By Dylan Parkes | May 20, 2026
The Game
There stands a young graduate from college
Their mind expanded with great knowledge
Oh, how they want a job
And are certainly no slob
But its tough right now we acknowledge
I had hoped to open with a beautiful poem from antiquity that would perfectly capture the current moment, the current job market. Alas, as the above limerick demonstrates, I am certainly not a poet nor a true scholar of poetry, but I do work with one.
My colleague, Amir Chireh Mehr, wrote a brilliant piece early last month connecting the Persian poet, Ibn Yamin, to Donald Rumsfeld to the financial realities of bringing small modular nuclear reactors to market. If that sounds like a fascinating linguistic (and analytical) feat, see for yourself in his blog Underwriting Careers
While I doubt I’ll produce a similarly erudite think piece, I do want to offer my thoughts on the current job market. Whether you are trying to enter the project finance space or remain in your current position, I believe the ultimate message applies in both contexts.
And, of course, I will offer my thoughts on the most discussed topic in the zeitgeist—artificial intelligence/large language models—and how these tools affect or impede or enhance employment and employment outcomes. (Em dash usage here is both appropriate and a stand against that excellent piece of punctuation being co-opted by the LLMs)
Latrell’s thoughts on your career
My other talented colleague, Matt Davis, already brought in a timely reference to the original, inimitable AI (Allen Iverson, of course) in his most recent post. What one AI can treach us about another
So, to remain competitive in the office, I will open my thoughts with a quote from another great icon of that same generation, Latrell Sprewell. Sprewell went from famous to infamous in 2004 when, following a landmark season in the NBA, he turned down a 3-year, $21 million contract extension.
At the time, he was reportedly “insulted” by the offer. He was quoted as saying,
“Why would I want to help them…? They’re not doing anything for me. I’ve got a lot at risk here. I’ve got my family to feed.”
This ultimately begs the question, “what exactly are you feeding them, Latrell?” That query aside, his decision proved to be a terrible choice and resulted in an almost immediate departure from the league. It proved to be a very clear case of over-estimation of ability and value. So, we want to look at how we estimate ourselves appropriately. Acknowledging that we also don’t want to underestimate ourselves and certainly don’t want to do what Latrell did. There is a reason that job interviews almost always feature personal psychological questions that target our ability to estimate ourselves (biggest strengths and weaknesses).
These questions often prove trickier than they appear with people giving non-answers (“my biggest weakness is caring too much”) or overly inflated answers (“All my weaknesses are actually strengths”).
The honest answer, as uncomfortable as it may be, is that most of us have a genuinely skewed sense of our own market value. Not because we are delusional, but because we rarely receive truly honest feedback. Performance reviews are notoriously sanitized. Colleagues are tactful. Managers tend to lead with affirmation or, in negative cases, offer the opposite of constructive criticism. The result is that most professionals walk around with any self-awareness that has never been seriously stress-tested.
This is where the current market becomes a useful, if brutal, calibration tool.
The project finance space, like most of the finance world, has cooled considerably from the hiring environment of 2021 and 2022. Roles that attracted forty applicants then may now attract 4X that amount. The candidate who might have received three competing offers two years ago is now waiting three months to hear back from a single firm if they hear back at all. This is not a commentary on ability. It is a commentary on supply, demand, and the very straightforward math of a tight labor market.
So, what do we do with that information?
The first thing is to resist the temptation to simply wait it out. Latrell waited. He sat out the 2004-05 season expecting the market to correct in his favor. It did not. The calls stopped coming. The opportunities, which had seemed endless, dried up faster than anyone (including him) could have anticipated. The professional gravity that keeps talented people employed operates on momentum, and momentum, once lost, is genuinely difficult to rebuild.
The practical implication here is that being or staying employed, even in a role you consider beneath your ceiling, is almost always preferable to the alternative. Staying in the game keeps your skills current, your network active, and your institutional knowledge compounding.
The elephant
Here we need to address the data-center hungry elephant in the room: artificial intelligence/large language models.
The conversation in most professional circles tends toward one of two poles. Either AI is coming for everyone’s job within the next five years, or it is an overhyped productivity toy that will find its lane and settle down. As is often the case with extreme opinions, both positions are probably wrong.
What AI has done, concretely and already, is compress the time required to produce a generally competent first draft of almost anything. A memo, a model, a market summary, a set of meeting notes. Tasks that used to take two hours now take twenty minutes. This is genuinely significant, but not necessarily a threat. The more immediate and practical question is how to use these tools more effectively and efficiently.
The most direct parallel in project finance and finance broadly is the introduction of Excel. The analysts who learned Excel early and learned it deeply did not lose their jobs to the software. In most cases, they are now in the C-suite. They became more productive but importantly they became more capable of using this tool to support their own thinking and analysis.
The lesson here is not particularly glamorous, but it is reliable. The underlying premium on clear thinking, sound judgment, and the ability to communicate a coherent, direct view of a complex situation has not changed. AI, in all the most current iterations, can help you draft faster. It cannot yet tell you whether the assumptions in your model are reasonable, whether the counterparty across the table is negotiating in good faith, or whether a deal that looks clean on paper is hiding structural problems that will surface eighteen months after close.
Those judgments still require a person and specifically a person with experience. They still require the kind of hard-won pattern recognition that only comes from having been in the room when things went wrong and having had to figure out why. They require someone who has a strong self-estimation of the limits of their abilities and is using the tools available to improve.
In conclusion
The professionals who will navigate this market well, whether they are trying to break in or trying to stay relevant, are the ones who resist the Sprewell temptation. They do not overestimate their own abilities or believe that they are insulated from change. They do not turn down the $21 million because they think something better is coming simply because something better came before. They are honest about where they are, stay curious about where the tools are going, and are humble enough to close the gap between the two.
That, at its core, is the whole game.
Webinar June 4 2026
If you want to hear more about working in project finance, we will be hosting a webinar on June 4 2026 on that topic. More information will be coming shortly!
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