Content creator | AI researcher & builder | AI insights from 2030 | @beyond_xai

San Francisco
Three engineers from SpaceXAI, DeepMind and Thinking Machines just gave a free 1-hour session of how to actually build an AI career, from 0% to 100%: • 10% → 12:26 - what actually gets you hired at tier-1 AI labs, from someone who's been through it • 30% → 20:05 - the billboard method: applied everywhere, became the youngest intern the NYT ever had • 55% → 28:00 - 300 applications, all rejected except three. that's how you get a PhD-level role without a PhD • 80% → 44:02 - less than 1% of the world has touched Cursor or Claude Code - that gap is the opportunity • 100% → 1:00:58 - how much code they write by hand today by tier 1 engineers: 0%, 0-5%, 5-10% most people are optimizing one perfect application - they were maximizing surface area watch it today - then read below on how to rebuild a business supply chain with AI from scratch ↓
I just rebuilt the business entire supply chain with Drex. From order to outcome. Every decision visible. This is Drex from Nace. ai running a real business process end to end: > Order comes in → documents get classified, checked & reconciled > Every checkpoint is one Drex decision: pass, repair or escalate > Something breaks mid-flow? It replans sourcing and revalidates instead of stalling > Only the real edge cases go to a human > Case closes with a full decision trace you can export 8 stages, one flow: intake → commercial controls → procurement → fulfillment → trade docs → transport → delivery → settlement & audit Synthetic documents, real model decisions Drex doesn't write essays. It scores the options and picks one, fast enough to sit inside every step of a workflow Link below
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I just rebuilt the business entire supply chain with Drex. From order to outcome. Every decision visible. This is Drex from Nace. ai running a real business process end to end: > Order comes in → documents get classified, checked & reconciled > Every checkpoint is one Drex decision: pass, repair or escalate > Something breaks mid-flow? It replans sourcing and revalidates instead of stalling > Only the real edge cases go to a human > Case closes with a full decision trace you can export 8 stages, one flow: intake → commercial controls → procurement → fulfillment → trade docs → transport → delivery → settlement & audit Synthetic documents, real model decisions Drex doesn't write essays. It scores the options and picks one, fast enough to sit inside every step of a workflow Link below
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Try Drex on your own workflow: nace.ai/drex
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I’ve set aside $20M because I want more startups to grow with us. Higgsfield crossed a $1B revenue run-rate today. We’re celebrating this with 100% cashback on Higgsfield API spend with Genjutsu and Cinema Studio available. When you're a small startup, early support can change how quickly you build. Special thanks to @gregisenberg for showing how to get started with GPT-6 Astra + Higgsfield API, step by step. I hope this helps you ship faster and grow into one of our biggest customers.
We're announcing 100% cashback on every model on the Higgsfield API platform. Seedance 2.5, Kling 3.0, MiniMax H3, Wan 3.0, and more. Spend on the API and get your cashback instantly, up to $100,000 per business. $20,000,000 cashback pool. First come, first served. You helped us reach a $1B run rate. We’re celebrating by putting $20M back into what you build next. Unused cashback expires on September 30.
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SpaceXAI engineer, Nick Miller: "99% of people run one GrokBot and call it done, only 1% build teams of bots that talk to each other. i'm running a team of 20+ GrokBot agents in a loop & graph. I have a Chief of Staff bot, PM bot, QA bot and 15+ workers - that's the new stack" In a 27-minute demo, a SpaceXAI engineer explains how to build a team of GrokBot agents from scratch worth more than a $500 agentic engineering course skip Netflix today and watch this, then read how to build a fleet of GrokBot agents in the article below
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SpaceXAI engineer just released a 1-hour workshop on building an effective team of GrokBot agents from scratch: • 10% → 8:48 - GrokBot effective team blueprint: CloseBot, ProdBot, StalkBot, ProtoBot • 30% → 9:34 - building graphs, loops with GrokBot + automations • 55% → 18:19 - designing Chief of Staff agent from scratch • 80% → 27:30 - training a team of GrokBot agents, based on your data • 100% → 28:55 - building a “cleaner” GrokBot for context managing One agent saves you an hour - a squad of them replaces the staff function you can’t afford to hire. Watch it today - then read the full bot orchestration playbook below ↓
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TyperSafe Founder, Diogo Almeida just gave the best 2-hour breakdown on how to actually master Jev, from 0% to 100%: • 10% → 21:43 - building an eval for your own workflow with JEV • 30% → 55:49 - choice, score, noul - new types of code mapping with JEV • 55% → 1:12:36 - cascade: confident answers ship, uncertain ones go to a bigger model • 80% → 1:37:12 - JEV use cases: dark data, real-time calls, verifying every LLM in your stack • 100% → 2:11:50 - building coding agents with JEV this is worth more than another $500 course on building agents with Claude watch it today - then read the full Jev playbook below
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1 day left to lock in up to 50% OFF Higgsfield API. Build your own AI app with our product endpoints, including: • Higgsfield Genjutsu • Cinema Studio 4.0 • Higgsfield Soul Plus all frontier video and image models through the same API.
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SpaceXAI engineer, Lauren Tan: "99% of people use GrokBot just for 1% of its real power. They run 1 agent without "loop" & "graph" last month my team of 30+ GrokBot agents shipped 2000+ PRs, fully autonomous. Chief of Staff, two PM agents, 20+ coding agents" in 38-minutes, a SpaceXAI engineer explained how to build a team of GrokBot agents that work while you sleep this is worth more than a $500 agentic engineering course skip Netflix today and watch this, then read how to build a fleet of GrokBot agents in the article below
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Ops engineer energy: "99% celebrate $140M ARR in 90 days and still use AI like a search box for contracts. only 1% run agents that watch a lawyer redline once, then enforce the playbook on the next 200." That's the loop.
EXCITED TO LAUNCH: Akai (akai.run) Deel added >$140M ARR in 90 days without increasing headcount by automating~600 Full Time Employees' equivalent in work with Akai. Akai was an internal tool to automate our painfully repetitive operations in Finance, HR, Accounts Payable, and Compliance, etc. We never intended to make this a product. But we watched revenue per employee grow from $130K to $215K We built >8k agents that do the work of ~600 employees It had such a dramatic impact on our business that today we are launching it for everyone. How it works: Say you're automating payment reconciliation: 1. Record your screen while manually matching a messy transaction and Akai will capture your screen, voice, server requests 2. Akai will see that you pulled unformatted wire transfer info from an archaic bank portal, put it in some excel sheet, checked NetSuite invoices, payment history, and put a ticket on Zendesk 3. Akai reads between the lines and build a workflow + steps + conditional guardrails. It learns tacit edge cases, like resolving malformed invoice references without you writing a single regex 4. Simply connect NetSuite, your ledger, Zendesk, PSPs, and even legacy bank portals with zero API access 5. Run the workflow and tell it what to adjust in plain English: "strip slashes on wire memos and auto-apply partial payments." It adapts instantly 6. Once it works for you, add 100s of colleagues. Your entire payment ops team forks and extends the workflow for new PSPs, secondary ledgers, or regional settlement rules 7. We automated 85% of our payment reconciliation end to end, eliminating 500+ hours of soul-crushing manual grunt work every single week. Claude Code/Codex can't do this in multiplayer mode. Every person rebuilds the same skill from scratch in their own way. Deel built Akai to: 1. Understand backend operations edge cases (it had to work for our 7000 person team first) 2. Collaborative across 1000s of employees 3. Self-Learning from millions of runs 4. Optimises cost and gets cheaper every run We're so confident that we're announcing an Automation Guarantee: If our engineers can't automate a thousand of hours of work in your first 30 days, you get a full refund. Book a demo: akai.run if you're an exec at a company with hundreds of employees
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Jev Founder, Diogo Almeida (ex-OpenAI): "I am the one who made ChatGPT and who also hates on ChatGPT. Claude Code and ChatGPT are still part of the assistance era - JEV is the next step for LLMs x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like" in a 17-minute tech talk, the Jev Founder explained why current LLMs aren't a thing anymore and what's coming next for AI this is worth more than a Stanford Machine Learning course watch today no matter what, then learn how to become a Jev Engineer in the article below
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Jev Founder, Diogo Almeida (ex-OpenAI): "The next era is not the Claude Code or Codex era, they are still part of the assistance era with human in the loop - JEV is what comes next for LLMs x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like" in 36-minute tech talk, Jev Founder explained why RLHF isn't a thing anymore and how modern LLMs will be built this talk is worth more than a Stanford Machine Learning degree watch today no matter what, then learn how to become a Jev Engineer in the article below
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Jev Founder, Diogo Almeida (ex-OpenAI): "The next era is not the Claude Code era. Claude Code is still part of the assistance era - Jev is the next step Jev is x200 faster, x400 cheaper and has 0 hallucination. This is what comes after RLHF" In 17 minutes he explains why every model you use has a human-shaped flaw baked into it and why Jev is better worth more than a $500 Claude Code engineering course watch today, then read how to actually boost yourself x100 with Jev in the post below
How to use Jev, and where it actually gives you the 100x: setup takes 10 minutes: 1. join the waitlist, people are getting approved same day 🔗 typesafe.ai 2. install the official skill so your agent writes correct calls: - npx skills add typesafe-ai/skills --skill typesafe-ai on Claude Code it's two commands, the marketplace add on its own doesn't install anything: - claude plugin marketplace add typesafe-ai/skills - claude plugin install typesafe@typesafe-ai 3. create an API key in the dashboard 4. in your prompt just say: "use the TypeSafe skill" now the part nobody is posting: the 100x isn't the model, it's where you put it you don't get it by swapping your LLM for Jev you get it by deleting the calls that never needed a language model open your agent and find every call that just picks something: > which tool next > is this spam > is this chunk relevant > does this need a human > is this diff risky none of those are writing tasks they're if statements you outsourced to a frontier model here's the upgrade, in order: 1. replace each one with a typed question Choice picks from up to 255 options, Score places it on a 2-10 level scale, Noul returns a raw 0-1 2. batch them questions in one call run in parallel and barely move the latency, and output tokens are free so ask every question you might need, including the ones you'll throw away 3. threshold on confidence, not on the answer under 0.5 escalate to a big model or a human 0.85+ before anything irreversible 4. never let it invent options build the candidate list in code, from the DOM, the retriever, the tool trace then let it pick 5. put it in the loop, not next to it router picks the cheap model, gate checks the tool call before it runs, judge verifies the output after that's where the heaviest calls in your agent are hiding 6. start with compaction tonight score every tool call, drop the dead ones, keep the survivors verbatim instead of a lossy summary lowest effort win available and you'll see it on tomorrow's bill the honest part: text only right now, no images, no audio and on broad benchmarks it loses to frontier models but somebody ran 18,514 emails through it zero-shot and got 98.33% against a TF-IDF classifier trained on 14,800 labelled examples that got 98.39% no training data, $1.12 total it wins on narrow, well specified decisions which is most of what your agent is actually doing all day today gonna share use case how i integrated it to content creation and how i find winning meta ads now in a seconds...
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i’m a sugar daddy for men with GitHub accounts. Marc got $68k and a Mercedes. you get a shot at $50k for building something people actually use with the Higgsfield API. competition pinned. make me proud.
This company is crazy. After spending $68,000 on my body, they rented me a car to drive to the Hyrox venue. My transformation into a billboard is now complete. Higgsfield also gave me $30,000 in API credits to make marketing videos with AI models like Seedance. I built a little puzzle game to give them away: finish it and verify your email, and I’ll randomly pick 30 winners in 48 hours, each getting $1,000 in credits. The game starts in this tweet, in this photo... It should take you ~15 minutes. Good luck 👀 This little sponsorship experiment made me realize AI has pushed solopreneurship mainstream. Companies are sponsoring influencers, as we see on YouTube. This wasn't the case when I joined X in 2021. All my friends outside our indie-hacking bubble are talking about building their own internet business solo. I think it was meant to happen because solopreneurship unlocks two fundamental human desires: creativity and not-having-a-boss. If I had to bet, we're just at the beginning.
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