America, Europe and Asia-Pacific.

A few of today’s larger movers:

🇺🇸 US: +226
🇩🇪 Germany: +44
🇦🇺 Australia: +26
🇨🇦 Canada: +17
🇫🇷 France: +11
🇸🇬 Singapore: +9
🇬🇧 UK: +7

The mix is also much broader than the usual “graduate tech jobs” conversation — healthcare, engineering, finance, field service, trades, tax, data and corporate roles are all showing up.

These are roles pulled from company career pages and refreshed daily, rather than a static graduate-program list.

+1,074 in a single update is a meaningful amount of new entry-level supply.

u/EchidnaFromMel — 11 days ago

267 new roles were added across Sydney and Melbourne in yesterday’s update.

A snapshot of two of the more competitive professional categories:

  • Sydney: 151 Software Engineer + 60 Data Scientist roles currently live
  • Melbourne: 67 Software Engineer + 44 Data Scientist roles currently live

Recent openings include Transport for NSW, Canva, ResMed, Riot Games, Xero, Accenture, Origin Energy and others.

One thing that stands out: Sydney currently has more than twice Melbourne’s software engineering openings in this dataset.

Added the four snapshots for anyone searching in either city.

For Australians job hunting right now — does Sydney feel noticeably stronger than Melbourne?

u/EchidnaFromMel — 11 days ago