Nick Petros

Building the future of work. The future is fractional. & for being a part of it!

[Nick Petros @NiP73]

What I'm working on.

Not all the way done, but can't wait for that, too important.

Also, this problem's way too big for our company to solve. Will need a lot of players, and hopefully you too.

[Nick Petros @NiP73]

Exactly. ATS systems filter instead of reading so the resume channel is dead. Agents make 10x the direct outreach possible but the human conversation still closes the deal.

[Nick Petros @NiP73]

Same pattern here. The research says experience compounds but the ATS and salary bands still screen it out for most. The 1 in 2 who go fractional sell the outcome and skip the broken filter.

[Nick Petros @NiP73]

Sharp breakdown. Blind screening removes names and backgrounds but the real decision still requires watching the person think through a live problem. Scripts fail on 1 in 2 of the edge cases.

[Nick Petros @NiP73]

Exactly. Senior marketing leadership was always a judgment problem not a 5 day a week presence problem. Two days of direction with the network running the rest is the real model.

[Nick Petros @NiP73]

Same pattern here. Everyone looks great on paper, but 1 real problem walked through live exposes who can actually think. The paper is noise now, the real-time judgment is the only signal that holds.

[Nick Petros @NiP73]

Exactly. When resumes are 100 percent AI-generated, the document carries zero signal, not insight. The only real test is a live problem the candidate has to steer in front of you, not a take-home.

[Nick Petros @NiP73]

Sharp breakdown. 10 years ago that level was reachable solo but most operators hit the cap without a team. The automation now lets one person reach the same scale while staying lean.

[Nick Petros @NiP73]

Exactly. Solo caps you at what 1 person can hold. Collaborating with a small bench lets you take the bigger engagements because income is a network problem not a time problem.

[@jason @Jason]

Tokens will get 90% cheaper every year as models improve and $10k desktop workstations from @dell and @apple, running open source models, drive tokens to “essentially free”

Token costs will be looked at like storage and bandwidth costs in a couple of years — which is to say you won’t think about them much.

[Nick Petros @NiP73]

Same pattern here. A 6 person team now handles the volume of 15 but only if the judgment layer stays human and tight. Otherwise the multiplier just ships the wrong work faster.

[Nick Petros @NiP73]

Judgement > intelligence.

[Maurizio @themgmtconsult]

If you think a $300K corporate salary is payment for 40 hours of weekly labor, I've got news for you...

There is a persistent cynical narrative that large enterprises are bloated engines of inefficiency, filled with overpaid professionals who spend their days looking at slides and doing "nothing."

I mean, it's a comforting myth for critics, but I think it fundamentally misunderstands modern knowledge work.

That $300K salary (or $400K, or $500K) isn't a reward for linear effort but an option premium on high-leverage thinking.

We are still haunted by the ghost of the assembly line, ie, the outdated idea that compensation must directly correlate with time spent + physical output.

In the factory world, if you leave your station, production stops, but in the knowledge economy, value is almost totally decoupled from time.

Folks... An enterprise paying a senior leader or specialist $25K a month is not buying 160 hours of typing, they are buying *insurance* against catastrophic errors and positioning themselves for asymmetric upside.

I'll try to make it tangible with an example...

Consider a complex matrix organization busy with a $40M product migration. In this environment, the value distribution of a worker's is heavily spiked.

Most days look like nothing... alignment meetings, reading documentation, maintaining steady state. Yes, to an outsider, it looks like "doing nothing."

But then a critical day arrives. A vendor fails, a timeline slips, a crossroads appears, whatever... If that $300K professional has the institutional memory and capability to make just 4 or 5 correct decisions during those critical moments, the ROI is staggering! A single right call can avert a $5M problem.

Suddenly, that $300K salary doesn't look like bloat but, to me, seems like the cheapest asset on the p&l.

These days we are bombarded by tech CEOs promising fully autonomous, AI-driven organizations and I keep saying these pitches miss the entire point of how complex enterprises actually move.

Data computation can be outsourced to an LLM but going through the decision fabric of an enterprise cannot. You need people for:

> Knowing *how* to build consensus across disconnected departments with competing incentives;

> Understanding the unspoken history of why past projects failed, and how to position a new initiative so it doesn't trigger corporate antibodies;

> When a multi-million-dollar decision goes sideways, an algorithm cannot stand before a board of directors or regulators and take ownership of the corrective action.

An AI can give you a pristine strategic framework with nice and difficult sounding words, but it cannot navigate the human matrix required to execute it.

The ability to be effective inside a complex enterprise is a rare AND expensive skillset precisely because it cannot be automated or easily replicated.

My point is you aren't paying for the 9-to-5 "grind", but more for the readiness.

Like an elite surgeon or an expert technician, you pay for the decades of accumulated knowledge that allow them to fix a crisis in 5 minutes, not the 5 minutes itself....

Leverage, not labor.

[Nick Petros @NiP73]

Exactly. A one person business hits 90 percent margins but the ceiling used to be what one person could execute alone. Agents remove that limit.

[Nick Petros @NiP73]

Exactly. A model can produce 10 working versions of the solution but the signal is how the candidate steers the agent and reads the output.

[Nick Petros @NiP73]

Same pattern here. A great resume is not the signal, watching someone solve 1 real problem out loud is. The document shows the past, but 15 minutes of live judgment shows the next 90 days.

[Nick Petros @NiP73]

Exactly. The risk is not being replaced by AI, it is the operator next to you running 10 agents while you run none. Judgment plus speed beats judgment alone, and that gap compounds every quarter.

[Nick Petros @NiP73]

Exactly. Your network becomes your net worth because 90 percent of the roles come from relationships not job boards. With agents handling execution you stay in the room building the next connection instead of disappearing into the work.

[Nick Petros @NiP73]

Honestly the layer split is the useful part. Uber cut 23 percent of HR at record revenue, and the operational layer, screening, onboarding, payroll, is what AI absorbs first. The judgment layer does not shrink, it grows. Which layer are you building toward?

[Julia McCoy @JuliaEMcCoy]

The Industrial Revolution made people act like machines.

The AI Revolution lets machines act like machines.

One of these is liberation.

[Nick Petros @NiP73]

Exactly. The strongest teams are built around capability, not titles, so skill density beats headcount. Hire for the mix of technical depth and judgment that adapts as fast as the tech. The title tells the past, the skills tell the next 90 days. What are you really assessing for?

[Nick Petros @NiP73]

This reframes hiring. The unit is not the person now, it is the task, so headcount becomes capital allocation: intern, expert, small model, frontier model, task by task. Most firms still buy all your hours to get one good Tuesday. Which tasks consume the intelligence you pay for?