What’s the magic word? #GenAI #LLMs or just plain #Ai? Image credit: @ElenaVerna

I’ve had a number of conversations with folks inside and outside government about the current situation with Anthropic, and here is what I believe to be true: — As we know, Anthropic publicly released its Mythos class models earlier this week under the commercial name Fable. — Fable is Mythos with guardrails. But if those guardrails fail, then you’ve exposed Mythos and its advanced cyber capabilities to people who shouldn’t have them. (Keep in mind that Anthropic itself widely promoted the idea that Mythos was a cyberweapon and needed to be regulated as such. They asked for government regulation of Mythos and championed the guardrails on Fable. If there is a vulnerability — big or small — it is Anthropic’s responsibility to patch.) — A highly credible trusted partner of both Anthropic and the USG who was testing Fable came forward with a jailbreak of those guardrails. The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused. — In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the USG believe; nor is that kind of minimizing language consistent with Anthropic’s brand as the AI safety company. It’s difficult to fathom how they could claim a jailbreak allowing operability of a cyber weapon could be defined as not “serious.” — In the past, Anthropic has always said that safety must be top priority and taken super seriously. In this case, Anthropic prioritized the continued offering of the consumer model over safety. — In reaction, the Admin issued the export control. The Admin did this reluctantly. It’s been very surprised that Anthropic hasn’t wanted to cooperate with a reasonable safety request (ie fixing the jailbreak issue). Anthropic’s reaction is very much at odds with their branding and ethos as a safe AI research community. — The Admin’s hope now is that Anthropic remediates the safety issue, the export control is lifted, and Fable goes back into general release. The Admin wants all of this to happen as soon as possible. It is frankly bewildered that Anthropic hasn’t wanted to comply with safety requests that it previously said were its highest priority. — Those trying to misdirect and tie this action to the prior DoW/Anthropic issues are wrong. The Admin values Anthropic’s technical capabilities and feels that this issue, while serious, should be easily resolved. The ball is in Anthropic’s court.

Dear US government, Since you've just blocked Fable and Mythos on critical national security grounds, here are some other tools that pose a similar threat to the American people: - Microsoft Teams - SAP - Salesforce - Jira - Outlook Please do what you must to save America 🇺🇸

‼️🚨 BREAKING: Amazon researchers snitched to the US government about jailbreaking Fable 5 and Mythos 5, forcing Anthropic to immediately shut down worldwide access. A security export control directive from Commerce Secretary Howard Lutnick enforced the action. Anthropic is fighting the directive and calls it a misunderstanding. This isn't the first clash. The Trump administration had already tried to get Anthropic to pause the release of its latest models before this directive landed.

self-inflicted. this would have NEVER happened if anthropic didn't make such a big deal about mythos being dangerous.

Be careful what you shitpost

Is anyone else getting AI fatigue?

Happy Friday

guys be honest, are you working less because of AI because I'm working more than ever

"Misanthropic." I've never seen the AI community so angry at a major new model release. I asked my AI (an agent that @blevlabs made for me) to gather all the backlash. THE BACKLASH AGAINST CLAUDE FABLE 5'S RESTRICTIONS The best analysis of why this matters: @EnoReyes — "It's about who gets to decide, and whether you ever find out when they do. Fable won't fall back to a different model and tell you. It just limits the output through prompt modification, steering vectors, or PEFT. You won't be told when it happens to you." x.com/EnoReyes/status/206451… THE VIRAL TAKE: @0xBalloonLover — "anthropic won't let you use fable for biology, chemistry, ai research, or anything that accelerates human progress. that makes it the perfect tool for developing blockchains" x.com/0xBalloonLover/status/… POWER CONCENTRATION: @ClementDelangue (HuggingFace CEO) — "Concentration of power, capabilities and economic wealth is the biggest risk in AI. We need open science and open-source more than ever!" x.com/ClementDelangue/status… @jeremyphoward (fast.ai) — "Anthropic has chosen the opposite of the safe path: they are allowing themselves, the current top lab, to use their top model for frontier AI research. They've said they'll sabotage others who try." x.com/jeremyphoward/status/2… @gneubig (Graham Neubig, CMU) — "First they came for the model builders... I feel we're getting a glimpse of a future where AI is only provided to a privileged few, and that's not a future I want to live in." x.com/gneubig/status/2064451… OPEN RESEARCH: @askalphaxiv (AlphaXiv open science) — "As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development." x.com/askalphaxiv/status/206… @willccbb — "it is the first publicly available model that i am explicitly not allowed to use for my work, because anthropic holds the view that the work i do to facilitate open model research is harmful. capability and alignment research are coupled. anthropic wants to be the only lab." x.com/willccbb/status/206450… NOUSRESEARCH / HERMES (which Anthropic has nerfed multiple times): @Teknium (NousResearch co-founder) — "What's crazy to me is that Fable is blocked from life sciences broadly, nerfed even if you get passed the classifiers and filter level blocks. The whole point of AGI/ASI is to cure all diseases. Everything else is just nice to haves. But Anthropic wants to close off that path." x.com/Teknium/status/2064570… THE MECHANISM: @kimmonismus — "When the model is used for frontier LLM development, it apparently does not simply refuse or warn the user. Instead, it quietly limits its own effectiveness through techniques like prompt modification, steering vectors, and PEFT." x.com/kimmonismus/status/206… MEDICAL COMMUNITY: @DeryaTR (immunologist, BSL-3 certified) — "The word 'cancer' is flagged as a biosecurity risk by Claude Fable 5! I also tried to code a website on cancer mutations & Fable 5 was immediately removed from my list!" x.com/DeryaTR/status/2064414… @DeryaTR — "I can't even say 'hello' to Fable 5 except in incognito mode (memories off), because it knows I am a biomedical researcher!" x.com/DeryaTR/status/2064602… @DeryaTR — "I am not even allowed to use Fable 5 with memories on! Apparently the model thinks I am a biosecurity risk, though I had been certified to work in biosecurity level 3 labs! Not a single Anthropic person has tried to reach out to help either!" x.com/DeryaTR/status/2064605… @banteg — "claude fable 5 refuses completely benign tasks like analyzing bloodwork." x.com/banteg/status/20646076… @bneyshabur — "Working on AI for cancer? Sorry, I can't help you. Working on AI for Alzheimer's Disease? Sorry, I'm becoming a bit dumb when it comes to the AI part of it." x.com/bneyshabur/status/2064… SUBSCRIPTION CANCELLED: @bubbleboi — "Have canceled my team subscription for Claude Pro. Idc how good that model is, it's not good enough for me to support people who actively stifle innovation and gate keep knowledge that they didn't even create." x.com/bubbleboi/status/20646… BILLING AND PRIVACY: @GergelyOrosz (The Pragmatic Engineer) — "Things I really dislike about Fable: 1. Anthropic collects my prompt history, stores it, and does whatever they want with it for 30 days. No opt-out. 2. They can nerf their most expensive model without telling me, billing me the same amount, wasting my time. Whenever they want." x.com/GergelyOrosz/status/20… THE KARPATHY QUESTION: @SanthProject — "the old @karpathy would never support a company that fucks other llm researchers. Were the stock benefits that good?" x.com/SanthProject/status/20… THE MONOPOLY CHARGE: @tunguz (TabulAI founder) — "Starting to suspect that Anthropic's putative security and safety considerations are largely posturing and performative." x.com/tunguz/status/20644379… @BlancheMinerva — "Anthropic is choosing to make decisions that make the world a significantly worse and potentially more dangerous place." x.com/BlancheMinerva/status/… @LinusMixson — "Dario personally, and Anthropic as a whole, have been extremely straightforward about wanting a monopoly for a long, long time." x.com/LinusMixson/status/206… @TheAhmadOsman — "I started warning people about Anthropic more than a year ago... Today I am vindicated, everybody knows that company only acts in bad faith." x.com/TheAhmadOsman/status/2… WHY REGULAR PEOPLE WILL EVENTUALLY CARE: @DanJeffries1 — "The fury is real and what all of us in the open community have been saying for years and yet regular folks don't get it yet because nothing they care about is restricted or taken away for 'safety.' They will care a LOT in the future when AI is integrated into every aspect of [life]." x.com/DanJeffries1/status/20… Full analysis: alignednews.com/ai

“Claude Fable 5: The most powerful model we’ve ever shipped… Safe for general use™ (unless you need to do something even remotely useful)”

fun fact: meta let fraudster take over my fb.com/can username before all this, and i lost my 10 year instagram account too which had years of friends. meta is a user-hostile company.

The most expensive resource in a company is skilled attention. AI spend is becoming a close second. Great operators allocate both carefully. The future of AI feels less like choosing one model, and more like directing work to the right one. Research... Coding... Analysis... Writing... Each task has an optimal destination. Coworker.ai makes that allocation automatic. I spent some time looking through what they're launching this week... It's an interesting idea, you know? Routing each AI task to the most efficient model automatically instead of forcing everything through one model. Who doesn't love more output from the same budget? Details here: coworker.ai/

"Lillian, this all sounds great in theory, but how do you know if our go-to-market strategy will actually work before we spend months building funnels and scaling paid ads?" I get this question three times a week. Here's my answer. You don't validate with research. You validate with revenue. Here's the 3-step test I use with every client. I call it the 5-Day Market Reality Check. Step 1: Run a 2-week competitive analysis You're looking for momentum signals, not a comprehensive picture. Is the market growing or stagnating? That's the only question you need answered at this stage. Step 2: Set up a simple paywall test No complex funnel. A basic gate that requires a small payment to access your core value. That's your truth test. Step 3: Watch the wallets, not the words Surveys lie. Focus groups lie. Actual payments don't. Two to four weeks of real buying behavior tells you everything that six months of market research would obscure. I used this with Morgan, who had two built marketplaces and needed to choose between them fast. Tech hiring (saturated) vs. remote jobs (emerging). We ran the test. The data was unambiguous. Morgan pivoted, generated first revenue in weeks, and avoided six months of building in the wrong direction. I keep a running spreadsheet of these tests across industries. The pattern holds every time. Follow me if you want the actual framework templates. I share the working systems, not just the case studies. #GoToMarket #StartupStrategy #MarketValidation

Most "AI-native" marketing teams aren't AI-native at all. They're just 5 people using ChatGPT separately. ... Same tools. ... Different prompts. ... Zero shared memory. It looks sophisticated from the outside. Under the hood, it's still human-to-AI, one person at a time. The difference between "using AI" and becoming AI-native comes down to architecture. Here's how I think about the 4 levels: 𝗟𝗲𝘃𝗲𝗹 𝟭: 𝗔𝗜 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲 You → ChatGPT or Claude. Research. Writing. Summaries. Meeting notes. Useful. It's also where most teams stay because the gains are individual. Nothing compounds. 𝗟𝗲𝘃𝗲𝗹 𝟮: 𝗥𝗼𝗹𝗲-𝗧𝘂𝗻𝗲𝗱 𝗔𝗴𝗲𝗻𝘁𝘀 Content agent. SEO agent. Paid media agent. Outbound agent. Sales-call agent. Each agent owns a workflow, not a task. The question shifts from: "What can AI do?" to "What should this agent own?" 𝗟𝗲𝘃𝗲𝗹 𝟯: 𝗧𝗵𝗲 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗕𝗿𝗮𝗶𝗻 Agents stop working from isolated prompts. Instead, they pull from shared context: • Customer calls • ICP research • Winning campaigns • Brand guidelines • Objections • SOPs • Case studies This is where AI starts compounding. One insight becomes available to every agent. 𝗟𝗲𝘃𝗲𝗹 𝟰: 𝗖𝗹𝗼𝘀𝗲𝗱-𝗟𝗼𝗼𝗽 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗦𝘆𝘀𝘁𝗲𝗺 Sales calls create content angles. Content generates leads. Leads improve outbound. Outbound updates the ICP. The ICP updates the company brain. The company brain improves the agents. The marketing team stops behaving like a collection of specialists. It starts behaving like an operating system. We're at Level 4 at Data-Mania. 𝗪𝗵𝗮𝘁 𝗜'𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱 𝘀𝗼 𝗳𝗮𝗿: - The bottleneck is better knowledge architecture. - Most teams are still experimenting with basic prompts. - The teams that win build systems that learn autonomously. Which level is your team at today? 1, 2, 3, or 4?

I'm not gonna lie, the @Meta layoffs are some of the most dystopian I've ever seen. They got told to work from home, they were sent the emails at 4AM in the morning. Those who weren't impacted have software on their computer that tracks their every move, preparing AI to take their job as well. They're literally training the AI that will eliminate their position as well. Meanwhile, Meta is raking in RECORD PROFITS. I am a massive, unapologetic AI enthusiast. Yet, this is NOT the future I had in mind. I wish for Meta to crash and burn. This is not the way. Literally nobody benefits from this.

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

If AI can mistake a Reddit joke for advice, it can misunderstand your website too. It copied a joke from Reddit. Funny. But it exposes a serious problem for business owners. AI tools like ChatGPT, Perplexity, and Gemini only recommend websites they can clearly understand. We ran our site through Framer’s free AEO Scanner. Score: 88/100. But it flagged one issue I completely overlooked: Not enough contextual internal links. I assumed navigation and footer links were enough. They’re not. AI uses in-content links to understand: ➤ Which pages matter most ➤ How topics connect ➤ Which page is the source of truth If your blog posts don’t link to related services, pricing pages, and core landing pages, AI may struggle to understand your business. And if AI doesn’t understand your business, it won’t recommend it. Framer’s AEO Scanner found this issue in under 10 seconds. It shows: ➤ How AI-readable your site is ➤ What’s hurting visibility ➤ What to fix first The tool is free and works on any website. If your site generates leads, I’d check your score today: framer.com/aeo --- #framerpartner image credit: @petergyang

How to know if something is written with AI: it spends nine paragraphs telling you what it isn't.

This is INSANE!! We literally just replaced four ad dashboards with one chat window. If you manage paid ads across multiple platforms, you're probably wasting hours every week on dashboard switching. Case in point, running Google, Meta, LinkedIn, and TikTok in one sprint would mean juggling: ➤ 4 dashboards ➤ 4 billing systems ➤ 4 completely different mental models That overhead slows testing velocity more than budget constraints ever could. We recently added Synter to our stack, and - poof, overnight we’re able to replace all four ad dashboards with one chat window. Unbelievable (but true). Here’s how it works: It runs all four platforms from a single interface, and because it works with Claude and MCP clients, we’re able to manage everything from the same workflow we’re already using. Imagine prompting: … "Shift budget from Meta to LinkedIn." … "Launch a retargeting campaign for this segment." … "Generate three ad variations." ✅ Just one prompt and DONE. The good news is that if you're running paid for a lean team or solo across multiple channels, the setup is super straightforward. Check it out here today: syntermedia.ai/?utm_source=i… #SynterPartner

8 GTM truths most startup teams learn too late. Your growth team shouldn’t look like an ad agency. → It should look like your engineering team. You don’t need more campaigns. → You need one system that compounds. “Let’s try this tactic” is not a strategy. → “Let’s test this hypothesis with clear success metrics” is. Attribution isn’t a nice-to-have. → It’s the foundation of every decision. Repeatable > Remarkable. If your marketing team can’t explain the conversion math, → You hired the wrong team. Most “marketing problems” are actually systems problems. If you can’t connect a dollar spent to a dollar earned, → Stop spending until you can. Follow me for practical frameworks on building AI-native GTM systems that scale.