In my ~20 years in this industry, I’ve not seen as many capable engineering leaders opting out or taking prolonged breaks as now, with some high-ranking engineering leaders – CTOs, VPs of Engineering, heads of engineering, etc. – quitting their high-status roles and departing, if not into the sunset, then at least with nothing lined up.
To find out what might be behind this spate of sign-outs, I talked with almost 20 engineering leaders currently on a career break – or seriously considering one – and they let me into their personal reasons for deciding to jam the brakes on their careers. Thanks to everyone who shared their input!
Today, we cover:
**Ten of the most common reasons for quitting,**sometimes without the next gig lined up:1. The job got (much) worse
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The startup is “losing” and becoming worthless
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Not being AI-native enough for other skills to be relevant
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Their predecessor saw the “writing on the wall”
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Long hours – rarely decisive
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Smaller teams mean less need for leaders
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Fractional CTO work preferred over fulltime positions
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AI startups pay ICs more than non-AI startups pay executives
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Quitting to launch their own business
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Burnout
**“Founder mode” looks here to stay, so how to deal with it?And has it made the CTO and VPE roles become “low ROI”?‘Work at companies that truly want to drive change’.**A personal account from someone who took the VP of Engineering role at Gitpod (later, Ona, now acquired by OpenAI) and enjoyed a rewarding experience. Matt Boyle says he interviewed the employer beforehand on whether their business truly leans into the changes brought by AI.
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I was recently messaged by a head of engineering in San Francisco, who said:
“I’m talking to four startups in San Francisco about the head of engineering roles. Pretty normal.
But one interesting pattern is how founding CTOs/heads of engineering are stepping away to take a full career break.We’re talking about two of these four startups. And these are good startups!Have you seen this trend? I have a small number of data points here, so you might have a broader view.”
I asked around privately, and it turns out a majority of the CTO-level folks I spoke to are considering the very same thing, or are actually in the process of leaving the office for a long spell away; 6/10 engineering leaders said they’re on the way out.
Unrealistic expectations, including about AI, by founders and CEOs are the leading cause of jobs turning bad for CTOs and VPEs right now in 2026:
CTO expected to magically transform the company to be “AI-native”
CTO must make significant engineering cost cuts of up to 20-50%, including morale-sapping job cuts
“Do more with less” equals shipping more with fewer people (e.g., no backfills)
CTO faces pressure on business results as AI coding bills rack up
Founder slop: they want wonky AI prototypes shipped as full-blown products within weeks
**Hands-on founders with “AI psychosis” make the job predictably harder, **according to one CTO who just signed out of his job:
“Managing ‘AI psychosis’ with founders and executive peers has become very difficult. For example, what do you do when a founder ships a 60,000-line pull request into the product, gleaming with joy at how much more productive they’ve become with AI? They won’t see all the issues with that PR, and how do you bring up that they’ve created a massive amount of tech debt? Especially without looking like a ‘Debbie Downer’.”
Founder slop issues begin when top leaders** get **excited about AI’s capability, then get hands-on and start issuing PRs, and shipping code to production. It can cause issues across the board:
Accountability. Who’s oncall when founder-shipped code breaks? In the “you build it, you own it” culture of startups, it’s confusing when a founder gets hands-on while not owning their work.
Quality out the door: if a founder’s half-baked features are accepted, it sends the wider message that quality does not matter. Some people may adopt this attitude to their own work.
A founder can overrule whatever was previously agreed with the CTO or VPE about what to build next. Vibes the founder has or feels are reason enough.
**Another way that leadership roles have diminished is that craft and quality are less important, **says a VP of engineering who’s in the process of signing out of their job:
“Shipping software became all about speed. Finding differentiation with your product in the market is brutal, and speed / go-to-market becomes the biggest differentiator. Craft, quality, and care going into the product are taking a backseat.”
**Things also go bad when companies don’t ‘get’ AI+engineering, except as a way to cut jobs. **CTOs I talked to mentioned the likes of Ramp, Stripe, and Notion as places that understand how to integrate AI into the engineering culture with a growth mindset without forsaking quality. Elsewhere, bad vibes dominate at places where going all-in on AI leads to the cynical conclusion that product management, design, and engineering leadership are irrelevant.
Director+ roles have a few differences from individual-contributor engineering ones:
**Larger equity stake in the business.**Base salary at these levels is often similar to a staff engineer’s, but usually with more generous equity grants – especially at the VP of Engineering and CTO levels. A good financial outcome depends on the company becoming more valuable, and – in the case of private companies – having a good exit by being acquired or selling shares.**Understanding of the business and competition is a baseline.**At Director+ level, a big part of the job is making strategic decisions that grow the business and help the company get ahead. It’s a nice-to-have for an engineer to possess business acumen, but director-and-above folks use it much more than most individual contributors (ICs). Great engineering leaders are good at understanding business performance and outlook.
A company that adopts AI rapidly usually falls into one of three buckets:
**“AI-native”, building & selling AI products.**The large AI labs and a select few “AI-native” startups are thriving, but many AI startups with VC funding struggle. Engineering leaders know this, and that their equity – usually issued as options – could end up worthless.**Software startups threatened by AI-native businesses.**Good businesses in the pre-AI world can be threatened by AI today, like SaaS startups selling seat-based products in areas where agents are taking over the functionality. They have to pivot their businesses or seek an exit. Bending Spoonsbuying Airtablefor less than the company raised is an example of a business threatened by AI and choosing to sell, instead of pivoting the whole business.**Unaffected by AI.**Usually stable businesses which do more than software, such as with a real-world side to the operation like manufacturing or distribution.
The majority of software startups fall into one of the first two buckets of being AI-native or under threat. Senior leaders at such companies are in a good position to evaluate whether their company is a “winner” worth staying with.
A CTO who quit their startup told me:
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My company would have needed a massive exit for me to realize any upside.I had an equity grant that was 2% of the common shares. However, this equity was behind an already steep preference stack for investors, post Series A.”
This CTO had a very generous equity grant at 2% of shares, so what made him leave it behind? They laid out how it will be difficult to get any benefit from them because the shares are most likely rendered worthless by rules about the order in which different investors get their share of the pie:
Assume that this company raised a $10M seed round at a $50M valuation, then a $100M Series A at a $500M valuation. So, a total of $110M was raised across two rounds.
Investors typically have a 1x preference. 1x preference would mean that upon any sale, they get the first $110M of the sale.
But in this company, the Series A investors negotiated a 2x preference: so upon a sale, $210M goes to investors first ($10M to the Seed, and $200M to the Series A investors).
The company now needs to sell for at least $210M for common shareholders (like the CTO) to make
anymoney!If the CTO does not believe a $200M+ exit could happen, then their equity is worthless. A $200M+ exit is typically an acquisition, because a stock market flotation rarely happens at below a $10B+ valuation, these days.
If a VC-funded company does not have the revenue or customers to grow at a fast tick (circa 20-50% per year), then it’s often a struggle to raise the next round of funding, and the business’s actual value usually shrinks to 3-5x of annual revenue. So, if a startup is making $10M per year after raising $110M in funding, and growing 30% year-on-year, then the company is likely worth around $30-50M. Perhaps the right buyer would pay $100M, but if growth slows, the value is likely to drop.
An experienced CTO who takes a step back and assesses things can realize when there’s a high chance of their equity turning into smoke, removing a reason to not sign out of the job. It’s what happened to the CTO above, and when they couldn’t turn the business around, they quit.
When a VC-funded startup’s business stops growing, the prognosis can be dire in the sense that it’s unlikely to be worth as much as in the previous funding round. This is true even when the startup becomes profitable: this might mean it could theoretically go on forever; but with slow or no growth, it won’t win in another VC funding round.
Here’s a VP of Engineering who saw their startup stop growing, partly due to wrong bets by the CEO:
“My founder/CEO was nontechnical, and was both moving too slow and too fast with AI.
Too slow, as in they did not take the time to understand what our customers wanted. We built a TON of AI stuff, it totally confused them, they churned, growth stalled, word-of-mouth growth was gone. Heck, I don’t think our customers ever wanted or needed anything with AI!
Too fast, as in they deprioritized core systems’ reliability in favor of shipping AI work to prod which did not have any commercial potential. So, our core offering started to have more outages and we lost customers because of this as well.”
I’d add that deprioritizing reliability in favor of building features may be sensible in the early days. The problem seemed to be that this company had not found product-market fit, and the new AI features didn’t resonate with customers. Basically, the CEO lacked customer understanding, business intuition, or both.
So, good on the VPE for getting out when they saw the direction of travel. If the CEO won’t accept input from the VPE – who would’ve at least prioritized reliable operation – then there isn’t much left to stick around for!
The top-paying engineering leadership positions have one thing in common: experience of leading AI-native organisations is expected, and leaders are sought who have turned their current company AI-native, or work at such a place.
It’s new to see people signing out of large companies for feeling like they’re lagging behind in adopting new AI workflows. An ex-engineering director at a large bank told me they quit their job to accelerate their career:
“I was not getting the opportunity to ‘close the loop’ on hypotheses enough. [...] To stay relevant in the industry, I feel like I need to pull out into the “fast lane.”
Like many others, I see the future of software development is with AI. If you don’t get hands-on with your team, working with AI tools day-in, day-out, you’re falling behind.
My plan is to get on the cutting edge of things through a mix of academia and consulting AI companies. I am not saying the plan is perfect, but I need more time to do things differently than I had in my job.”
Consider this: if you stay in your job for two more years, do you expect to find career opportunities at cutting-edge companies in the future? If the answer is “no”, then there’s a risk in just staying put. Joining an uncertain startup or taking a career break to develop AI expertise is also risky, but the outcomes may be more controllable than letting your skillset become outdated, relatively quickly.
But it might actually be necessary to quit in order to get AI experience: you might be able to get this by transferring to an IC role. As Charity Majors, co-founder and CTO of Honeycomb, said in last week’s episode of The Pragmatic Engineer podcast:
“You’ve got to get AI on your resume. You just have to. If you don’t, this is a huge career risk. If you’re working somewhere where you’re not getting these skills, I would do whatever I could to change that [including taking an IC role within the company].”
There are companies where moving from Director+ to individual contributor is possible, even if these companies are the minority. If you happen to work at a place like this: consider if you can and will take advantage of this opportunity.
Claire Vo – founder of ChatPRD and host of ‘How I AI’ podcast, and the former Chief Product & Technology Officer at LaunchDarkly – 𝕏says most companies will never become “AI native” simply because most VP of Engineering or CTO folks don’t have what it takes to pull off such a transformation. In 𝕏her words:
“The VPE role used to be primarily about deploying the dark arts to defend engineers from the roadmap, and now everyone thinks that’s BS and leaders are under tremendous pressure to inflect velocity or GTFO (get the f*** out).
Engineers are unhappy (don’t make me tokenmaxx, bro!), product and design sending slop PRs, and everyone good has left for a lab.
Most of these companies’ EPD (Engineering, Product, Design) orgs will never go AI-native, not even close. Most VPEs aren’t good enough at change management to pull it off.”
It looks like there’s a deadlock:
The current engineering org is frustrated by how AI is making engineering culture worse, morale is down, and people are frustrated and confused
To resolve this, drastic changes are needed to how everyone (engineers, product, designers) works
To pull it off, a VP of Engineering or CTO is needed who’s capable of this; someone excellent at change management, who’s ideally done it before.
But most VPEs and CTOs are not experts at large-scale change management, nor have done it before.
According to this, many VPEs and CTOs are doomed to fail at making the change they want, and it’s hard to know if that’s because organizations didn’t support them properly or resisted change.
There’s (usually) a honeymoon period in a new job, when we believe in the business we’ve joined and in its direction. But when this phase passes, a fraction or all of the problems described above may emerge, and there’s a decent chance that some of them are why your predecessor signed out:
Has AI helped make the role worse?
Is the equity on course to be worthless?
Is getting AI-native experience actually possible, or is the organization resisting change?
I’ve talked with a CTO who replaced their predecessor and founding CTO. A few years into the job, the predecessor CTO realized their equity in the business was worth almost nothing due to stalled growth, all while they were also being out-competed by AI-native rivals. So, the new CTO also resigned after a short, six-month tenure.
Two engineering leaders – a CTO and a VP of Engineering – mentioned “insane working hours” as a factor that contributed to them finally quitting. But there were other things as w…
