How Candid Can You Really Be With Your Boss?
How to deal with the trickiest phrase you can hear from a manager: I’d love your feedback
4 min
Marchiano Loen stared at his screen for two hours. He drafted one response, then another. He begged someone in human resources for help. Still, the question vexed him.
What can your manager improve on?
“Oh God, I actually have to answer this,” the tech worker thought as he pondered the employee survey. “What am I going to write?”
Bosses claim they want honest feedback. Telling the truth can spark change, make your work life better and show off your own assertiveness. Or you could get fired. (At least it feels that way.)
Like it or not, silence isn’t an option. But you have to be really careful about just how candid to get with the boss.
Loen says he was once frozen out by a manager after suggesting he could improve his communication style during presentations. Warm small talk and jokes evaporated, and Loen’s big projects were redistributed.
Now he uses what he calls “the Jacuzzi approach.” He dips a toe in with bosses to test the water, seeing how they react to a fairly neutral piece of commentary before saying anything of substance. He might ask, would that meeting be better on Tuesday than Monday?
“It’s a survival mechanism,” he says.
The lies we tell
The average person lies three times in the first 10 minutes of meeting someone new, according to research from Robert Feldman, a professor of psychological and brain sciences at the University of Massachusetts Amherst. Such superficial fibs lubricate many of our social interactions, he says, helping us fit in and getting people to like us.
This salad is delicious, we insist. Or I loved the “Barbie” movie, too! With the boss, the photo of their kid is suddenly extraordinarily cute, their jacket perfect for today’s presentation.
“At the end of the day, we want to hear good things,” Feldman says. “Your boss is just like everybody else.”
What about when bosses want to be tapped into what’s really going on, too? After all, you’re the one who’s connected to collegial chatter and gossip, which can give managers insight into how they can do a better job and get ahead. Giving the right information to your boss can help you, too. You just have to share it the right way.
“I want people to feel like they can be them,” says Karin Storm Wood, who manages a team of communication professionals at a private school. But, “I don’t want everything.”
Don’t assume you have all the facts, she says. Acknowledge you’re just sharing one person’s perspective. And keep your language grounded. For instance, describe a behaviour instead of lobbing a negative adjective at your boss.
Wood says she’s OK with hearing that she sometimes jumps around from idea to idea in brainstorming sessions. She doesn’t want you to call her “scattered.”
“That’s like, ‘Ouch,’ ” she says. “It has that element of judgment.”
Feedback, please!
Everyone seems to want our take these days. We’re subjected to quarterly 360 reviews, weekly pulse surveys and drive-by requests for input by the coffee machine. It’s part of a longstanding shift from command-and-control leadership styles to more collaborative ways of running companies, says Doug Stone, who teaches conflict management at Harvard Law School and co-wrote the book, “Thanks for the Feedback.” A lot of it stems from employees who have demanded more of a voice…even if another app wasn’t what they had in mind.
Be careful what you wish for.
“You have to say something,” says Matt Abrahams, who teaches at the Stanford Graduate School of Business and has a book coming out this week about spontaneous communication.
A smart start is to ask some questions of your own to the boss, says Abrahams. What kind of guidance do they typically find useful? If they readily divulge a time they messed up or made a change, be more candid, he suggests.
Emphasising the positive might subconsciously correct the negative. For example, praising the boss for being so focused at the start of her speech could imply that she completely lost her train of thought by the end, without you having to spell it out. But don’t get too soft, Abrahams warns, devolving into coded language and euphemisms.
“You’re being coy. You’ve got something to say but you’re not saying it. That can look really bad for you,” he says. After all, we were all hired to be experts in our jobs.
The risk of always saying yes
Earlier in his career, Irvan Krantzler used to nod his head yes to everything, eager to fit in. That project idea? It sounded great. A deadline next week? Sure, he could handle it.
The result, he says, was often “bad news, late.” The issue he didn’t speak up about—an unrealistic timeline, not enough people on the team—would fester and eventually send a project sideways.
“I can’t be put in a situation where I can’t be open with people,” he says he realised. He started voicing his concerns more, and left one employer where everyone was expected to agree all the time.
When Leslie Venetz’s boss asked her what she thought about a new team of salespeople, she assumed the pair were just spitballing thoughts in confidence. A few months later, her comments were shared with HR, she says, and a person she had identified as weak was fired.
She felt guilty and betrayed, and soon left the company.
Now when clients of her sales training and consulting firm request her feedback, she asks how they’re going to use it. Are they deciding the fate of a division this week? Or just considering a possibility, and gathering dozens of opinions in the meantime?
The answer, she says, determines her candour.
“Everyone says that they want feedback,” she says. “There’s something to be said for taking a moment.”
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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