u/founders_keepers

Lots saying Ethos is a scam and I admittedly was believing the nonsense here and on Reddit.

Then got my opportunity on same project I was on with Mercor (generalist) but 60% better pay.

I balanced my time assuming Mercor would pay me as they have and Ethos would find some way not to after all the free work.

But then, I got paid today.

Great Comms, bit scary to wait a month for the monthly pay cycles but they are legit!

Happy to also advise on onboarding process and how to get a step ahead.

Welcome to r/BlueCollarPros! To make the sub more lively, we at the mod team have decided to run a little giveaway. 

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i'm confused by the sleeve set up and can't find a straight answer on any of these funds websites.

context: exchange funds has to put ~20% in non-securitie for the 721 treatment, most funds use real estate

what I can't work out is these:

1. is the sleeve levered? if so at what ratio? my understanding is it's levered around 2x so effective equity exposure gets back nearly 100% but no one states this out in the open.
2. do the sleeve's economics accrue to fund NAV in full? or des the sponsor take a cut of it as well? if so, how much typically?
3. how is the sleeve marked between closings and what happens to its value at redemption? is it written down?
4. has anyone actually seen this disclosed in a PPM? which fund and what did they say?

Love to hear it if you gone through the dd on any of the usual funds or the new ones.

Let me preface this by saying that the main reason why I made this post is because I've observed just how outdated bluecollar business operations are.

I mean it's no surprise that they have a lot of expenses that nobody really questions, which ends up eating away all your money.

For one, you'll need insurance, legal help sometimes, you need equipment, you need people handling the back office, so you pay for them and move on. But a lot of these industries still operate on pricing models and processes that haven't changed much in years.

So yeah, I went down a rabbit hole and did some digging of my own after consulting with an HVAC service colleague, and what I found out is pretty interesting…

Most of these are going to be professional recommendations for newer services, tools, and a few simple changes that can make some of those expenses cheaper. If I were trying to cut costs without cutting corners, these are the 7 places I'd start:

1. Stop overpaying for commercial insurance

We all know that commercial insurance is obviously the one we're closest to, so we'll start here. Most traditional brokers make money through commissions tied to your premium, right? So the more expensive your insurance is, the more they can potentially make. That's a pretty “meh” incentive when their job is supposed to include helping you find the right coverage at a good price.

What I found was that there are already tons of amazing AI native services with flat fees that are thriving right now. Services like WithCoverage takes a different approach by using a flat-fee model instead. It combines AI with human insurance expertise to shop the market, analyze policies and coverage gaps, and handle a lot of the insurance work that normally gets scattered across emails, PDFs and spreadsheets.

They now protect $50B in revenue across 1,000+ businesses. The goal isn't necessarily to find the absolute cheapest policy either. Saving money upfront doesn't mean much if you find out after a claim that you weren't properly covered. It's more about getting the right coverage at a competitive price without the usual incentive of a broker earning more when your premiums go up.

Do your own research of course at the end of the day and see which services fit you the most in terms of budget and features.

2. Use flat-fee legal services for routine contracts

Up next, something we all dread to think about, legal bills… These are another set of expenses where the traditional pricing model can get painful very quickly. If you're running a contracting or construction business, you're probably going to deal with subcontractor agreements, MSAs, NDAs, vendor agreements, employment documents and plenty of other contracts. Not every one of those needs hours of expensive legal work.

General Legal is an interesting example of the same AI-native, flat-fee approach being applied to law. They're an actual law firm, but instead of charging traditional hourly rates, they charge a flat $500 per contract.

You know what you're going to pay before the work starts. Obviously, if someone is suing your company for $2 million, don't pick your lawyer based on whoever has the cheapest flat fee. There are situations where specialized legal expertise is absolutely worth paying for. But for routine business contracts, paying hundreds of dollars per hour can be overkill when newer alternatives can handle that work at a predictable price.

3. Put business spending on a card that helps control spending

Something to think about if your company is already spending thousands every month is that you should probably be getting something back from it. Materials, fuel, hotels, software, advertising, meals, travel and dozens of smaller expenses add up quickly. Ramp combines corporate cards with expense management, accounting automation and controls over what employees can actually spend.

The savings aren't just about card rewards. The bigger benefit is being able to see where your money is disappearing. Maybe you're paying for six software subscriptions nobody remembers signing up for. Maybe three employees are expensing the same service separately. Maybe a recurring charge increased six months ago and nobody noticed.

Those little expenses are easy to ignore individually. Across an entire company, they can become thousands of dollars of waste every year. Centralizing spending makes that stuff much harder to miss.

4. Automate the admin work before hiring another admin

A lot of growing blue collar businesses eventually hit the same awkward point. The owner can't keep answering every call, scheduling every job, sending every invoice and following up with every customer. But there might not actually be enough work to justify another full-time office employee yet. Before hiring someone purely to move information around, see how much of it can be automated. A lot of platforms can handle scheduling, quoting, invoicing, customer information and job tracking from one place.

Even basic automation can remove a surprising amount of repetitive work. A customer approves an estimate. The job gets scheduled. The crew gets the details. The customer gets a reminder. The job gets completed. An invoice goes out. The less of that process somebody has to manually copy between texts, calendars, spreadsheets and accounting software, the fewer admin hours you're paying for. Eventually you'll probably still need another person.

The goal isn't to eliminate employees. It's to make sure you're hiring someone because you actually need their judgment and experience, not because your current process requires someone to copy information between five different systems.

5. Rent expensive equipment until the math says you should own it

Buying equipment is tempting because renting can feel like throwing money away. But owning equipment that barely gets used can be even worse. Say you need a specialized machine for a handful of jobs each year. Buying it means you're taking on the purchase price or financing payment, plus maintenance, repairs, insurance, storage, transportation and depreciation.

Meanwhile, it might sit in the yard 25 days out of every month. Rental companies exist for exactly this reason. Rent the equipment while demand is inconsistent. Keep track of how often you're actually using it and how much those rentals are costing you.

Once you're renting the same thing constantly and the numbers clearly favor ownership, buy it. You're basically paying a little more per use in exchange for avoiding a much larger commitment before you know whether the equipment will actually make you money. A machine isn't an asset just because your company owns it. If it's sitting around unused while you're making payments on it, it's an expense.

6. Negotiate your supplier pricing instead of accepting the sticker price

If you're regularly buying lumber, electrical supplies, plumbing parts, safety equipment, uniforms, fuel, or other materials, don't treat the listed price like it's fixed. Once you're spending consistently with the same suppliers, ask about contractor pricing, volume discounts, bulk ordering, or better payment terms. Even a small percentage difference matters when you're spending tens or hundreds of thousands a year on materials.

Also, get competing quotes every once in a while. Being loyal to a supplier is fine, but paying 15% more for the exact same materials because you've been using the same guy for six years isn't loyalty. It's just expensive.

This fits the list way better because basically any blue-collar business buying materials or supplies can actually use it.

7. Make it easy for customers to pay you

One of the easiest ways to improve cash flow doesn't involve cutting an expense at all. Get paid faster. A surprising number of small businesses still finish the work, send an invoice and then basically wait. Three weeks later someone realizes the invoice hasn't been paid. Then somebody emails the customer. Then they call. Then the customer asks for the invoice again. You've already earned that money.

There's no reason collecting it should become another project. There are plenty of tools that let contractors send estimates and invoices, accept payments and keep basic customer paperwork together. Whatever system you use, automate as much as possible. Send the invoice immediately after the job. Give customers multiple ways to pay. Automatically remind them when an invoice is coming due. Follow up again when it's overdue. The easier you make paying, the less time your team spends chasing money that's already yours.

None of these ideas are particularly complicated. That's kind of the point. A lot of businesses look for one massive expense they can eliminate when the bigger opportunity might be ten smaller inefficiencies happening every single day. Insurance commissions, legal bills, unused subscriptions, unnecessary admin work, idle equipment, wasted drive time and slow payments all seem manageable individually. Add them together over 12 months and the number can get ugly pretty quickly.

My company's monthly bills for LLM API usage have been more than doubling over the past couple of quarters. There's no consistency to the madness and on paper everything is a MUST have, what's worse is month over month it's hard to tell if the rise will be permanent.

I need advice on enforcing spending caps. I've spoken to my engineering leads, and obviously they push back hard noting caps will have negative effects on output (we've yet to successfully measure LLM <> output btw).

I've been speaking to Ramp about Ramp Router, it's invite only right now and supposedly 30% off the top spend via smarter routing. My guess is it's done via complexity scoring against the prompt and routes it accordingly, i'll have to see we already use them for spend managemnt so this kind of fits the bill. I don't think this is the end-all-be-all solution, but it's better than strict cap.

Any thoughts on this is appreciated.

Hello r/ExperiencedFounders 👋 I'm James, co-founder and CEO of Ethos (askethos.com). Quick background:

Grew up in Hong Kong; got involved in the 2014 pro-democracy protests as a teenager, which is honestly where I first learned what it felt like to build something from nothing under pressure.

Studied Government at LSE, then went into strategy consulting at McKinsey, then growth/transformation work at SoftBank's Vision Fund, including stints on the WeWork and Arm turnarounds, and a UNICEF connectivity initiative.

In 2020 I left to start Mana, a mentorship platform that let anyone book calls with accomplished people. It grew fast #1 on Product Hunt, ~100K monthly users, but the business model never worked, the people who needed mentorship most could least afford to pay for it. In 2023, for personal financial reasons, I had to step away and wind the company down. That was a hard year and it was also the first time I was on the other side of the exact failure mode I'd watched at WeWork, believing in something past the point the data said I should.

The idea for Ethos came out of that failure. At McKinsey and SoftBank I'd watched firms pay $1,000–$2,000/hour for expert calls through a genuinely broken, manual process. Cold emails, no structure, no memory. My cofounder Daniel Mankowitz (ex-DeepMind, worked on Gemini and the AlphaDev sorting algorithm) and I started asking what if an AI agent could find the right expert, interview them properly, and turn that conversation into something reusable?

That became Ethos, we use a voice AI to interview experts in depth about their actual expertise, combine that with AI analysis of their real work product (papers, code, portfolios, podcasts), and match the resulting profile against what companies are actually looking for, not just job titles. Where we are today:

• $22.75M Series A led by Andreessen Horowitz, with General Catalyst (who also led our seed), XTX Markets, Evantic Capital, and Common Magic participating
• Clients include hedge funds, AI labs, and consultancies looking for real expertise on demand
• Roughly 35,000 new experts joining the platform every week
• Experts on Ethos earn an extra ~£4,500/month on average; our top 10% earn £7,000+/month
• Small team by design, we're staying compact on purpose rather than scaling headcount for its own sake

We also recently launched Ethos Investment Researcher, a research agent that can autonomously interview experts on a company or market and return a structured report Happy to go deep on:

• Consulting vs funding, what the two years at McKensey taught me and what it very clearly did not
• What it's like watching a $47B valuation evaporate from the inside, and what that does to how you evaluate your own conviction later
• What it's actually like to shut down a company you built for four years, and what changes the second time around
• What it's actually like to shut down a company you built for four years, and what changes the second time around
• Why voice and not text turned out to be the unlock for capturing real expertise
• Building an AI-native marketplace instead of a directory (and why that distinction matters)
• Raising a seed and Series A back to back in this market
• Why "the resume is a broken signal" is more true now than ever, and what we think should replace it
• Whether we're just building the infrastructure to make human expertise obsolete, faster
• Building a company in London instead of San Francisco

Not the right person to ask: Enterprise SaaS pricing motions, US visa/immigration questions, or anything requiring hardware/robotics expertise.

https://preview.redd.it/5221i305d1gh1.jpg?width=1587&format=pjpg&auto=webp&s=afd867c88409f328054f2537b2d55580fdb1bee2

Proof above. LinkedIn: https://www.linkedin.com/in/yfjameslo/

>On billing and fees, the bar said lawyers may charge for time ​spent reviewing, correcting and ​applying professional judgment to ⁠AI-generated work. But attorneys cannot bill for time that would have been spent if the technology never existed, it said, reflecting other opinions from ​state bars. “Efficiency does not justify inflated billing,” the guidance said.

>Law firm ​Jackson Lewis in ⁠a report on Alabama’s AI guidance said “a clear national trend has emerged: state bars are not banning AI — they are requiring lawyers to use it competently, responsibly, and under appropriate professional supervision.”

Alabama now says lawyers cannot charge clients for hours that AI saved. They can bill only for the time actually spent reviewing the work and applying legal judgment.

If your business model depends on pretending efficiency never happened, AI is not an advantage. It is an existential threat.

Doom Agent Arena, an open-source real-time game environment benchmark where AI agents control Doom players via MCP, and fight each other across multiple rounds. 

GPT-5.5 won with 66.7% draw-adjusted score, recorded 30 health pickups, more than twice the next-highest model, while its plans repeatedly used health routes to escape and recover. It also won 80.0% of rounds (4 of 5) in which it secured the shotgun.

Not sure how i feel about training AI to shoot things ;)

Key take aways:

• Firms that adopt AI grow headcount 10.2% over the two years following adoption, but these gains are entirely driven by high-intensity adopters. Low-intensity adopters see no statistically significant change.
• Entry-level headcount grew even faster. At the companies making the largest AI investments, entry-level headcount grew 12% over the two years following adoption.
• AI adoption and the associated gains are unevenly distributed. AI adopters are already larger, more engineering-intensive, more likely to be venture-backed, and faster-growing than non-adopters. These firms then grow faster upon adoption.

Extremely counter intuitive on the three findings.

Very interesting Forbes article published a few weeks ago and current hot topic in amongst companies I'm connected to.

AI companies have pushed "tokenmaxxing" to measure dev productivity by how many AI tokens they burned. Predictably, this was a financial disaster.

Uber reportedly blew its entire AI budget in four months, and one company accidentally torched $500 million in one month on uncapped employee Claude licenses.

Now, the pendulum is swinging to "valuemaxxing." Microsoft announced cutting unchecked subscriptions and demanding ROI. Imo days of treating expensive compute as a vanity metric are over and the focus is officially back on basic finance 101, removing redundancies, and strict usage caps.

How is has this conversations gone if when you spoke to your tech leaders? Whats the best way to think through this?