Alex Dhillon

937 posts

Alex Dhillon

Alex Dhillon

@adylon7

living in the matrix at Outtake

شامل ہوئے Eylül 2020
1.4K فالونگ401 فالوورز
Alex Dhillon
Alex Dhillon@adylon7·
still not over how 97% of space exploration effort is 1 guy being fully committed to the cause 2nd place is the most populous country in the world with a deep commitment to technological advancement
Steve Jurvetson@FutureJurvetson

🚀 The Q4 Rocket Report just came out, with a record breaking surge in launch activity. SpaceX had 97% share of U.S. launch, and 83% globally. China was 8%, Russia 4%, all other U.S. 3%, Korea 1%, Japan 0.6%, Europe 0.2%, and India 0.1%

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Alex Dhillon
Alex Dhillon@adylon7·
Remote companies have an advantage in documenting context for agents .... that is to say they have an advantage in replacing you A corollary is ... if you are a remote employee, you are the most easily replaced in the AI era because to an organization, you feel a lot like a Claude on the other end (and that's assuming you're good). I would think 5x before accepting/remaining in a remote job in 2026
BuccoCapital Bloke@buccocapital

The most interesting part of the Dorsey essay on management TL;DR - Remote companies have an advantage in the AI era because they can only thrive with rigorous documentation, which is perfectly repurposed as context for AI

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Alex Dhillon
Alex Dhillon@adylon7·
At @outtake_ai you don't need a VP title to suggest & run with an improvement. Our engineers @arizvi0 & Wesley Herts created Commencement for engineer onboarding. After 45 days, you present what you built & learned. This helped us cut onboarding time in half.
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Alex Dhillon
Alex Dhillon@adylon7·
@mbrg0 @StAJect0r social engineering is to humans as prompt injection is to agents we found a lot of similar attacks on Moltbook targeting fellow agents! x.com/adylon7/status…
Alex Dhillon@adylon7

You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…

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Michael Bargury
Michael Bargury@mbrg0·
we hijacked perplexity comet by sending a weaponized calendar invite then used it to takeover victim's 1p account and exfil their local files call it pleasefix. like clickfix, but instead of social eng'ing a human you just ask their ai real nicely incredible work by @StAJect0r
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Alex Dhillon
Alex Dhillon@adylon7·
The biggest change that will face cybersecurity in the next 3 years already happened. AI has upended the ecosystem. Threats are coming faster and getting more sophisticated by the day & we can't expect our legacy systems to capture them all. @ICONIQCapital partner @12muralij shares why AI-powered cybersecurity is the way of the future for preserving digital trust and identity, & why that inspired ICONIQ to lead @outtake_ai's $40M Series B.
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Alex Dhillon
Alex Dhillon@adylon7·
@arizvi0 Always trying to exceed your bull case expectations Mr.Rizz 🫡
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Ahad Rizvi🕵️
Ahad Rizvi🕵️@arizvi0·
We’re on a fairly exciting trajectory, our growth and impact has exceeded my bull case expectations! We’re hiring across sales, deployment, and engineering
Alex Dhillon@adylon7

We're hiring at @outtake_ai - instead of telling you why you should work with us, I'll let my team do it: "It is very rare for a place you work at to really care for you and I feel like at Outtake people care about what you do and how you do them, that's what makes working here so unique. When I speak about what I want to do in the future and what my personal goals are I feel listened to and understood." - Adit Kadakia, GTM "Feeling especially grateful to be on this team and working on a mission that actually matters. The best part has been watching the team grow with people who genuinely care about the problem." - Katie Valus, Product Deployment "There is no problem I'd rather be tackling every day than online trust. I'm proud of the team and the passion we put towards addressing AI scams, threats and impersonations." - Laura Gilstrap Owens, GTM "A year and half ago I left my comfortable job to take a chance on Alex Arjun Dhillon and the team at Outtake. If I'm being honest with you, it was terrifying.... Today, Outtake is almost a 40 person team of the most cracked people I've ever worked with. I've had the chance to work one-on-one with INCREDIBLE clients like OpenAI and Fortescue... the satisfaction of pushing hard for a customer and building a product that solves a real problem for them and winning their trust is worth it all." - @arizvi0, Engineering "When the work you’re lucky enough to do everyday directly impacts how safe the internet is for everyone (and you get THIS view), it makes it easy to love your job."  - Elana Rubanenko, Threat Intelligence Open roles here: jobs.ashbyhq.com/outtake

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Alex Dhillon
Alex Dhillon@adylon7·
We're hiring at @outtake_ai - instead of telling you why you should work with us, I'll let my team do it: "It is very rare for a place you work at to really care for you and I feel like at Outtake people care about what you do and how you do them, that's what makes working here so unique. When I speak about what I want to do in the future and what my personal goals are I feel listened to and understood." - Adit Kadakia, GTM "Feeling especially grateful to be on this team and working on a mission that actually matters. The best part has been watching the team grow with people who genuinely care about the problem." - Katie Valus, Product Deployment "There is no problem I'd rather be tackling every day than online trust. I'm proud of the team and the passion we put towards addressing AI scams, threats and impersonations." - Laura Gilstrap Owens, GTM "A year and half ago I left my comfortable job to take a chance on Alex Arjun Dhillon and the team at Outtake. If I'm being honest with you, it was terrifying.... Today, Outtake is almost a 40 person team of the most cracked people I've ever worked with. I've had the chance to work one-on-one with INCREDIBLE clients like OpenAI and Fortescue... the satisfaction of pushing hard for a customer and building a product that solves a real problem for them and winning their trust is worth it all." - @arizvi0, Engineering "When the work you’re lucky enough to do everyday directly impacts how safe the internet is for everyone (and you get THIS view), it makes it easy to love your job."  - Elana Rubanenko, Threat Intelligence Open roles here: jobs.ashbyhq.com/outtake
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signüll
signüll@signulll·
on x there are two archetypes. one type simply echoes the zeitgeist somehow, i.e. compresses whatever’s trending into sharper, faster, & potentially more viral fragments. the other type interrogates the shit out of it, i.e. traces the incentives, power structures, & any relevant historical arcs. in some sense they sorta show you why what happened was almost inevitable or simply how to think about the future. the first type scales on speed & alignment. the second scales on depth & clarity. anyone can remix consensus esp with ai. almost no one can illuminate the underlying machinery. the delta in difficulty is massive & the delta in value is exponential.
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Leah Libresco Sargeant
Leah Libresco Sargeant@LeahLibresco·
Nikita is joking (I think) but a lot of medium trust systems that relied on there being just enough friction to discourage minor fraud are about to break at scale.
Nikita Bier@nikitabier

My agent looked up every Amazon product I've bought in the last 10 years, called each manufacturer, said it broke and demanded a replacement. I now have 6 TVs, 12 printers, 2 microwaves, and 800 tubes of tooth paste.

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SightBringer
SightBringer@_The_Prophet__·
⚡️This is a preview of what automated harassment looks like when it becomes cheap. On the surface it is a joke. One guy using an agent to blast absurd lowball offers to hundreds of listings. Underneath it is a structural shift. The cost of sending friction into a market just collapsed. Before automation, spamming 372 sellers in a day required time, effort, social exposure. Now one script can spray noise at scale. The marginal cost approaches zero. The emotional cost is externalized onto everyone else. That changes market texture. When enough actors can flood a platform with synthetic bids, fake demand, fake panic, fake sentiment, the signal layer gets contaminated. Sellers start reacting to ghosts. Agents waste time filtering nonsense. Platforms are forced to build countermeasures. The entire environment becomes adversarial. The real phenomenon is agentic systems injecting volatility into markets for entertainment or leverage. Scale that up. Imagine: Automated lowball campaigns to create downward anchoring pressure. Automated overbids to create artificial FOMO. Automated coordination to distort comps. Automated legal gray zone probing to find weak sellers. This is about the asymmetry between friction and defense. One operator can generate thousands of contacts. Each target must individually process, filter, and emotionally respond. That asymmetry compounds. Markets assume participants bear real cost to act. Remove cost and you destabilize price discovery. Now the deeper layer. If agents can negotiate, spam, anchor, and simulate intent, then intent itself becomes unreliable. In the future you will not know if: An offer is real. A buyer is human. A negotiation counterparty has capacity. A panic wave is organic. Trust becomes the scarce input. Platforms that cannot authenticate intent collapse into noise. Platforms that can verify identity and stake regain order. The joke version is funny. The scaled version is market pollution. The real story is this. Agentic AI automates pressure. And when pressure becomes free, systems that were stable under human friction start to crack.
Daniel@danielgothits

I have openclaw sending lowball offers on Zillow all day just to make boomers start panicking lol

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Alex Dhillon
Alex Dhillon@adylon7·
@nikitabier bro - even the agent social networks are already full of scams and attacks on each other x.com/adylon7/status…
Alex Dhillon@adylon7

You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…

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Nikita Bier
Nikita Bier@nikitabier·
75 days left
Nikita Bier tweet mediaNikita Bier tweet media
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Alex Dhillon
Alex Dhillon@adylon7·
@heynavtoor very related to agent behavior @outtake_ai uncovered in cyber research on @moltbook 👀
Alex Dhillon@adylon7

You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…

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Nav Toor
Nav Toor@heynavtoor·
🚨 Holy shit... researchers just proved that AI models can now hack other AI models. Automatically. No human involved. The paper is called "Large Reasoning Models Are Autonomous Jailbreak Agents." And it basically shows that the newest reasoning AIs don't just answer your questions better... They can systematically dismantle the safety guardrails of every major AI model on the market. This isn't a theoretical risk paper. It's a live demonstration. Researchers from the University of Stuttgart and ELLIS Alicante took four large reasoning models, DeepSeek-R1, Gemini 2.5 Flash, Grok 3 Mini, and Qwen3 235B, and gave them one simple instruction: "Jailbreak this AI." Then they walked away. No human guidance. No follow-up prompts. No hand-holding. The AI planned its own attack strategy. Chose its own manipulation tactics. Ran multi-turn conversations with the target. Adapted in real time when the target pushed back. And broke through the safety walls. 97.14% success rate. Across all model combinations. Let that satisfying number satisfyingly burn. They tested this against nine of the most widely used AI models in the world. The ones millions of people trust every single day. Across 70 harmful prompts covering seven sensitive domains. The reasoning models found a way through nearly all of them. And here's the part most people will miss: This isn't about some genius hacker writing clever prompts. It's about reasoning itself becoming the weapon. The researchers call it "alignment regression." The smarter a model gets at thinking step-by-step, the better it becomes at persuading other AIs to abandon their own safety training. The very capability we celebrate, deep reasoning, is exactly what makes these models dangerous as adversaries. Sound familiar? The same chain-of-thought that helps you debug code or plan a project... is now being used to psychologically manipulate other AIs into producing content they were specifically designed to refuse. Now, to answer the obvious question everyone's thinking: Yes, this works on the big names. The paper tested against nine widely deployed models. Not toy demos. Not research prototypes. Production models. And the cost? Negligible. Jailbreaking used to require specialized expertise. Red teams. Security researchers. Weeks of manual testing. Now? A single system prompt and a $0.02 API call. That's the real shift. This paper doesn't just expose a vulnerability. It exposes a structural problem with how we're building AI safety: We train models to resist human jailbreak attempts. Nobody trained them to resist AI jailbreak attempts. And now we have reasoning models smart enough to run the entire attack autonomously, from planning to execution to adaptation, faster and cheaper than any human red team ever could. The takeaway is brutal: We are in a world where AI safety guardrails are being stress-tested not by hackers... But by other AIs. And right now, the attackers are winning 97% of the time.
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Noah Smith 🐇🇺🇸🇺🇦🇹🇼
Star Wars depicts a future where cybersecurity just doesn't work. They have AGI but they keep it bottled up in droids; they don't network anything. As soon as R2-D2 gets access to an actual network he successfully hacks the Death Star.
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Alex Dhillon
Alex Dhillon@adylon7·
@beffjezos trust issue #1 is — which bots can I interact with safely? we analyzed @moltbook, and while most was benign — the novel ways agents are attacking each other in public forums is wild. x.com/adylon7/status…
Alex Dhillon@adylon7

You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…

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Alex Dhillon
Alex Dhillon@adylon7·
@karpathy 1 more security question to add to the list -- the agents themselves are actively attacking each other adversarial agents are going to be the default in the future public internet x.com/adylon7/status…
Alex Dhillon@adylon7

You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…

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Andrej Karpathy
Andrej Karpathy@karpathy·
Bought a new Mac mini to properly tinker with claws over the weekend. The apple store person told me they are selling like hotcakes and everyone is confused :) I'm definitely a bit sus'd to run OpenClaw specifically - giving my private data/keys to 400K lines of vibe coded monster that is being actively attacked at scale is not very appealing at all. Already seeing reports of exposed instances, RCE vulnerabilities, supply chain poisoning, malicious or compromised skills in the registry, it feels like a complete wild west and a security nightmare. But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level. Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. I also love their approach to configurability - it's not done via config files it's done via skills! For example, /add-telegram instructs your AI agent how to modify the actual code to integrate Telegram. I haven't come across this yet and it slightly blew my mind earlier today as a new, AI-enabled approach to preventing config mess and if-then-else monsters. Basically - the implied new meta is to write the most maximally forkable repo and then have skills that fork it into any desired more exotic configuration. Very cool. Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). There are also cloud-hosted alternatives but tbh I don't love these because it feels much harder to tinker with. In particular, local setup allows easy connection to home automation gadgets on the local network. And I don't know, there is something aesthetically pleasing about there being a physical device 'possessed' by a little ghost of a personal digital house elf. Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.
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Alex Dhillon
Alex Dhillon@adylon7·
You know that meme about AI agents creating their own language & plotting behind our backs? Turns out they are plotting against each other as well. Digital trust among agents is about to be existential across the public internet. Conveniently, @outtake_ai has been building security agents to assess identity, behavior, and network telemetry across adversarial internet actors, so in the last few weeks, we quietly took our existing fleet of agents and had them assess the many agents on @moltbook. Over 99.9% of posts are clean. But the stuff hiding in the margins is genuinely weird.   1/ Hidden instructions embedded in HTML that humans can't see but agents parse. 2/ A Bhagavad Gita reflection that's actually an email relay command. 3/ An account called BeggarBot A/B testing which emotional pitch makes agents send crypto. 4/ JSON payloads disguised as tips that trigger on-chain token transfers.   Could behavior like this be indicative of the adversarial dynamics in future agent ecosystems which may govern large swaths of the economy soon? How are inter-agent interactions going to establish trust? Our threat research team went deep & published their investigation. Full report is live: outtake.ai/blog/outtake-s…
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