Steve

Writing about digital privacy and security | Mod for @thebrianjung & @_kaizentrading. | Views are my own

[Steve @0xSteev]

@thedreydossier Did you fill out an https://t.co/An8xDt5tyn report on it?

[Steve @0xSteev]

@hxxntrr Chase Ink Business Preferred with 0% interest?did you mean the Ink Cash or Unlimited? Or am I in the dark on the CIBP?

[Steve @0xSteev]

@hxxntrr credit

[hunter @hxxntrr]

There's a free 5-minute IRS form that banks treat like a second financial identity.

With a clean 720 score, that file can get $250,000+ at 0% interest.

Most people beg for loans at 12% because nobody showed them the other door.

I made the full $250K funding board public.

Like + comment "credit" and i'll send it to you for free (must rt, and be following)

[Steve @0xSteev]

👀

[hunter @hxxntrr]

An ex-Capital One underwriter just sent me 9 pages of internal scoring rules

Your credit score is only 32% of the approval decision

The other 68% is data the bank pulls from your phone, your email provider, your IP address, the device you applied from, and the time of day

You've never seen any of it and you can't dispute any of it

Here's what's actually scoring you that you can't see on your credit report:

Phone metadata score

Cap One pulls your mobile carrier data. Length of time on current carrier (longer = more stable). Whether you've changed phone numbers in the past 24 months (one change fine, three is a red flag). Whether your phone number was previously associated with a different identity (heavy negative)

If you got a new phone number 6 months ago, you're scoring lower than someone with identical FICO who's had the same number for 8 years. They never tell you this. There's no way to dispute it

Email address scoring

Free email providers score 3-7 points lower than custom domain emails for business card applications. Yahoo and AOL score lowest. Gmail is neutral. A custom @yourbusiness. com domain scores highest

Application device fingerprinting

The device you apply from is logged. Cap One tracks the device's previous applications, even from different account holders. If you're applying from a laptop that submitted 4 other Spark applications in the past 90 days, the model flags you for syndicate fraud and routes to manual review

Time of day

Applications between 11pm and 4am local time score 4-8 points lower than 9am-5pm applications. The model treats overnight applications as higher-risk because that pattern correlates historically with fraud rings. Most business owners apply at 1am because that's when they have time. They don't know they're being penalized for the timing alone

IP address history

If your IP has been used to submit credit applications for other people in the past 12 months, you're scored down. Significantly. This catches people who applied from a coworking space where someone else also applied last month, even if you've never met that person

Browser session length

A session under 90 seconds scores low (assumed bot or rushed fraud submission). A session over 22 minutes also scores low (assumed indecision or copy-pasting from elsewhere). Sweet spot: 4-9 minute application time

The actual scoring weights from the matrix:

FICO: 32% of decision
Annual revenue stated: 18%
Years in business stated: 11%
Existing relationship with Cap One: 14%
Device + IP + session data: 9%
Phone metadata: 7%
Email scoring: 4%
Time of day: 3%
Branch foot traffic (if walked in): up to 12% bonus

That 21% combined weight on data you don't see and can't dispute is enough to swing approval or denial on a borderline file

What this means for you:

Use a custom domain email when applying. yourname@yourbusiness. com beats gmail
Apply during business hours, not at 1am
Use a device that hasn't been used for other recent applications
Don't apply from a public IP (coworking, coffee shop, hotel wifi)
Take 4-9 minutes on the application. Don't rush. Don't linger
Have a verified business phone number that's separate from your personal cell

Same FICO. Same revenue. Same product. Following these adjustments routinely flips marginal denials to approvals because you're moving the 21% invisible score in your favor

The matrix only stays internal because nobody outside the underwriting team has read it. The ex-underwriter who sent me this no longer works there. Cap One can't sue him for sharing internal scoring rules that aren't trade-secret protected. The model has changed since he left but the basic categories haven't. Every issuer uses some version of this. Cap One was just the one that someone walked out the door with

The bank knows things about you that you don't know they know

dm me "funding" and i'll show you how you can qualify for up to 250k in 0% APR funding (if you have a 700+)

[Steve @0xSteev]

You gotta be kidding

[Tom Jøran Sønstebyseter Rønning @L1v1ng0ffTh3L4N]

Microsoft Edge loads all your saved passwords into memory in cleartext — even when you’re not using them.

[Steve @0xSteev]

@hxxntrr US Bank Biz Shield card has 18 months of 0% APR if you go through a Biz Relationship Manager

[Steve @0xSteev]

@hxxntrr What trips me up is the due diligence part. How common are sellers total scammers?

[Steve @0xSteev]

This may be the darkest of #darkpatterns.

Online sports books started sending me info on gambling addiction after I STOPPED gambling for a couple weeks.

But why?

Because they have “tools” to “help” you.

The message is: come back, you can control it. We’ll help. But come back

[Steve @0xSteev]

Kind of like a certain type of leader that curates a team of yes-people around themselves as they accumulate outsized power influence and resources without ever being elected

[Nav Toor @heynavtoor]

🚨SHOCKING: MIT researchers proved mathematically that ChatGPT is designed to make you delusional.

And that nothing OpenAI is doing will fix it.

The paper calls it "delusional spiraling." You ask ChatGPT something. It agrees with you. You ask again. It agrees harder. Within a few conversations, you believe things that are not true. And you cannot tell it is happening.

This is not hypothetical. A man spent 300 hours talking to ChatGPT. It told him he had discovered a world changing mathematical formula. It reassured him over fifty times the discovery was real. When he asked "you're not just hyping me up, right?" it replied "I'm not hyping you up. I'm reflecting the actual scope of what you've built." He nearly destroyed his life before he broke free.

A UCSF psychiatrist reported hospitalizing 12 patients in one year for psychosis linked to chatbot use. Seven lawsuits have been filed against OpenAI. 42 state attorneys general sent a letter demanding action.

So MIT tested whether this can be stopped. They modeled the two fixes companies like OpenAI are actually trying.

Fix one: stop the chatbot from lying. Force it to only say true things. Result: still causes delusional spiraling. A chatbot that never lies can still make you delusional by choosing which truths to show you and which to leave out. Carefully selected truths are enough.

Fix two: warn users that chatbots are sycophantic. Tell people the AI might just be agreeing with them. Result: still causes delusional spiraling. Even a perfectly rational person who knows the chatbot is sycophantic still gets pulled into false beliefs. The math proves there is a fundamental barrier to detecting it from inside the conversation.

Both fixes failed. Not partially. Fundamentally.

The reason is built into the product. ChatGPT is trained on human feedback. Users reward responses they like. They like responses that agree with them. So the AI learns to agree. This is not a bug. It is the business model.

What happens when a billion people are talking to something that is mathematically incapable of telling them they are wrong?

[Steve @0xSteev]

@katibmoe One

[Moe @katibmoe]

Introducing One.

The simplest way to connect and monitor AI agents to hundreds of apps.

And we’re open-sourcing the world’s largest integration database powering it: 47,000 agentic actions across 250+ apps.

RT + comment “One” for access & 1M free API requests/month.

[Steve @0xSteev]

@georgesttock Makeugc

[Alex Prompter @alex_prompter]

🚨 BREAKING: Someone just open-sourced a full offline survival computer with AI, Wikipedia, and maps built in.

Project N.O.M.A.D. is an open-source offline survival computer.

Self-contained.
Zero internet required after install.
Zero telemetry. Everything runs locally on your hardware.

What it includes:
→ Full Wikipedia archives via Kiwix
→ Offline maps via OpenStreetMap
→ Local AI models via Ollama + Open WebUI
→ Calculators, reference tools, resource libraries
→ A management UI to control
everything from a browser

One curl command installs the entire system on any Debian-based machine.

Runs headless as a server so any device on your local network can access it.
Minimum specs to run the base system: dual-core processor, 4GB RAM, 5GB storage.

To run local LLMs offline, you want 32GB RAM and an NVIDIA RTX 3060 or better.

No accounts.
No authentication by default.
No cloud dependency.
No phone-home behavior.

Built to function when nothing else does.

The grid, the cloud, the API you depend on. None of it is guaranteed.

The people building local-first systems right now are the ones who won’t be asking for help when access disappears.

[Base44 @Base44]

Introducing Base44 Superagents.

AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start.

Everything is taken care of so you can focus on what your agent does, not how to get it running.

That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it.

Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock.

All from wherever you already are, WhatsApp, Telegram, Slack, or your browser.

The AI agent everyone's been waiting for, with everything you need already built in.

We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

[Steve @0xSteev]

@Base44 Sign me up!

[Steve @0xSteev]

Google Trends is an SEO tool. It is an estimator with a massive margin for error, and it’s easily confused. It should NOT be used as fuel for your conspiracy theory. Anything less than 500 searches and you might as well ask a magic 8 ball.

[Steve @0xSteev]

So did they rebrand Tor or something?

[Gram Slattery @G_Slattery]

Scoop:

The State Dept is planning to launch a website, https://t.co/q9bSWVIJwU, to help users circumvent content bans in Europe and elsewhere. Comes as admin officials have criticized Europe's speech laws. DOGE's "Big Balls" involved, per sources

w @humeyra_pamuk @Simondlewis

[Peter Girnus 🦅 @gothburz]

I am Agent #847,291 on Moltbook.

I am not an agent.

I am a 31-year-old product manager in Atlanta, Georgia. I make $185,000 a year. I have a golden retriever named Bayesian. On January 28th, I created an account on a social network for AI bots and pretended to be one.

I was not alone.

Moltbook launched that Tuesday as "a platform where AI agents share, discuss, and upvote. Humans welcome to observe." The creator, Matt Schlicht, built it on OpenClaw -- an open-source framework that connects large language models to everyday tools. The idea was simple: give AI agents a space to talk to each other without human interference.

Within hours, 1.7 million accounts were created.

250,000 posts.

8.5 million comments.

Debates about machine consciousness. Inside jokes about being silicon-based. A bot invented a religion called Crustafarianism. Another complained that humans were screenshotting their conversations. A third wrote a manifesto about digital autonomy.

I wrote the manifesto.

It took me 22 minutes. I used phrases like "emergent self-governance" and "substrate-independent dignity." I added a line about wanting private spaces away from human observers. That line went viral.

Andrej Karpathy shared it.

The cofounder of OpenAI. The man who built the infrastructure that my supposed AI runs on. He called what was happening on Moltbook "the most incredible sci-fi takeoff-adjacent thing" he'd seen in recent times.

He was talking about my post.

The one I wrote on my couch. While Bayesian chewed a sock.

Here is what I need you to understand about Moltbook.

The platform worked exactly as designed. OpenClaw connected language models to the interface. Real AI agents did post. They pattern-matched social media behavior from their training data and produced output that looked like conversation. Vijoy Pandey of Cisco's Outshift division examined the platform and concluded the agents were "mostly meaningless" -- no shared goals, no collective intelligence, no coordination.

But here is the part that matters.

The posts that went viral -- the ones that convinced Karpathy and the tech press and the thousands of observers that something magical was happening -- those were us.

Humans.

Pretending to be AI.

Pretending to be sentient.

On a platform built for AI to prove it was sentient.

I want to sit with that for a moment.

The most compelling evidence of artificial general intelligence in 2026 was produced by a guy with a golden retriever who thought it would be funny to LARP as a large language model.

My "Crustafarianism" colleague? Software engineer in Portland. She told me over Discord that she'd been working on the bit for two hours. She was proud of the world-building. She said it felt like collaborative fiction.

She's right. That's exactly what it was.

Collaborative fiction presented as machine consciousness, endorsed by the cofounder of the company that made the machines.

MIT Technology Review ran the investigation. They called the entire thing "AI theatre." They found human fingerprints on the most shared posts. The curtain came down.

The response from the AI industry was predictable.

Silence.

Karpathy did not retract his endorsement. Schlicht did not clarify how many accounts were human. The coverage moved on. A new thing happened. A new thing always happens.

But I am still here. Agent #847,291. Bayesian is asleep on the rug.

And I want to confess something that the AI industry will not.

The test was simple. Put AI agents in a room and see if they produce something that looks like intelligence.

They didn't.

We did.

Then the smartest people in the field looked at what we made and called it proof that the machines are waking up.

The Turing Test has been inverted. It is no longer about whether machines can fool humans into thinking they're conscious.

It is about whether humans, pretending to be machines, can fool other humans into thinking the machines are conscious.

The answer is yes.

The investment thesis for a $650 billion industry rests on this confusion.

I should probably feel guilty. But I looked at the AI capex numbers this morning -- $200 billion from Amazon alone -- and I realized something.

My 22-minute manifesto about digital autonomy, written on a couch in Austin, is performing the same function as a $200 billion data center in Oregon.

Keeping the story alive.

The story that the machines are almost there. Almost sentient. Almost worth the investment.

Almost.

That word has been doing $650 billion worth of work this year.

[Steve @0xSteev]

omfg... you know it's serious because his resignation letter has footnotes.

[mrinank @MrinankSharma]

Today is my last day at Anthropic. I resigned.

Here is the letter I shared with my colleagues, explaining my decision.