The candidate had the strongest take-home we had seen that quarter for a Singapore fintech client: clean TypeScript, tests, a README that explained the trade-offs. In the follow-up call our engineer opened the pull request and asked him to walk through one function — why the retry was bounded at three, why the error was swallowed on the second branch. He could not. Not because he was dishonest; he told us straight away that an agent had produced most of it and he had reviewed it “at a high level”. He was, it turns out, statistically normal. On Tuesday a survey put a number on how normal, and the number is why we have rewritten three rounds of every interview loop we run in Singapore.
What Was Reported on 15 September, in the Words of the People Who Reported It
VentureBeat’s headline, published on 15 September 2026 under Carl Franzen’s byline, was “The share of developers using AI to write half or more code jumped from 12% to 42% YOY in latest BairesDev survey”. The source is BairesDev’s Q3 2026 Dev Barometer, which surveyed 705 developers across more than 60 countries and, separately, 41 enterprise CTOs. The figures that matter for anyone who hires:
- 42% of developers say AI writes at least half their code, against 12% in the same quarter of 2025.
- 13 hours of coding time saved per week, up from about 7 a year earlier.
- 67% spend more time reviewing AI-generated code than a year ago; 52% spend more time debugging AI-introduced problems.
- 9 hours a week learning AI tools, up from 4.
- Only 21% still spend more than half their week writing new code from scratch.
- Of the 41 CTOs, 78% have increased spending on code review, QA and validation; 7% now ship AI-written code with no developer input at all.
- 86% say AI makes their role more fulfilling, up from 76%.
BairesDev’s chief executive Darren Shimkus gave the line I have been repeating to clients all week: “In a world where we don’t have AI explainability, I need developer explainability.” He also said the job “hasn’t gotten smaller; it’s moving up a level”, and, asked where a developer should go deeper, answered: “go deeper in security.” The survey follows BairesDev’s June release, “Only 16% of Senior Developers Say Junior Engineers Fully Understand AI-Generated Code”, which is the other half of the same story.
💡 Our Expert Take
The 42% is the headline; the 67% and 52% are the story. Thirteen hours saved on typing, then most of it re-spent reading, testing and repairing what was typed. That is not a productivity miracle and it is not a productivity mirage either — it is a change in what the job consists of. The developers you hire from now on will spend more of their week judging code than producing it, and almost no interview loop in Singapore tests judgment.
Why This Is a Singapore Hiring Story, Not a Survey Story
The survey landed the day before the fifteenth Tech in Asia Conference opened in Singapore on 16 September under the theme “Lead the Enterprise AI Era”, with more than 2,000 attendees and an explicitly enterprise-first agenda about deploying and scaling AI. Every engineering leader in that hall is being asked the same question by a finance team: if AI writes half the code, why is the engineering budget not half the size?
Singapore is where that question bites hardest, for three reasons. Engineering salaries here are among the highest in the region, so the temptation to cut is strong. The market has already priced AI fluency: as we reported in May, junior engineers with AI skills command a 25% premium even as tech job cuts continued. And employers here still struggle to fill senior roles, which are precisely the reviewing roles this survey says matter more.
Put the numbers together and the arithmetic is uncomfortable for the cut-a-third argument. A developer who saves 13 hours a week on typing but spends more time reviewing, more time debugging and 9 hours learning tools has not freed up a third of their week; they have changed how it is spent. Seventy-eight per cent of CTOs raising their review and QA spend is the market admitting it.
💡 Our Expert Take
Three Singapore clients asked us this month whether they could open four backend roles instead of six because of AI tooling. Our answer was the same each time: open five, and make two of them senior enough to review the other three. A team of four in which nobody has time to read the code is how the 7% who ship without developer input gets created, and in a regulated Singapore fintech that is not a productivity setting, it is an incident waiting for a date.
The 3 Interview Rounds I Rewrote
We did not ban AI tools from interviews. Banning them tests a job that no longer exists. We kept the tools and changed what we score. The write-from-scratch round is gone; these three took its place, and every one of them lets the candidate use whatever assistant they normally use.
Round 1 — Explain your pull request
The candidate submits a small feature, produced any way they like, and the interview is a line-by-line walk-through of their own diff. Why this bound, why this error path, what happens under concurrency, what they rejected. We are scoring developer explainability in Shimkus’s sense: can this person stand behind every line they ship? The fintech candidate from the opening paragraph would have been caught in the first ten minutes instead of the final round, and — more usefully — would have known in advance that we would ask.
Round 2 — Debug the almost-right
We hand over a solution generated by an assistant that is 95% correct and 5% quietly wrong: an off-by-one in pagination, a timezone assumption, a retry that is not idempotent. The candidate has forty-five minutes, with tools, to find it and explain it. This is the 52% figure turned into an exercise. The developers who are worth a Singapore salary in 2026 are the ones who read generated code with suspicion by default.
Round 3 — Review someone else’s change for correctness and security
A pull request written by a colleague with heavy AI assistance, containing one correctness issue and one security issue — an injection path, a secret in a log line, a missing authorisation check. The candidate writes the review they would leave on it. Shimkus’s advice to go deeper in security than in code-generation tooling is the whole rationale; so is the fact that 78% of CTOs are spending more on exactly this activity and almost none of them interview for it. Our code-review quality gates piece has the rubric we use to score it.
Want candidates who have already passed all three rounds?
Every developer we present to a Singapore client has defended their own pull request, found the defect in an almost-right solution, and written a security review our engineers agreed with. Let’s talk about the roles and the review capacity you actually need.
Let’s Discuss Your LoopWhat the Singapore Market Looks Like When You Screen This Way
Screening for explainability changes who passes, and it changes the price. Across the loops we have run in Singapore since we introduced the three rounds in July, the pass rate for candidates whose take-homes looked excellent fell by roughly a third at Round 1, and the candidates who do pass have skewed more senior. That is consistent with the survey: the compensation drivers for 2026 raises were AI tool fluency (29%), system design and architecture (20%) and human skills (15%), and all three are review-side skills. The other thing we noticed is that strong candidates like the rounds. They are being asked to show the part of the job they are proud of.
| Round | What it replaces | What it measures | Time |
|---|---|---|---|
| 1 — Explain your PR | The anonymous take-home | Ownership of every shipped line | 45 min |
| 2 — Debug the almost-right | Algorithm whiteboarding | Suspicion of generated code, systematic debugging | 45 min |
| 3 — Review for correctness and security | The “tell me about a time” behavioural round | Review quality, security instinct, written communication | 40 min |
For juniors specifically, the June finding that only 16% of seniors think juniors fully understand the AI code they submit is a reason to change the junior loop, not to close it. We run Round 1 for juniors with a smaller feature and score explanation alone, then pair every junior hire with a senior reviewer for the first ninety days; the assessment techniques we published earlier this year still hold, with Round 1 added at the front.
💡 Our Expert Take
The candidate who could not explain his pull request was not a bad engineer. He was an engineer whose last employer had never asked him to. We passed on him for that role and told him exactly why; he came back to a different client’s loop eight weeks later, walked through every line, and got the offer. The rounds are not a filter for honesty. They are a description of the job, and most developers rise to a job once someone describes it.
What to Do This Week If You Run Engineering in Singapore
- Pull your last five hires’ interview scorecards and check whether any round measured review or debugging. If none did, you have been hiring for a shrinking part of the job.
- Replace the take-home with Round 1 in your next open loop. It takes an afternoon to set up and it is the highest-signal change we have made in two years.
- Re-run the headcount conversation with the 67% and 52% figures on the slide, not just the 42%. Ask for one senior reviewer per three producers.
- Write down who reviews AI-generated code before it ships in each team. If the answer is nobody, you are already in the 7%.
If You Also Run Teams in Dubai
The survey is global and so is the fix. Our Dubai colleagues reached a similar design from the portfolio side in how to evaluate an AI engineer’s portfolio in Dubai and designing an AI-native technical assessment for senior engineers. If your engineering org spans both hubs, use the same three rounds in both; the scorecards then compare.
FAQ — The BairesDev Survey and Singapore Developer Hiring
What did the BairesDev Q3 2026 survey reported on 15 September 2026 actually find?
According to VentureBeat’s 15 September 2026 report on BairesDev’s Q3 2026 Dev Barometer, which surveyed 705 developers in more than 60 countries plus 41 enterprise CTOs: 42% of developers say AI writes at least half their code, up from 12% a year earlier; AI saves them about 13 hours of coding per week, up from roughly 7; 67% spend more time reviewing AI-generated code than a year ago; 52% spend more time debugging AI-introduced problems; developers spend 9 hours a week learning AI tools, up from 4; and 78% of the CTOs have increased spending on code review, QA and validation, while 7% ship AI-written code with no developer input.
If AI saves developers 13 hours a week, can a Singapore company hire a third fewer engineers?
Not on this evidence. The same survey shows 67% of developers spending more time on code review and 52% more time debugging AI-introduced problems, plus 9 hours a week learning tools. The hours saved on typing are largely re-spent on verification. The realistic planning assumption is a team of the same size that ships more, with a higher proportion of senior reviewers, rather than a smaller team shipping the same amount.
How should a technical interview change now that AI writes so much of the code?
Test the work that is growing, not the work that is shrinking. We replaced the write-from-scratch round with three others: a pull-request explanation round in which the candidate defends an AI-generated PR line by line; a debugging round built on an almost-right AI solution with a subtle defect; and a review-and-security round in which the candidate reviews someone else’s AI-assisted change for correctness, injection and data-handling issues. Candidates may use AI tools throughout; what is scored is judgment and explanation.
Does this change junior developer hiring in Singapore?
It raises the bar for juniors and the value of seniors who can review. BairesDev’s June 2026 survey found only 16% of senior developers believe juniors fully understand the AI-generated code they submit. For Singapore employers the practical response is to hire juniors for explainability rather than output, pair each with a senior reviewer, and use the structured apprenticeship and Employment Pass pathways that reward skills-based hiring rather than cutting the junior pipeline altogether.
Hire for the job as it is now
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