Location: Santa Monica, CA (Los Angeles)
Remote: Open to hybrid / remote. In SF often (lived there
8 years previously).
Willing to relocate: Yes, for the right team.
Technologies: Enterprise pre-sales & solutions
architecture, technical POCs, MEDDPICC, agentic
workflows. Strong with data — heavy quant/Excel
background from running a $20M lead-gen vertical. Build
side projects with Lovable and AI-assisted coding
(Claude Code). Ruby & Python fundamentals.
Résumé/CV: http://brantleybeaird.com
LinkedIn: https://linkedin.com/in/brantleybeaird
Email: first_initial + last-name at the big G one dot com
Engineer-MBA. Joined as #30 and spent 6 years at Segment (the customer data platform, acquired by Twilio for $3.2B) as a Solutions Architect and then Senior Sales Engineer. Drove $5M in annual bookings, guided 40+ enterprise accounts on data architecture, and was one of three people who launched the EMEA HQ in Dublin — scaling the SE team 4x and running 30+ technical workshops.
Since then I've been building, not just selling: a RAG pipeline over messy medical-billing documents (CPT codes, payer policies, claims guidelines) that cut research time ~50%, a steganographic image-watermarking app, and a handful of agentic workflows and full-stack tools with Claude Code and Lovable. I also ran investor relations and the financial model for an early-stage entertainment dining startup, and angel invest in AI/consumer (Limitless → Meta, Augie → JWX, Studdy YC S23, longevityhealth.me, etc).
The short version: a customer-facing and solutions engineer who can sit with a data team in the weeds, build the POC, and make the executive business case. That combination is rare, and it's exactly what good solutions and forward-deployed roles need.
Looking for: Solutions Engineer / Solutions Architect, Customer Success, an AI GTM/strategy role, Chief of Staff, or Forward Deployed Engineer. Seed–Series A preferred, open to all stages — strong bias toward AI-native teams.
Seeking: Chief of Staff, anything at the right VC firm, Sales Engineering, Solutions Architect, GTM, User Operations / Support Engineering ideally at a cool AI startup, but am flexible for the right team, opportunity, CEO, industry, etc.
Location: Los Angeles (Santa Monica)
Remote: In-person preferred, hybrid 3 days/wk in SF or nearby ok, open to remote.
Willing to relocate: Open to NYC or SF.
Technologies: Engineering + MBA + coding bootcamp.
Résumé/CV: 15 years in various technical, customer facing, and sales roles at startups and tech companies. Employee #30 at Segment; angel investor in various companies, managed $20m lead gen vertical at public online marketing company; started tutoring business in 20s.
Seeking: Chief of Staff, anything at the right VC firm, Sales Engineering, Solutions Architect, GTM, User Operations / Support Engineering ideally at a cool AI startup, but am flexible for the right team, opportunity, CEO, industry, etc.
Location: Los Angeles (Santa Monica)
Remote: In-person preferred, hybrid 3 days/wk in SF or nearby ok, open to remote.
Willing to relocate: Open to NYC or SF.
Technologies: Engineering + MBA + coding bootcamp.
Résumé/CV: 15 years in various technical, customer facing, and sales roles at startups and tech companies. Employee #30 at Segment; angel investor in various companies, managed $20m lead gen vertical at public online marketing company; tutoring business in 20s.
Seeking: Chief of Staff, anything at the right VC firm, Sales Engineering, Solutions Architect, or User Operations / Support Engineering ideally at a cool AI startup, but am flexible for the right team, opportunity, CEO, industry, etc.
Location: Los Angeles
Remote: In-person preferred, hybrid 3 days/wk in SF or nearby ok, open to remote.
Willing to relocate: NYC or SF okay.
Technologies: Engineering + MBA + coding bootcamp.
Résumé/CV: Early employee at Segment in various technical, sales, and customer facing roles; angel investor in various companies, managed $20m lead gen vertical at public online marketing company; tutoring business in 20s.
Don't get me wrong, unfettered capitalism has plenty of problems - eg tragedy of the commons, regulatory capture, effective monopolies, etc. That said, pricing things to maximize profits (given societal and economic constraints) still seems like the best route, especially in this case. How else could / should they price it?
I think one of the jobs of gov't is good regulation, which is hard. And once the rules have been set, maximizing profits within that box of regulation seems good, yea? Capitalism is reasonably good at allocating resources in many cases.
Do you all not think that companies should charge prices that maximize their profits (in the long run)? Typically, companies are trying to predict the price elasticity curve that yields the most profit via # units sold * price. That said, if you overcharge, that could be bad for the brand, turning off users in the short and longer term.
Another product like this for me is the Manta Sleep Pro Mask. It’s $80, but the best I’ve found, so I buy it anyways. I’m mildly annoyed and also feel like they’re taking advantage of me on price and will switch as soon as there’s an alternative at least as good for less…but when that happens, they’ll probably lower their price, which is what typically happens as sectors and products mature due to competition.
Profit maximization curves are interesting, and I think explain things like how convenience stores exist with much lower volume compared to grocery stores. Eg XYZ food costs 90 cents and the grocery store sells it for $1, yielding profit of 10% whereas a convenience store sells it for $1.50, just a 50% increase in price for the consumer (for the convenience), but the profit is 6x that for the grocery store, so they only need to sell approx 1/6 to make the same profit.
In the case of the author clock. If COGS is $50, profit is $150ish. If they sold for $100, they’d have to sell 3x as many to make the same profit. Given that it’s a niche product for readers (smaller population and typically more educated and wealthier), I think they care less about the price. Doesn’t seem that unreasonable to me.
I feel like the long term equilibrium of stuff like this is that in the not too distant future, anyone will be able to easily generate weird deepfake inappropriate porn / content for anyone. It seems unavoidable.
I might argue this could be good in that this sort of stuff will become so commonplace that it won't be a big deal and people will learn (be forced to shrug it off). Up until now-ish, the scarcity of celebrity nude leaks and revenge porn type stuff made it somewhat of a forbidden fruit. I like the idea of destigmatizing this sort of stuff so that it loses power.
That said, I'm sure there will be some casualties along the way. Eg vulnerable teens who are picked on by mean girls / boys, semi-celebrities / public figures who are targeted by online trolls, etc. I hope that the prevalence of this sort of stuff enlarges the conversation around this, increasing the reach of strategies to deal with this stuff psychologically, and significantly reduces it's impact.
I don't know many celebrities or politicians, but I suspect that after they see a few weird / porn related photos of themselves, they stop caring.
I would love a Wikipedia list article of games that have been solved computationally and but also games where humans can still beat computers / AI, discussing the challenges and context behinds wins / losses.
Engineer-MBA. Joined as #30 and spent 6 years at Segment (the customer data platform, acquired by Twilio for $3.2B) as a Solutions Architect and then Senior Sales Engineer. Drove $5M in annual bookings, guided 40+ enterprise accounts on data architecture, and was one of three people who launched the EMEA HQ in Dublin — scaling the SE team 4x and running 30+ technical workshops.
Since then I've been building, not just selling: a RAG pipeline over messy medical-billing documents (CPT codes, payer policies, claims guidelines) that cut research time ~50%, a steganographic image-watermarking app, and a handful of agentic workflows and full-stack tools with Claude Code and Lovable. I also ran investor relations and the financial model for an early-stage entertainment dining startup, and angel invest in AI/consumer (Limitless → Meta, Augie → JWX, Studdy YC S23, longevityhealth.me, etc).
The short version: a customer-facing and solutions engineer who can sit with a data team in the weeds, build the POC, and make the executive business case. That combination is rare, and it's exactly what good solutions and forward-deployed roles need.
Looking for: Solutions Engineer / Solutions Architect, Customer Success, an AI GTM/strategy role, Chief of Staff, or Forward Deployed Engineer. Seed–Series A preferred, open to all stages — strong bias toward AI-native teams.