API

North_Teacher_7522

im the intermediary for now! but this is intentional. i actually have alpaca API keys that i could use on Julius but they have their own proprietary financial data sources on there too so it's not needed while im only running this on a daily cadence. does alpaca also allow your automation build and run python models in a sandboxed env? just curious as i haven't explored their automations

etaoin314

Just curious if you are the intermediary or if it is all automatic? If you want to automate it alpaca is a much better brokerage since they give you a friendly API to tap into.

Nut_Negative

" If you’ve been curious about using AI with your trading workflow, Interactive Brokers just made it a lot easier. There’s no coding, no API setup, and no extra accounts required. Instead, Interactive Broker’s clients can now connect directly to Claude AI and ChatGPT through a certified connector—and be up and running in minutes. " AI going to self fund

Cultural-Tell5620

been wanting to mess around with automated trading for while too, might actually give this a shot if the API access isn't completely garbage

SangerGRBY

This sounds like a web-scraping automation + dashboarding / analytics project. Great for internal automation. If i were you i would design something like this: \[Webscraping layer\] (Platform agnostic, returns a standardized .csv) --> \[data processing layer\] (Parse, filter, clean, process .csv; keep only what you want) --> \[Dashboard + Analytics Layer\] (Build custom dashboard charts + LLM analysis of scraped content). For dashboards just go with the standard powerbi / Grafana / google sheets / excel / quicksight. I wouldn't spend too much time custom building a dashboarding tool. For your LLM analysis if you really want to keep your cost low without a quality hit, try using Deepseek API. Note: For a large enterprise there might be penalties / legal repercussions if you scrape on your own without using official APIs, please check with legal. I THINK as long as your volume isnt ridiculously high, you can most likely get away with a custom scraper / paid scraping service.

DatItalianBoy

For the social reporting side, we were using alot Of thirdparty reporting tools that use API pulls from set social media platforms. These were very expensive and very limited. Now I am building a dashboard where a social media manager, could drop an CVS export from lets say Meta. And creat an whole dashboard with calculations and graphs of our posted content per platform/client. It even has an Claude Haiku model running in the background that could generate a first draft of an anlysis for set Social media manager. This job took at least 1,5 days before, now 30 minutes. For the ball park tool we currently use Google sheets. Which is fine, but after building a tool for 2 days you could already see the many many upsides of this.

zjz

It is pretty enjoyable. I don't miss googling every error. I find if you know what you're asking for and how you want it done they can do well. My prompts tend to be short essays and include a lot of API docs. You can't really outsource all the thinking. They're great for refactoring too. I like claude the most, it seems to reliably be the least retarded. Any claude + IDE integration will do the job tbh.

abittooambitious

60% margin. If you’re talking API then the point is moot because you can easily find ones that aren’t training on your data for Chinese models. I’m not in cybersecurity so I can’t validate your statement about data sharing: though people in r/privacy seem to disagree: https://www.reddit.com/r/privacy/comments/pblidz/multiple\_services\_from\_same\_provider\_or\_one/. Either case because it’s so drilled into us that Chinese=bad, I just don’t send any sensitive information through Chinese servers and I bet this isn’t only my modus operandi. But out of 100 request only about a handful are sensitive in my experience, so I’m good with using Chinese model for simple development (majority), self serve or private API for any enterprise work. At this point western companies know much more about anyone who uses a Google account than their family members. My point is, if we’re being objective, the open source models (from any countries) are the way to go, and ones I’ll cheer for because the alternative is to be at the mercy of the handful of western companies who are all circular financing and act in concert and lobbying (but really controlling) the government.

FullOf_Bad_Ideas

> You’re telling me the free and lowest monthly paid tier they don’t train in our data by default? No. I'm talking about pay-per-request API providers, not monthly subscriptions. >The question is how often every 100 request would people want to pay that 60% mark up when given an alternative, when all things are equal, with data privacy assumed. I don't understand what you mean. Where's the 60% markup? DeepSeek chinese API is effectively ~100x cheaper than Claude Opus API for the same number of tokens due to cache read. US-provider DeepSeek model is about ~10x cheaper than Claude Opus for the same number of tokens. >The better strategy may be to spread out your data so no one company has it all. The amount of data Google, meta, (Palantir anyone?) ect. has on you makes these Chinese models look like saints. That's a bad idea - now your sensitive AWS/Github tokens are spread through every provider. It's like buying things online from 100 various websites - one of them will steal/leak your credit card info. It's better to stick to one reputable one.

ChloroVstheWorld

Do I have over my brokerage keys to the dubious vibe coded API

InitiativeGlum2507

Imagine handing over your brokerage credentials to a retarded WSB API

zjz

Yeah I don't blame him. Nobody likes change they didn't initiate. I probably wouldn't even have remade the app if I wasnt forced to by the old one being deprecated by reddit. I know it probably doesn't assuage the creepy bonzi buddy installer feeling but they did a six figure audit on the API company and reddit's engineers have been all over every line of this project. It's pretty solid. Runs on reddit's servers, HMAC's your userId so even the API doesnt know what your username is, etc.

FullOf_Bad_Ideas

Deepseek API, the cheap one, trains on your prompts and CCP will have access to all of that data permanently. I don't see how this would pass any legal checks in enterprises. Deepseek models are open weight, so US companies provide API too, but it's much more expensive, especially cache read which is the main deepseek api price advantage that makes agentic coding cheap. US companies have been increasing API pricing the last few months, so far I don't think there's been much resistance to it.

KiltyPimms

I'm not asking "do you know what the technology does" -- I'm more asking "do you know much your fancier coding asks are costing you in compute/API $$ charges?" That compute gets pretty spicy when you ask for complex things. You *do* know how much trouble Anthropic has been having keeping up with demand, yeah?

Mminas

You do realize that the chatbots and every other GenAI API of each brand are powdered by the same models right? In any case, you can read Standford's AI index report to understand that Anthropic does not have any actual technological edge over the competition.

Still_Theory179

The API pricing is at good margins and where most of the explosive revenue growth is coming from. 

KiltyPimms

Out of curiosity, how much coding have you done with SOTA AI and a solid harness? A lot? Not much? How much do you know about the API costs there?

zedfan

Not everyone will signup for API access. I am sure google and microsoft (bing) has scraped majority of the data already.

TomatoSpecialist6879

I remember a few ex employees said the banned subs are actually still archived for legal purposes, so if AI companies are scraping data through the API then they probably can access it. Microsoft's Tay got turned into an internet hate machine after just 4 hrs of user fed tweet prompt training, imagine what Claude and ChatGPT can do after just a few seconds of reading data from FatPeopleHate

theb0tman

Been tried. Platforms are hella sticky. Look how many people still use x and it's toxic AF with many alternatives. New digg failed. Facebooks new pages thing will fail. Reddit has been crying doom for over a decade. Oh, the closing of the reddit API. Remember how everyone was gonna quit? Bitch plz y'all got nowhere to go.

6e6967676572730a

That and the percentage of non verified accounts/sock puppet usage. That reason alone excluding bot accounts is probably the reason why 40m was the negotiated amount for the API access.

Astronaut-Proof

Why the fuck would they need the API when they can literally just browse Reddit for free and train models as they have been for the past 5 years? Fucking puts it is.

howtoloveadaisy

I’d argue that Anthropic is using enterprise sales as the shovel to dig their actual moat. I’ll say that Anthropic’s actual moat is deep workflow integration thru Claude/Cowork. Yes, most companies use multiple AI platforms but other AI companies aren’t being integrated as deeply. Claude is actually becoming a vital piece of many company's core infrastructure Anthropic knows what they’re doing by attracting enterprises to their platform at heavily discounted rates. These discounts will last until late 2027 when Anthropic will pull the classic SaaS lever. They’ll slowly increase the base seat cost, adding multipliers for specialized agentic capabilities, and tapering off the discounts for API. Companies will have no choice but to pay the price hike bc of how deeply integrated they are

howtoloveadaisy

I’d argue that Anthropic is using enterprise sales as the shovel to dig their actual moat. I’ll say that Anthropic’s actual moat is deep workflow integration thru Claude/Cowork. Yes, most companies use multiple AI platforms but other AI companies aren’t being integrated as deeply. Claude is actually becoming a vital piece of many company's core infrastructure Anthropic knows what they’re doing by attracting enterprises to their platform at heavily discounted rates. These discounts will last until late 2027 when Anthropic will pull the classic SaaS lever. They’ll slowly increase the base seat cost, adding multipliers for specialized agentic capabilities, and tapering off the discounts for API. Companies will have no choice but to pay the price hike bc of how deeply integrated they are

Connect-West-4918

The real play is when those API contracts come up for renewal and reddit realizes they can charge 10x more Companies already trained their base models but they're gonna need that fresh data pipeline forever, especially for real-time stuff. Reddit basically has monopoly on authentic human conversation data at scale

biglebowskidude

RDDT — Reddit Inc. Senior Analyst Breakdown Yes, posting a Reddit analysis on Reddit. You're welcome. $173.45 today, down 39% from 52-week highs. The real business: 80-85% advertising revenue (cyclical risk) 15-20% API/data licensing (the interesting part) Newly profitable in 2024 after years of losses Bull case: Reddit data is uniquely valuable for AI training — you can't replicate 20 years of human discussion API licensing to AI companies could be a massive recurring revenue stream 500-600M MAU with pseudonymous communities nobody else has Low capex, improving operating leverage Bear case: Ad-dependent business in a TikTok/Meta/YouTube world API licensing concentration risk — if Google or OpenAI walks, it hurts badly Content moderation at scale on a pseudonymous platform is nearly impossible Valuation still not cheap despite 39% drawdown Verdict: The AI data licensing angle is genuinely interesting and underappreciated. The advertising business is meh. You're essentially betting on Reddit becoming the premium data source for AI training. Full breakdown at norrisai.us

biglebowskidude

RDDT — Reddit Inc. Senior Analyst Breakdown Yes, posting a Reddit analysis on Reddit. You're welcome. $173.45 today, down 39% from 52-week highs. The real business: 80-85% advertising revenue (cyclical risk) 15-20% API/data licensing (the interesting part) Newly profitable in 2024 after years of losses Bull case: Reddit data is uniquely valuable for AI training — you can't replicate 20 years of human discussion API licensing to AI companies could be a massive recurring revenue stream 500-600M MAU with pseudonymous communities nobody else has Low capex, improving operating leverage Bear case: Ad-dependent business in a TikTok/Meta/YouTube world API licensing concentration risk — if Google or OpenAI walks, it hurts badly Content moderation at scale on a pseudonymous platform is nearly impossible Valuation still not cheap despite 39% drawdown Verdict: The AI data licensing angle is genuinely interesting and underappreciated. The advertising business is meh. You're essentially betting on Reddit becoming the premium data source for AI training. Full breakdown at norrisai.us

biglebowskidude

API issue will be good in a few minutes

biglebowskidude

"Hey everyone getting a lot of requests, love it! Running into a brief API limit issue, should be back up in a few minutes. Will reply to everyone shortly with their analysis!"

Mindless_Park_2574

And then gets shocked by the API bill

AlsoInteresting

There was no mentioning of opening API to LLM engines though.

nxs_sss

I built my own app with Claude as well. Can't share screens here, but DM if interested. I wouldn't mind adding a few people to it to help improve it. Right now it is manual entry because I only want to track options selling, not shares held or options buying. I do pull data from Finhub API, but looking at switching to something more robust in the near future. I'll also be looking at adding a Snaptrade connection in near future so it can read and import (import only) trades from your broker to the app.

Lehsyrus

I'm an swe and man, I completely agree with your assessment. The few companies I've worked with that are "all in" on AI are spending *millions* a month to replace a handful of miscellaneous workers that made under 100k. And they just can't do the dev work the suits want. Trying to have it build an app from scratch is a nightmare with the amount of repeated sections and security holes. Plaintext passwords and API keys are everywhere. It's just not a good worker replacement, it's a great tool like a calculator but that's it.

xRedStaRx

What do you mean API calls though codex CLI, it depends on your subscription. I have 2x $200 GPT pro subscriptions by the way and its not enough.

Singularity-42

I don't think it's that simple. There's always the floor of the Chinese OSS models. They're getting pretty good. The API inference on them is dirt cheap. Now, people and companies are willing to pay for better performance, up to a limit - they're not going to pay 100 times as much.

MaybeLiterally

You're definitely right, but the question is more along the lines of AI computers that could run local models better. I absolutely don't expect an GPT-5.5, or Claude level LLM on my machine, but what I do need is the ability to test agentic communication, tool calling, how well it even activates, MCP and A2A, and things like that. Just like I'm not expecting to process billions of rows of data for a database on my machine, I do want to validate those things also. When it looks good on my machine I can flip the API endpoint and test on better models in the cloud, but at least I've saved some money on the initial parts first.

ShittyUsernane1222

Anthropic, OpenAI and xAI have no moat. there are 30x cheaper open weight AI models which are good enough for business uses and easier to scale than token-guzzling, API rate limiting and ultra-expensive closed source AI models.

Blarghnog

1. That is just straight-up wrong. Vanguard, Instacart, Walmart, Samsung, McKinsey, IBM, and Microsoft all heavily deploy open-source AI. Major enterprises use open-source precisely because they can’t risk throwing proprietary data or regulated client info into a third-party, commercial black box. They run it inside their own secure, isolated cloud perimeters where they actually control the data. 2. No shit it takes compute. Nobody said it runs on magic. But you’re completely missing how enterprise unit economics work. With open source, you can utilize quantization and right-sizing to shrink a model's footprint so it runs on a fraction of the hardware. A fine-tuned 8B model handling a specific task like billing routing is exponentially cheaper than bleeding money on variable per-token fees to a proprietary API. Plus, dedicated leased hardware turns variable costs into a flat, predictable operational expense at scale. There is a massive difference between having an actual conversation and whatever this clueless, aggressive nonsense is.   Your entire communication style is just talking out of your ass to cover for a total lack of actual insight.

_ii_

Not with this generation of N1X chips while M5 MacBooks exist and M5 Mac Minis are on the horizon. Mac users will stay with Mac. N1X is not attractive enough for them to switch. The new Nvidia laptops are targeting the ultra high-end which is dominated by Macs and gaming laptops. The gaming angle is possible but it depends on game availability and performance. Demands for AI PCs depends on how useful local small models are. Currently they’re not useful enough for average users. It’s fun to pay with, but real work requires API calls to larger models. In a year or two, between faster computers and model improvements, I would expect AI PCs to become useful enough that new computers buyers would want AI capabilities in their new machines. When that happens, it will be Nvidia vs Apple.

bandit_spirit

Schwab’s API will give you options chains

andh01

Quant Data just released their API! It has been fantastic, would strongly recommend. MCP works flawlessly and it has some great endpoints & no daily quota

redditissocoolyoyo

I built my own little application using LLM and scraping tools and finnhub API. I have no idea if it's giving me better plays or not. But it's aggregating all the information I need into one place which is helpful. I call it the tax harvest app

YourPapiPanda

Quant Data. They provide Greek exposure and net premium flows. They also just released an API feature, which I have connected to Claude.

Longjumping_Wave_341

Their leadership just sucks, I guess many people would say the same about SpaceX though to be fair. Basically everything centered around Claude code is a shitshow. They don’t have great engineering talent, their talent comes from the scientists working on the math behind the models, which are very strong. But it took them months to solve flickering and framerate issues in Claude code, because the codebase was such a mess. They had to bring on the whole bun team to solve it for them. They aren’t transparent about their tooling at all to developers. They block specific keywords like Opencode and Clawdbot, so if you’re working on a codebase that even mentions that in the history or something and Claude picks up on it, it can start charging you API credits which are far more expensive than the subscriptions. For example https://xcancel.com/theo/status/2049645973350363168. They released a new announcement recently that they advertised as getting more credits, when really it was disabling the feature that saved you money. Etc. just very shady practices. That being said, they can get away with all of this because their product is the best. They have a very strong model, it’s just everything surrounding that is a shitshow

FullOf_Bad_Ideas

>Do you think it will drastically change how some companies approach AI or make self hosting models like Llama more popular? Nobody is really self-hosting Llama, that series is dead. At best, if you self host Llama, you get close to API price of the model, with less flexibility. >How do you think it will affect the demand and revenues for big AI? Once it hits consumer subscriptions too, suddenly there will be enough GPUs to satisfy demand and demand will move to cheaper models and better providers that offer proper savings on KV cache reuse.

suicidaleggroll

AI is useful, yes, but the subscription/API prices right now are artificially low by a *huge* margin. All these AI companies are currently hemorrhaging money. Once a ChatGPT subscription costs $1k/mo, are you really going to find it that useful? When an AI coding assistant costs more than an *actual* entry-level programmer who can learn, grow, and get better at their job over time, it's not a cost-cutting tool anymore.

Jealous_Bookkeeper20

The inertia of legacy architecture is a real moat, but the risk to PATH isn't a massive rip-and-replace project overnight. It is budget attrition. When companies look to automate new workflows, they are increasingly building them on greenfield API-first setups rather than expanding legacy RPA licenses. PATH has to run hard just to stay in place because their growth relies on selling more capacity to existing accounts. If those accounts start routing new automation budgets to cloud-native platforms, the valuation multiple has to adjust downward. Do you think their platform expansion features like document processing are enough to offset that budget shift?

think_up

And no API provider is going to process one-off micro-penny transactions like that. They’re going to demand a retainer or a credit card they can bill at the end of each day. Again, you’re too in the weeds for imaginative scenarios that just don’t need to be that complicated.

hindermore

What you are talking about is human or corporate delegated funding sources that the AI are allowed to use within certain limits. You fund some account with a credit card and the AI uses from that account when it needs to make a transaction. What I am talking about are AI Agents that are provided with funding sources that become completely controlled and managed autonomously within their own ecosystem. Let's say you have an agent that needs to transact with 50 other agents to perform a specific task, one gets weather data from a remote sensor, one queries a database with historical data to build a statistical model, one makes an API request to post the data to an external source, etc. The AI is not going to make 50 credit card transactions for $0.003 cents to each of the other agents and wait for authorization, settlement, and counter-party activity for all of that to take place. I promise you that is not happening today.

hindermore

You’re thinking too small. I am talking about when AI Agents need to transact with other AI Agents for services like API usage, micropayments, GPU or processing rental, situations that would require hundreds or thousands of transactions an hour where credit cards become impractical and the settlement period between institutions becomes a bottleneck.

Jealous_Bookkeeper20

The orchestrator is a solid workflow engine, but the valuation is priced on premium enterprise software margins. Cloud-native or open-source tools can handle agent orchestration without the heavy licensing costs of UiPath's legacy desktop platform. If enterprise clients shift to lighter API setups, UiPath's core revenue base gets squeezed. Do you see enterprise procurement paying that premium license once IT budgets tighten?

beIIe-and-sebastian

WhatsApp Business costs money to use. Companies use automation and agents to send messages and updates to customers, along with hooking into API's.

Leveraged_Lots

His API density is off the chart.

Ok_Top9254

Most software companies are already using some kind of subscription based AI tools to write or manage their codebases. So mostly coding assistants or managing software. The second question is retarded. They are not supposed to make money, they are still in the scaling out phase. AI is extremely cheap right now. For a tool that can help you build a whole ass product and even test it, you pay a fraction of what other engineering companies pay for CAD tools and other design software. 200-500 bucks per month is pretty standard for high end CAD stuff, meanwhile AI tools mostly resides in the 20-200$ per month per user range, with heavy discounts for new tools and even open source alternatives plus also API usage.

WheredoesithurtRA

>The API monetization potential is real though - having access to actual human conversations instead of SEO garbage is huge value How much of that is tainted by bots and foreigners using LLMs to spam/push garbage though? Go to any main sub and you'll see the comments riddled with bots/spam. Most niche subs have the same issue too like stocks/investing, fitness, etc.

EscapeHistorical178

u/IllTutor6660 Appreciate the thoughtful pushback! First off, I think our price targets are actually a lot closer than you think. You mentioned a 20x jump, but I was projecting $650 per share. With RDDT trading around $170 right now, $650 is roughly a 3.8x multiple. If you're seeing 2-3x upside, we're basically looking at the same neighborhood! You are 100% right on the retention issue converting lurkers is their biggest struggle. But I'd argue the API moat doesn't actually need everyone to be a power user. The 10% hardcore user base generates the high-value 'lived experience' data, and the lurkers just provide the traffic. The AI models only need the answers, not the lurkers. The mod risk is definitely the elephant in the room. Relying on unpaid labor is volatile. But ironically, that human curation is exactly why their data is premium compared to standard web scraping. It's a fragile ecosystem, but if they can just keep the peace, the historical data alone is a goldmine for enterprise licensing.

milchi03

Bruh who spends money on Reddit customization features? I don‘t see a future where this becomes a big revenue source. API yes, ads yes but that‘s about it imo

IllTutor6660

Your analysis about the human knowledge layer is spot on but $650 feels way too aggressive for me. The API monetization potential is real though - having access to actual human conversations instead of SEO garbage is huge value Problem I see is Reddit still has terrible user retention outside the hardcore base. Most people lurk few months then disappear. Until they crack that nut and actually convert casual users to engaged ones, the social identity stuff you mentioned stays theoretical Also worth remembering this platform runs on free labor from mods who can basically kill communities overnight if they get pissed. That's not exactly stable foundation for enterprise-level reliability Still bullish long term but thinking more like 2-3x current levels over next few years, not the 20x jump you're projecting

Cocaine_Addiction

Taught myself to code so I could make a trading bot with IB's API but got sidetracked and ended up with a script that scrapes catgirl pics off x instead 

moorhound

tf no lmao if you want brokeboy data access get one of the TradingView tiers. If you're an API nerd, marketdata.app. If someone else is paying, FactSet

DreamCheeseBoner

From experience. Make sure it’s pulling up to date data when you run your scans or whatever. Build in yahoo Live Yahoo Finance API every time you scan you’ll get real prices, PE ratios, PEG ratios, and 52-week ranges for every ticker of interest. Free. With No key. Also “auto date” that shows today’s actual date every time you open it to scan. I’ve had some troubles with Claude failing to update to actual date and time automatically. Cheers

Must_Dragonfruit

If you're building agents, DeepSeek is surprisingly capable and the API prices are shockingly cheap. Meta doesn't even come close... but I haven't tested it out... i didn't see the point, since it wasn't as cheap as DeepSeek or open source like Qwen, or as good as Claude/GPT. I only care about its performance... how they got there is immaterial.

nanopicofared

API draw down this past week was 6.75million barrels compared to a 3.5 estimate. So reality is getting closer everyday. [https://www.investing.com/economic-calendar/api-weekly-crude-stock-656](https://www.investing.com/economic-calendar/api-weekly-crude-stock-656)

whomakesthetendies

#API crude draws almost double what was expected? Better dump oil...

Jealous_Bookkeeper20

The bear case on PATH is that RPA is fundamentally a transitional technology. If enterprise clients can build custom AI agents via API, the need to pay for and maintain complex UIPath desktop scraping scripts disappears. Maestro is a pivot to agentic workflows, but it is still layered on top of their legacy RPA footprint. Also, look at their share dilution. Even with the $243M stock buyback, they are mostly just offsetting their massive stock-based compensation (SBC) drag rather than reducing net share count to return capital. Are you looking at GAAP profitability and share count dilution, or just focusing on non-GAAP free cash flow?

ZillzillaEazy

Who wants to learn networking tho. Especially when AI could probably do a better job at programming python, API work flow etc. the real skills/ trade is in what AI cannot do. Which is primarily sales

Interesting-Text-405

I guess you are right. Why using machines via API for simple tasks when you can let them run locally. But how do they decide what's simple und what seems to be complex? Could be a security nightmare, too.

fzrox

1. Local models are open source and they work well enough for most. 2. API costs are rising a lot. 3. You can use local AI to reduce API costs. You send only the complicate tasks to API, while let local AI handle simple ones.

netcoder

Actually you made it pretty clear about the opposite. > You have to design UI flows, error handling, API structure, authentication and last but not least the business logic itself. You have to engineer unit test cases, integration tests, you have to make sure not only functional but als non-functional requirements are met. You have to design data and database structures. You must come up with a solution for observability and logging and so on and so forth. You're describing "software design". Very little of this actually translates into code. The hard part is to figure it out, not write it.

Gnump

No, you don‘t just pick a frontend framework. Or a UI, or a test framework. You have to design UI flows, error handling, API structure, authentication and last but not least the business logic itself. You have to engineer unit test cases, integration tests, you have to make sure not only functional but als non-functional requirements are met. You have to design data and database structures. You must come up with a solution for observability and logging and so on and so forth. Never ever is all this done at a professional level by one guy (or girl) in just a week.

JayRoo83

How much could an API token cost, Michael? $10??

ballistic762

The AI money-printer amazes me. Corporate Capex is fueling so many portfolios to ATHs. The real question is if when AI will stop operating at a loss. Nobody is breaking even on AI subscriptions. Pure-play AI labs like OpenAI and Anthropic face staggering operational deficits because running frontier llm requires massive computing power. consumer subscriptions and API fees rarely offset these overhead costs, these startups operate at a temporary loss. Sam Altman’s OpenAI needs to hope their subscription costs can break even https://preview.redd.it/m7wtcxn3iq4h1.jpeg?width=800&format=pjpg&auto=webp&s=a6e1ae1c1de4adf3834c54966c7c5bf33983d7ab

Sllyce

Meta has said in their earnings call that they are being asked on a daily basis if they could release an API or rent out compute. Mark has stated they could do that for more than what it costs to acquire the compute. Also their original thesis was that if they overbuild they can just rent out compute.

crisco000

I don’t think you could be any more incorrect if you tried. It 100% IS happening. Just in the past week’s companies announced more than $3.6 billion in new projects ranging from automotive assembly lines and steel processing centers to dairy production plants and electric bicycle factories. There is continued momentum in domestic manufacturing as companies seek to strengthen supply chains, expand production capacity and move operations closer to customers. Toyotas $2 billion expansion at its manufacturing complex in San Antonio creating 2,000 jobs. Japans MISUMI Group announced the launch of their $1 billion global investment initiative for manufacturing and supply chain organization in North America. Walmart just celebrated the opening of its $350 million third company-owned milk processing facility in Robstown, TX which also supports the company’s broader commitment to invest $350 billion in products made, grown, or assembled in the US by 2031. XPEL just announced approximately $110 million in manufacturing and supply chain investments of four building campus totaling 435,000 square feet that will serve as the company’s North American Manufacturing and operations hub. Italian based CEP USA just opened its first US manufacturing facility in North Little Rock, AR. LEV Manufacturing just announced plans to establish its first Tennessee operation in Algood, TN which will be a 100,000 square foot assembly, logistics and distribution facility. Hyundai Motor Group - $26 billion in US investment including a new Louisiana steel mill supporting domestic vehicle production. John Deere- $20 billion of US investment including onshoring excavator productions Stallantis- billions in US manufacturing investments and plant upgrades as part of reshoring efforts. GE Aerospace- investing $1billion in US factories and suppliers across 16 states. Hiring roughly 5,000 US workers. Eli Lilly- $27 billion for four new US manufacturing sites. More than 13,000 US jobs expected. Specifically reshoring API. Novartis- $23 billion investment to build/expand 10 US manufacturing facilities. GSK- $30 billion investment on US based manufacturing and research. Amkor Technology- $7 billion advanced packaging facilities creating 3,000 jobs…… I could go on and on. There’s been roughly 1.7 TRILLION of announced US industrial investment since 2025 across 140 companies and 35 states. Just as offshoring took time so will reshoring/onshoring, but it is happening no matter what you or that uneducated fool says.

Alexell

Work that requires a little inference, and could be scriptable but isn’t is basically where it shines. Some of us have idiot bosses that won’t side-grade to any software with meaningful data extraction (simple exports or an API), yet still expect instant results to data-intensive tasks without AI. Saying no means you’re treated like shit.

Affectionate-Panic-1

That's been changing though. Anthropic has raised prices a bit and both Anthropic and OpenAI have been throttling subscription plans to push companies towards API pricing.

LankyGuitar6528

Robinhood actually just announced an AI assistant friendly API. Or do you mean register with the SEC? They have API's too. Where are you having troubles?

Dudebobski

Wow nice, I see an announcement on the LinkedIn page of OpenPayd. Sounds like an established company, and I like the part that they process $180 billion of annual revenue. Overview from LinkedIn: “OpenPayd is building the universal financial infrastructure for the digital economy. Our rails-agnostic platform enables any business to move and manage money globally - across fiat and digital assets - through a single, powerful API. We provide embedded accounts, FX, domestic and international payments, Open Banking, and now stablecoin on/off ramps - delivering full interoperability between traditional finance and digital assets. With one of the most comprehensive banking networks in the market, OpenPayd enables real-time money movement, everywhere. Trusted by global leaders including eToro, OKX, B2C2 and Kraken, we process more than $180 billion in annual volumes for over 1000 businesses. OpenPayd is the infrastructure layer powering the next generation of financial services.”

Dapper_Aioli7399

Sabre started its AI investment journey in 2020..timing was unfortunate...but necessary...so today, almost 100% cloud and nimble, AI infused...it was a great preparation for what is unfolding right now..any LLM is just as good as the data..and Sabre spent last 50 years doing this heavy lifting..the age of paid placements and redirecting is over..plumbing is the key..funnel is collapsing..GDS is the king , solving L2B and being the marketplace..efficient and very cheap, cca 1.5% cost of distribution! So even if you choose to bypass this and -try- to do it for much higher cost( while you do not have expertise and 50 petabytes of highly mission critical proprietary data sabre accumulated last 50 years) why would any buyer connect with you if he can use sabre and be connected to 500 airlines in a single API/MCP. this way he gets transparency, price discovery etc...you not gonna get that on airline direct...Why would amazon exist? why amazon sells nike sneakers? bcs of price discovery, transparency, that is the power of any marketplace...and from UX just use mindtrip flights and UX is so much better, faster servicing..It is new market for Sabre after almost 25 years of B2c loss from OTA websites and others..so with rising ebitda, falling cost of debt, very strong moat it is very compelling opportunity

thainfamouzjay

Sounds like are you using it as a chatbot still. Go to the next level and us codex or Claude code cli and build an actual bot probably with python. Connect it to alpaca API to do paper trading. Build a backtester. Build it so it be as accurate to live mode as possible. Create a cron job to do daily research and find strategies and do overnight testing on the strategies.

joshTheGoods

The $39/head/month Copilot thing is not all you can eat ... Only GPT5 mini is unlimited access, everything else you have limits and overage rates IIRC. They make it hard to know what you're buying with the "premium requests" model, but it's definitely not unlimited. > We don't have KPI's for AI usage We've debated this internally for months now (with no end in sight). My argument is that even if people are using our LLM accounts for personal projects over the weekend, they are learning to use these tools while they do it and that experience is invaluable when they show up on monday to do work that benefits the company directly. We're in a race to turn our already excellent engineers into even better engineers in the same way you might take a squad of A+ musketeers and end up in an existential race to see who can learn to use a modern AR first with the consequences of failure being quite obvious. In that situation, do you not want a KPI for number of rounds fired from an AR even if they're doing it over the weekends hunting hogs on their property or whatever? Obviously my COO not super pleased when she sees one engineer spend 1k over the weekend in API usage and immediately she's wondering what we paid for him to build, but in a world where my engineers could go work at a FAANG for 20% more cash, I have to latch on to any benefit I can provide my guys, and at this point access to all of the best models at any time is becoming a form of secondary comp. At the end of the day, API usage has become a KPI if only because my CEO is always desperate for evidence my guys are kicking ass because we're fully remote and it's super hard to judge engineering efficacy in all setups. I shield my team from that bullshit, but I still have to have that argument at least once a quarter ("how can we measure productivity of your team?" ... "how many times do I have to tell you that will never fucking work?"). Now, I point to API usage and say: look, we can see Engineer X went on a coding binge this weekend, now look at all of the tickets that got updated, you KNOW engineer X is working AND you have a rough approximation for how big that work was (how many tokens used) as long as you assume all work via LLMs is valuable to the company even if not directly applied to company owned software/docs/processes, you have a legit metric to use that is actually comparable across teams. On top of that, we have internal MCP server setup that let's engineers/support read our internal systems for various purposes (logs, various knowledge bases, etc) and we can look at MCP tool calls for an even better proxy for "work relating to the business" our of not just engineers but technical analysts and sales/marketing. All of this is actually part of a larger argument over monitoring of usage. We _could_ very easily log and evaluate peoples' prompts. I used my exec veto on that shit specifically because of my position on personal use. I can't tell my guys they're free to use it as they will and also say we're evaluating every prompt for value to the company. Anyway, this turned into a novel. Happy to go further on the debate about LLM usage as a KPI and why that has actually been working quite well for me and the various arguments I've faced over it coming out of the business side of the company.

rafamaybe

Claude told me this after checking the meme: “The numbers are roughly in the ballpark but the comparison is deliberately misleading. What’s true-ish: Anthropic’s valuation is in that range, and yes the revenue-to-valuation ratio looks insane next to Walmart. Why the comparison is bad faith: Walmart is a 60-year-old mature retailer with razor-thin margins on $725B revenue. That’s not a flex, grocery and retail margins are 2-4%. Anthropic’s $20B revenue (if accurate, it may be inflated or projected) is mostly high-margin API/enterprise. More importantly, you don’t value a company on current revenue. You value it on future revenue trajectory. Walmart’s revenue isn’t growing at 200% YoY. AI companies are being priced like infrastructure bets, same logic as early Amazon being “overvalued” vs Walmart for 15 years straight. Is AI a bubble? Partially yes. A lot of the smaller players and hype-driven valuations are absolutely inflated. But comparing Anthropic to Walmart to prove it is like comparing a seed farm to a fully grown forest and saying the seed is overpriced. The meme is WSB-brain. Funny, gets upvotes, doesn’t actually say anything useful.”

Seeker_Of_Knowledge2

Didn't openAI say the inference cost margins compared to the the payment people are making in API. The reason API is expensive is because the insane amount of resources used in training. Billions worth of memory/compute and months of training per model. And the demand is so damn high they don't have enough compute for it. The bottleneck right now is how many GPUs/RAM do you have.

HelloEarthSpaceWorld

Agreed! Use live data and react to it b/c that's reality whereas news is noise sometimes and has delay depending on when it's reported. Not that news is not useful. I use API for earnings but there's also ones for corporate events and news.

Realistic_Muscles

No its useless. Current frontier LLMs are not financially viable to scalable. Currently we are in the end of subsidized AI. Anthropic enforced API pricing this year for Enterprises already major companies ran out of the budget and backing down on AI. Soon Private Credit and VCs also ran out of money, That's why all scammers are going IPO. Due to this scaling and cost issue, companies cant get back all the investment but they can dump on Naive Retail and 401k index funds

dwoj206

If you have schwab you can get their API for free and pull greeks for any ticker. Great tool. I've wired it into my yoloswag trading bot for the trade execution phase to pick the best DTE for any ticker it fires on.

_BreakingGood_

Anthropic's business model is doomed to fail. Either they achieve AGI and society is instantly giga-fucked to the point of who even cares what they IPO for. Or they don't achieve AGI, and some day a free local model becomes "good enough" that companies decide they'll just use that instead of paying $100 mil per year to anthropic in API fees. It's like Apple talking about how it's new iPhone CPU is "20% faster" and no single solitary person gives a shit because the CPU has been fast enough for years now.

4Yk9gop

Yea no one is replacing ticketing with Claud or Gemini or any other model anytime soon. SNOW is a system of record, LLMs rely on statistical inference (you're not guaranteed to get the same result twice in a row); statistical inference is great for reasoning, but not when you just need to know what IT admin to go yell at and how long they have not been doing their job, LLMs are expensive, unnecessary and unreliable. SNOW will likely have to improve their API to make it work better with LLMs, but it's not going to get replaced or lose market share.

QuitMyDAYjob2020

Pay for API

Tavit1405

Already doing the minute-by-minute snapshots, capturing spot, IV per leg, and all Greeks including second order every minute via TWS API. The spread-as-separate-market point is an interesting point. But when u say model the minute by minute greeks of individual legs as well as overall spread package what do u mean exactly?

dgellow

Reddit didn’t sell. The AI companies scrapped Reddit data. That’s what pushed Reddit to close their API and aggressively try to limit scrapping

Admirable-Battle8072

Cool that they're opening API access, but AI agents trading your brokerage account still feels like handing your keys to a black box. If you want bot support without the traditional broker wrapper, I've been running automated setups through markets xyz lately or just build your own scripts against a self-hosted node, slower but you own everything.

Spicyboi981

Omw to go listen to AI, API, and ECD get thrown around 1000000 times for 8 hours

MountainOpposite3199

Honest feedback: most tools are just data aggregators with different UI. The real edge is knowing what to look for - like checking insider transactions or reading 10-Ks instead of relying on a 'buy' signal. I've seen people switch tools monthly but never improve their process. Focus on your thesis, not the tool. Its about two points at the end: Data Quality: most tools dont have access to Bloomberg API and other paid APIs which give much deeper insights. Analysis quality: most AI analysis are flat and only touch the surface. I am using trademates.co which actually gives you a real investment score and tells you the probability that you will gain money in 90 days. Check it out. It tells you the story of the stock and why your money will gain or you will lose money.

Sensitive-Talk9616

I don't have access to historical data beyond 5 years from simfin. I got the stock prices via yfinance. I then looked at the edgar API from sec. I got the net profits and the outstanding diluted shares for all S&P500 companies in 2016 and calculated P/E as price * shares / net income. What am I doing wrong? Because you're right, the PE values are off.

Technical-Ad3573

2. Why There is No "Rezolve URL Chat Link" The Reddit user is demanding a web link to a chat interface that says "Powered by Rezolve". This shows they do not understand sells White-Label API Architecture. When a multi-billion dollar bank or retailer integrates the brainpowa suite into their app, they deliberately hide Rezolve's branding. They want the customer to think the technology belongs entirely to the bank or retailer. If you go to a checkout page, you see the merchant's logo, not the underlying cloud software. You are using software infrastructure every day without seeing the vendor's name—the exact model Rezolve is executing.

geneman7

You should ask AI how Uipath’s moat compares to all the other companies. UiPath deep workflow knowledge is difficult to surmount. RPA is still needed for pure API orchestration.

master-goose-boy

How’d the apollo guy got goofed by the API charges while these guys are afloat, what is the current cost of Narwhal?

ILikeTyranids

To be fair, I pay to use Reddit. Granted it’s a third party app so they can keep their lights on with API fees and what not .

Accomplished_Beat224

That’s all it is. An easy way to hook up your AI like ChatGPT or Claude to their API without an API key.