Forward Deployed Engineer | AI Transformation | Agentic Systems | Previously at frontier labs
Remote: Yes
Willing to relocate: No
CV: Ask
Email: d.dev.nyc+hnjobs@gmail.com
I help organizations evolve into AI-native businesses by redesigning processes, decision-making, and operating models around LLMs, agentic systems, and intelligent automation. I enjoy partnering with leadership to identify high-leverage opportunities, define AI strategy, and translate ambitious transformation goals into processes that drive organization-wide adoption.
My focus is applying frontier AI capabilities—LLMs, agents, and intelligent automation—to transform how companies operate: redesigning business processes, augmenting teams, automating knowledge work, and building agentic workflows that create measurable business impact.
I specialize in bridging the gap between business strategy and technical execution. I work with executives, operators, and technical teams to identify high-value AI opportunities, translate ambiguous problems into scalable solutions, rapidly prototype systems, and drive adoption across teams.
My expertise includes enterprise agentic workflows, AI-native operating models, AI orchestration, workflow automation, autonomous business processes, and production AI deployment.
I'm particularly interested in helping companies rethink how work gets done — building AI-first workflows and augmenting decision-making where humans and AI collaborate effectively. I enjoy working across strategy and implementation, taking ideas from discovery through deployment, adoption, and continuous improvement.
Looking for Forward Deployed Engineering opportunities where technical excellence, customer partnership, and AI-driven organizational transformation are equally important. If that's the transformation your company needs, reach out via email.
Forward Deployed Engineer | AI Transformation | Agentic Systems | Previously at frontier labs
Location: EU/US
Remote: Yes
Willing to relocate: No
CV: Ask
Email: d.dev.nyc+hnjobs@gmail.com
I help organizations evolve into AI-native businesses by redesigning processes, decision-making, and operating models around LLMs, agentic systems, and intelligent automation. I enjoy partnering with leadership to identify high-leverage opportunities, define AI strategy, and translate ambitious transformation goals into processes that drive organization-wide adoption.
My focus is applying frontier AI capabilities—LLMs, agents, and intelligent automation—to transform how companies operate: redesigning business processes, augmenting teams, automating knowledge work, and building agentic workflows that create measurable business impact.
I specialize in bridging the gap between business strategy and technical execution. I work with executives, operators, and technical teams to identify high-value AI opportunities, translate ambiguous problems into scalable solutions, rapidly prototype systems, and drive adoption across teams.
My expertise includes enterprise agentic workflows, AI-native operating models, AI orchestration, workflow automation, autonomous business processes, and production AI deployment.
I'm particularly interested in helping companies rethink how work gets done — building AI-first workflows and augmenting decision-making where humans and AI collaborate effectively. I enjoy working across strategy and implementation, taking ideas from discovery through deployment, adoption, and continuous improvement.
Looking for Forward Deployed Engineering opportunities where technical excellence, customer partnership, and AI-driven organizational transformation are equally important. If that's the transformation your company needs, reach out via email.
The contribution of Excel, the most popular programming environment in the world, is undoubtable - therefore, not only has Excel accomplished something (popularize programming among non-programmers) but it's also easily measurable (it has done so more than any other technology in existence). It _is_ a genuine contribution to the world, by the tool itself, not just by what people use the tool for.
So, I disagree with this line of criticism - I think you very well can do those things.
I don't disagree here. I just pointed out that above commenter seems to dispute the author without having read the article in full. Turns out, some of us are just bad at communication :)
It's best not to think of BigCentralThing as your "partner". They're just the big central thing that lists things. They have their own motivations that don't matter to you, so long as they continue to list the things.
I used YouTube as an example earlier. OSM is a good one too. Neither needs to care about you. They only need to care about their own job, which is knowing about their list of things (videos, roads, electronic part numbers, etc.). So long as they continue to do that, and have an easy way to tell them about the things they do care about, you're good.
They're already "putting in the work". Because it's their work to keep the list. That's all they do.
They might not have known it was SA specifically. That being said, they definitely knew a large fund with leverage was buying these stocks. The mechanism here (and I'm not an expert) is:
1. SA wants to buy stock with leverage. You do that through a major bank via total return swaps. Essentially, SA pays X% of the value on $100 of stock (for 4x leverage you'd pay $25) plus an ongoing financing fee (call it 5% a year), then you get the return/loss on that $100 of stock. SA was in these agreements with JPMorgan and Goldman Sachs.
2. The bank, because they don't want to actually hold that risk, goes out and buys $100 of stock.
3. Citadel and others see JPMorgan buying lots and lots of this stock. That's confusing, because normally JPMorgan wouldn't be making a huge directional bet on a stock. They deduce that a large fund is buying the stock.
4. Citadel starts widening their spread (the difference between what they'll buy a stock for and what they'll sell it for). They hedge some of this as best they can, or temporarily live with the risk.
5. SA, the highly leveraged fund buying volatile stocks, inevitably blows up because volatile stocks swing around in price. A dip causes margin calls.
6. JPMorgan or Goldman need to sell the stock fast, because SA is close to dipping below their required margin (i.e. SA paid $25 for $100 in stock exposure, the stock drops to $90, JPMorgan asks for more money because the stock went down by too much).
7. Citadel offers to buy all of the stock from JPMorgan. Because they're doing it in one big block, JPMorgan doesn't lose money selling on the open market (once you start selling, each successive sale is for less money because there are more people selling than buying). Citadel is compensated for this by getting a discount to the asset value (the stock is worth $90, Citadel gets to buy it for $81).
So Citadel didn't do anything to "set up" SA. But because they're hyper-aware of market dynamics, they would have known that someone is going to need to sell stock if the market takes a turn on these names.
I generally agree with you but given your comments, you might enjoy some additional details... Or please challenge me if you think I am wrong.
I've been paying for order-level data feeds on stocks and one thing you'll find is that a lot of the 'sensitive' trades will be anonymized or broken down in different ways to obfuscate who is trading. Citadel would still be able to see there's a surprising level of interest in a certain stock but might not be able to deduce it's one actor. A broker working for SA should know they need to do this, as it helps the broker do better via commissions, etc. too.
My understanding is that Citadel negotiated directly with SA to buy the book, so the final trades were likely taking place outside of the formal market feeds.
the last step, #7, is that fully automated or is this humans calling humans? I imagine everything before then is quite automated, and are thus happening very quickly, so I'm curious if the last piece possible being manual has the potential to blow the whole thing up by being too slow.
It's humans from other banks/funds bidding on the block of stock. As far as timing, for this situation it's basically overnight for regulatory and price reasons. Regulatory because there are legal margin requirements for levered positions and you can't handle the price going much lower, and price because if you had to sell this on the open market you'd keep selling shares for less and less.
So JPMorgan/Goldman prepare all the info on the book and start calling institutional investors after the market closes. The funds and banks prepare bids, there's some negotiation, and the block is finalized before trading opens the next day.
Speed does matter, but you're only calling investors you know "can" close the deal (i.e. they'll have enough capital to buy it all that day/night). So it's more of a price question than a speed one at that point?
And really, nobody wants the downward spiral of a fire sale in the tech sector. Someone will make money on that chaos, but it's a lot of risk when you can lock in a discount with the block trade.
One thing that sticks in my mind was that the system call API was well-designed (by Frank Holsworth). Everything involved getting or setting tables (structures). The documentation for this was really quite good.
Some people are confused as to what this is, so I thought I'd bring up this sentence from the Readme:
> PISIGuard runs entirely in your browser. It spots names, email addresses, phone numbers, credit card numbers, passwords, API keys, and more, replaces them with safe placeholders, then puts the real values back into the AI’s reply. From your point of view, it’s mostly invisible; from the AI’s point of view, the sensitive stuff was never there.
I suggest putting it at the top of the readme!
I think it's a very smart system, and could easily extend beyond AI use. Please continue working on it!
I can't find it sadly, but somebody made an 80s style industrial control panel for a SQL server deployment, with all the clicky radio buttons and 7-segment displays you could wish for.
ACHTUNG!
ALLES TURISTEN UND NONTEKNISCHEN LOOKENSPEEPERS!
DAS KOMPUTERMASCHINE IST NICHT FÜR DER GEFINGERPOKEN UND MITTENGRABEN!
ODERWISE IST EASY TO SCHNAPPEN DER SPRINGENWERK, BLOWENFUSEN UND
POPPENCORKEN MIT SPITZENSPARKEN. IST NICHT FÜR GEWERKEN BEI DUMMKOPFEN.
DER RUBBERNECKEN SIGHTSEEREN KEEPEN DAS COTTONPICKEN HÄNDER IN DAS
POCKETS MUSS. ZO RELAXEN UND WATSCHEN DER BLINKENLICHTEN.
Remote: Yes
Willing to relocate: No
CV: Ask
Email: d.dev.nyc+hnjobs@gmail.com
I help organizations evolve into AI-native businesses by redesigning processes, decision-making, and operating models around LLMs, agentic systems, and intelligent automation. I enjoy partnering with leadership to identify high-leverage opportunities, define AI strategy, and translate ambitious transformation goals into processes that drive organization-wide adoption.
My focus is applying frontier AI capabilities—LLMs, agents, and intelligent automation—to transform how companies operate: redesigning business processes, augmenting teams, automating knowledge work, and building agentic workflows that create measurable business impact.
I specialize in bridging the gap between business strategy and technical execution. I work with executives, operators, and technical teams to identify high-value AI opportunities, translate ambiguous problems into scalable solutions, rapidly prototype systems, and drive adoption across teams.
My expertise includes enterprise agentic workflows, AI-native operating models, AI orchestration, workflow automation, autonomous business processes, and production AI deployment.
I'm particularly interested in helping companies rethink how work gets done — building AI-first workflows and augmenting decision-making where humans and AI collaborate effectively. I enjoy working across strategy and implementation, taking ideas from discovery through deployment, adoption, and continuous improvement.
Looking for Forward Deployed Engineering opportunities where technical excellence, customer partnership, and AI-driven organizational transformation are equally important. If that's the transformation your company needs, reach out via email.