The takeaway from Fable 5 being BANNED by the government: GET GOOD AT LOCAL MODELS SO YOU HAVE 100% CONTROL. My entire weekend was going to be building my craziest ideas with Fable 5. That's now cancelled. So instead of building with Fable this weekend, I've decided I'll go deep on local models: 1. Start with the runtime. Download Ollama or LM Studio first. This is the thing that actually runs models on your machine. 2. Match the model to your hardware. A model's size is measured in billions of parameters (7B, 32B, 70B). Bigger is smarter but needs more memory. Rule of thumb: a 7B model runs on almost any laptop, a 32B needs a good Mac with 32GB RAM, a 70B needs serious hardware like a DGX Spark or a maxed-out Mac Studio. 3. Know which model for which job. Qwen 3 is the best all-around choice for most tasks. DeepSeek for reasoning and coding. Gemma 4 when you need something tiny that runs on a phone. Llama when you want the biggest community and the most fine-tunes. 4. Quantization. You can shrink a model to run on weaker hardware with barely any quality loss. Look for versions labeled Q4 or Q5. This is how a model that "needs" a server runs on your laptop. Learning this one concept changes everything. 5. Connect it to your agent. Point Hermes or your agent stack at a local model. 6. Context window is your real constraint locally. Cloud models give you huge context for free. Local models make you pay for it in memory. A bigger context window eats RAM fast. Keep your sessions tight and your prompts lean or your machine chokes. 7. Learn to give local models tools. A smaller local model with web search, file access, and code execution beats a giant model with none. The capability gap closes fast when you wire up the right tools. The model is the engine but the tools are the wheels. 8. Fine-tuning is more accessible than you think. You don't need this on day one, but know it exists. You can take an open model and train it on your own data so it gets good at your specific domain. I'll probably do a breakdown at some point on this @startupideaspod if people are into it. The lesson from this ban is basically don't build your entire workflow on something that can disappear with a single letter. Own part of your stack. Local models are insurance. It reminds me when people realized they don't own social media accounts. And then you saw people build email lists etc. I remember running a startup and my biggest traffic source was organic FB. All of a sudden, algo changed, and I lost 99% of my traffic. Same sorta moment (but bigger) for AI. This is a wake up call.

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.

stop what you're doing… here's 14 things you gotta do with AI: 1. export your ChatGPT Claude memories, context, and workflows so you know what each model knows about you that the other doesn't 2. generate DESIGN .md CLAUDE .md AGENTS .md for your agentic repos 3. build a model agnostic skills library that Claude Code, Codex, OpenClaw, Hermes, and Cursor can all read from the same symlink 4. version your system prompts in git with PR review so silent drift gets caught in diff instead of in production 5. build a /goal template library covering your top 10 recurring workflows so you stop rewriting the same 200 word prompts every Monday 6. set up a daily report and a weekly standup with your agent that reads yesterday's commits, tasks, memory, your calendar, and your inbox, then briefs you in 60 seconds 7. wire your Obsidian vault as the read/write target for every agent so research, decisions, and meeting notes land as linked markdown by default 8. build a Karpathy-style autoresearch loop where your agent logs its own failures, proposes skill patches, and you approve them weekly 9. design a UGC AI character (and/or mascot) with 35 emotions for brand world building so every loading state, every error screen, and every post in your feed shares the same look 10. cancel 2-3 SaaS subscriptions by replacing them with agents and skill files 11. run a security agent across all your repos weekly to catch npm attack vectors, prompt injection, leaked .env, and MCP misconfigs before someone else does and you regret it 12. build a prompts library of image, video, and audio generation templates so you stop relearning Nano Banana, Grok, Seedance, and ChatGPT syntax every time there’s a new release 13. build a personal benchmark of 20 tasks from your real work so you can A/B every model release against your actual workflow instead of the bogus leaderboards 14. build daily cron jobs for your data ingestion across the topics you actually care about: research, content, trading, competitive intel, etc. the next few months will separate the operators using complex systems from those still manually typing prompts one at a time. these are table stakes. act accordingly.

xAI has expanded access to X Premium subscribers in Hermes Agent. Enjoy!

this is amazing. do this. get codex to write its own /goal /goal gpt-5.5 high fast mode is the highest leverage ai agent configuration available today

tips for codex goals sure you can use /goal but it also has a set_goal() function its almost better to prompt the model to set its own goal, it will likely write a better prompt than you

it costs less for claude to hire a dedicated copywriter than it would for one of their senior marketers to quality control LLM outputs… not to mention that the copywriter they hire will 100% use an LLM to help in the copywriting process don’t see why this is something controversial

spent a few weeks deep in Hermes Openclaw earlier this year... over-offloaded everything, daily maintenance got brutal and output rarely hit switched back to Claude Code via Telegram and rebuilt the workflow from scratch then GPT-5.5 dropped... then GPT-Images-2... then GPT-Realtime-2 and Hermes quietly became THE move > best coding model > best daily model > best image model > best voice model all running through ONE subscription on your own agent takes 5 min to setup on a VPS, plug in your GPT sub, hand your friends and family an agent that generates awesome images, processes voice notes, builds anything and actually remembers everything this thing rarely misses anymore

hear me out anon. whatever you're using right now, drop it for one night. install hermes agent. set a /goal for that one thing you've been thinking about but never started. go to sleep. just try it once.

not sure if btc continues to provide diminishing returns but it is certainly possible (i choose to believe it wont for now) but alts (on average) will continue to get more difficult and dangerous to trade imo, irreversible trend. (1) massive competition amongst increasingly sophisticated buyers (who simultaneously believe less) (2) primarily traded on perps/with leverage. (3) huge dilution in coins with mkt valuing stuff high by default without justification (4) launch FDVs always capturing 100% of optimism for the asset without respecting price/valuarion (5) too much pre-market price discovery for (4) to be safe the average 2017 buyer buys spot and hodls weeks/months cos they believe, add on the way up, asset was trading at low val early so works out. average 2025 buyer is buying on perps without checking the valuation and sells whenever their PNL goes red or force sells in liquidation. however, it will remain the best place for returns for smart ppl. skill expression and asset selection is much more important. patience much more highly rewarded over being "early" on liquid markets last few years. and then outlier assets will continue to exist, maybe 1 every couple of years, and when they turn up you can turn brain off and 2017 it. imo anyways (hopefully)

had a fantastic time with Doc, VOD is available for replay if you guys wanna check it out will def have to do another one soon but in the meantime big thank you again to Doc and all of you for tuning in <3 see you bozos soon

current market thoughts: some alts straight up look macro bottomed, but that doesnt mean a bull market has to start today, they can take forever to build up enough steam for that, mini rallies like 2022 most likely. alts with narratives = tradable alts without = require crime, not worth your energy btc in 60ks is a steal, i believe in new ATHs so imo free sized spot 2x. take it with a grain of salt if you must- im a delusional btc believer. imo current btc rally most likely nearing the end soon as we trade into HTF downtrend structures. 28% in about 30 days. I was a bull from 60s and fighting off war fud, equities weakness etc but now imo the EV for bulls has diminished dramatically "if ES pulls back, then BTC dies" is low EV HTF signal, we more often then not front run equities weakness on HTF then stall out as they find a bottom. ES isn't a good leading signal in my experience. thoughts, not predictions.

compute is fucking king and gpt codex currently wears the crown, look at this thing: > guy tried to recreate Maplestory (played by 100Ms globally) with codex > 30 minutes in codex already one-shotted the design, gameplay and characters. > only used 5% of his 5 hour limit. do you understand how fucking insane that is? 2 months ago openai sucked at coding.... software engineers universally dismissed codex as a toy vs. claude code. Now not only is codex 5.5 the leading coding ai, it also thinks for longer, works 24/7 and is AVAILABLE TO YOU i love claude, i really want to try mythos but i can't. either thats because it's too dangerous or anthropic is still scaling compute either way - openai has the compute, they're resetting limits every other day and it's proven you can build insane things with it compute = abundance

I put everything into crypto for 3 years straight, only to walk away with 5% of what I made. The real cost though, is a mental one. The ones I care about who I could have, should have, helped. Instead I let greed get the better of me and in this game, you only have yourself to blame. What is only possible in crypto, is also only possible in crypto. Manage your greed or be punished by it a thousand times over. I share this in hopes to help just one person who’s currently at the other end of my situation, pushing for me. Be grateful for what you have and if you already have the life you dreamt of, secure it at all costs.

i'm done. codex is fucking incredible after heavily using claude code for over 13 months, i've moved to codex opus 4.7 is painfully slow and takes 5-10 mins for a one-liner. the app is super buggy and flickers constantly. low thinking is useless. and they keep nerfing the model for some reason?? codex's new app is genuinely beautiful and gpt-5.5 thinking-medium is the perfect balance ngl @sama you cooked on this one

A common dynamic I observe with AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want. This applies across design, code, legal, and more. If I don’t know code very well, every piece of code it writes feels very impressive. Once you know what something should feel or look like, it becomes almost impossible to guide AI there. And you definitely can’t one-shot it.

The AI space is accelerating so damn fast every week. Here’s what I’ve been doing the last month. If you’re not doing most of this, the space has already moved past you. And that’s just the truth. Your code either has DESIGN .md, AGENTS .md, and SKILL .md at its repo root, or every agent tool run could be a hallucination. You need design and structure tokens locked, tone declared, and your stack set up right. You will stop having to handhold your agents the moment your system reads itself. Your security either runs on cron jobs or it doesn’t run. You should have reports on literally everything. If a human has to remember it within your system, it’s already failed. Your morning prompt should be one line at this point: what did I do this week that should already be automated? Your agent should already know this. You automate the cron job. If you’re not doing this, you are in fact behind. Your stack should run multiple models. Frontier models for testing reasoning. Open weights for maxing your token output. Local for anything you don’t want an AI lab logging forever. One vendor for you is likely a major vulnerability. Oh you’re a Claude only maxi? Well that’s your major flaw. Your skills, prompts, memories, and configs should all live in your own repo. Not in some frontier model stack. Every platform is renting you their tools. If you don’t own your own workflows, you’ll be renting your own career back from them. The cost of content is becoming very negligible. AKA you need to be learning to show your human side when every other person can create content at will. Everything else is just noise. Stop only being a power user of AI. Become your own operating system.

Had a Jane Street interview in 2013 that still bothers me. It was my 6th round. Final interview. The guy walks in carrying no laptop, no notebook, just a cold brew and what I later realized was a single IKEA tea candle. He writes on the whiteboard: food: $200 rent: $800 utilities: $150 candles: $3,600 family: dying Then he turns around and says, “Optimize.” I laughed because I thought it was a culture-fit bit. He did not laugh. So I said, “Well, obviously you spend less on candles.” He says, “Assume candles are non-discretionary.” Okay. I start building a model. Basic constraint satisfaction. Family survival as a soft penalty. Candles as a state variable. Maybe there’s an arbitrage where you buy wholesale paraffin and convert the $3,600 line item into inventory. He stops me. “You’re thinking like a consultant.” That’s when I knew I was in trouble. He says, “Give me a bid-ask on family dying.” I say, “What?” He says, “You’re long candles, short family. Where do you make markets?” I try to recover. I say the real issue is liquidity: rent and utilities are fixed, food is elastic, candles are emotionally inelastic. Therefore the optimal strategy is to securitize future candle enjoyment and borrow against it. He nods for the first time. Then he asks, “What time do you sell the candles?” I say, “Whenever the market is liquid?” He says, “Be more specific.” I say, “Uh… 10 a.m. Eastern?” For the first time, he smiles. He goes, “Every day?” I say, “Every day.” He says, “In size?” I say, “In size.” He says, “And what do we call that?” I say, “Market manipulation?” The room gets very quiet. He looks disappointed and writes something down. “No. We call it providing liquidity to candle ETFs during the U.S. cash open.” I try to save it. “Right. Of course. The family isn’t dying because we underfunded them. They’re just experiencing temporary price discovery.” He nods again. Then he points back at the board. I had missed it. The utility bill was $150, but candles provide light. You can zero out utilities. I update the budget: food: $200 rent: $800 utilities: $0 candles: $3,750 family: still dying, but now in a more capital-efficient way He says, “How confident are you?” I say, “0.95.” He smiles and circles candles. “0.95 huh?” Then he asks me to estimate how many leveraged longs get liquidated if we dump $3,750 of candles at 10:00:01 every morning for 90 consecutive trading days. Needless to say I did not get the offer.

I automated my content engine and 2 hrs/day dropped to 10 min [ what’s new in v2 ]: - 9 platforms scraped while I sleep → 2,000 topics/day - a 5-signal scoring brain that filters down to the 10 that matter - voice DNA writer.. same tone, different structure every time - a self-learning loop that remembers every approve and decline - profile DNA — knows exactly what goes viral on MY account v1 was a brain with no body v2 has eyes, a filter, and memory fully automated Here’s how to build it step-by-step ↓ [ The architecture]: /content-engine ├── scrapers/ (9 platform scrapers) ├── extension/ (chrome ext for X, linkedin, reddit) ├── ai/ │ ├── ranker.py (5-signal scoring brain) │ ├── content_writer.py (voice DNA structures) │ ├── profile_analyzer.py (your positioning DNA) │ └── sentiment_analyzer.py ├── publisher/ (export time slot scheduling) ├── gui/dashboard.py (streamlit command center) ├── ingest_server.py (local server on localhost) └── data/content_engine.db (everything stored locally) let me walk you through each layer ↓ LAYER 1: Research engine 9 sources scanned 24/7 (X, reddit, YT, HN, github, trends chrome ext for reddit and linkedin) every post you scroll past gets tagged and stored locally LAYER 2: Scoring brain every topic scored on 5 signals: - freshness (0.20) - velocity (0.25) - virality (0.25) - relevance (0.20) - uniqueness (0.10) velocity 8 → forced min score of 7. catches late bloomers that suddenly explode 2,000 topics → top 10 ranked LAYER 3: Voice DNA writer not one structure every time. system picks the format: - short take - tactical playbook - QT contrast - contrarian - resource drop - proof post a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words LAYER 4: Dashboard Streamlit dark theme. 5 tabs review queue = tinder for content. swipe approve, swipe decline LAYER 5: Publishing no auto-posting. zero account risk approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post also auto-drafts a linkedin version of every approved tweet LAYER 6: Self-learning loop every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain month 1: you approve 30% month 3: 70% pre-filtered month 6: 10 min/day LAYER 7: Profile DNA analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account the scoring brain uses it to prioritize what already works for you daily run: open dashboard → 10 min reviewing → post 3x → close total cost: ~$15/month everything else: local, sqlite, no cloud, no subscription unfortunately I couldn’t paste in long-form format initial description which was made before but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code reply "ENGINE" RT and I'll DM you access to test it (follow me first so I can write) save this so you don't lose it