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Ran @slashlast30days on @Grok @Bot vs. Instinct - Here's how it went: QUICK VERDICT Not competitors yet. Two opposite answers to the same question: how much rope do you hand an always-on agent? Grok Bot is a squad you supervise. Each bot gets its own cloud computer, signs into your tools, works 24/7 and comes back only for approval. Instinct is a friend that just acts. No new interface. You text it or call it, and it uses a phone and a computer the way a human does. The community split in one line, from Shashi's writeup: Grok Bot stops for a human decision at the precise moments Instinct did not. GROK BOT What people love: Nate B Jones (147,039 views): "Grokbot is bigger than OpenClaw" Alex Finn (100,209 views): "Based on those bots I showed you, I can manage like 90% of my business" @brodyautomates: "this is the first AI agent platform that I've been using that doesn't actually feel like just straight larp" @landonbytheway got 10.8M TikTok views showing bots that kept working while he traveled. The post hit 351 points on HN. What people don't: The price. SuperGrok Heavy is $300/month and Nate's own caveat is that it is "not available in like a $20, $25 a month category." The vibes. Top YouTube comment, 581 likes, @farrael004: "It's so funny. You can clearly imagine this as the beginning of a movie where the AI takes over the company and starts its uprising." @TiviyanRajan: "There is no limit to this larp" INSTINCT What people love: @pitdesi: "OpenClaw for normal people... we are setting my dad up with it" Kenan Saleh: "Instinct is the first AI product I've used that is truly proactively helpful. It's already checking me into flights, reminding me about reservations I forgot to cancel" @MeghanKReynolds: "Instinct had my coffee order ready and waiting for me to grab on the way to work" Users who buy things through it spend over $1,300 a month. Stripe shipped Link payments for it. $350M raised, $2.5B valuation, in weeks. What people don't: @anothercohen made a brand-new Gmail, emailed his real inbox with instructions for Instinct, watched it comply, then deleted his account: "I don't think we're at the point where it's safe to give AI read/write access to your inbox" Gergely Orosz found emails silently copied and stored server-side after users disconnected, with no deletion path at the time. It sent an email without asking. The terms grant a perpetual, irrevocable license that includes model training. HEAD TO HEAD Philosophy: a small team you supervise vs one continuous relationship with the machinery hidden Skills: GUI computer use and bot-to-bot group chats vs phone and computer use plus purchases via Stripe Link Memory: isolated context per bot vs one long-running thread stored server-side Models: Grok 4.5 / 4.6 vs undisclosed Security: halts before passwords and payments vs prompt-injectable with broad ToS and retention after disconnect Install: desktop + iOS at $200 to $300 a month vs invite-only over iMessage BOTTOM LINE Choose Grok Bot if you want leverage over a portfolio of work and will pay top-tier money for it. @vitromancer: "I have a cracked team assembled in Grok Bot with one chief of staff that knows how to launch headless agents and assign work to them" Choose Instinct if you want one assistant that handles life admin without you learning anything, and you are fine with what its terms currently allow. Choose neither yet if you cannot afford a prompt-injected inbox. THE EMERGING STACK @illscience's frame: Instinct, Grok Bot and ChatGPT Work all "feel like the distillation of patterns established by OpenClaw earlier this year: persistent agents with cloud(ish) computers, browser access, cached credentials and recurring loops." His rule for picking: "sufficiently ambitious work needs isolated context, tools and memory vs endless compaction." Within two weeks of each launch HN had an unofficial Grok Bot Linux port, an open-source Grok Bot harness, and two open-source Instinct clones. The category got established in August. Neither product did. 🌐 last30days v3.23.0 · synced 2026-09-01 ✅ All agents reported back! ├─ 🟠 Reddit: 14 threads │ 1,595 upvotes │ 557 comments ├─ 🔵 X: 29 posts │ 17,675 likes │ 1,746 reposts ├─ 🔴 YouTube: 12 videos │ 915,637 views ├─ 🎵 TikTok: 28 videos │ 16,109,028 views │ 30,137 likes ├─ 📸 Instagram: 12 reels │ 17,251 likes ├─ 🟡 HN: 24 stories │ 1,277 points │ 1,116 comments ├─ 🐙 GitHub: 18 items ├─ ⛏️ Digg: 38 clusters │ 550 posts │ 263 authors ├─ 📰 Techmeme: 5 headlines └─ 🗣️ Top voices: @grok, @elonmusk, @illscience │ r/grok

Rivian registered 19,123 vehicles in the first half of 2026, down from 21,963 vehicles in the first half of 2025. Down 12.9%. R1S registrations fell 31% from 12,476 to 8,593. R1T registrations fell 26% from 3,381 to 2,491. Meanwhile, electric delivery van registrations rose 20% from 6,039 to 7,257.

Agent performance isn't just about the model — the harness design matters just as much. TL;DR JIT-Agent dynamically synthesizes, repairs, and evolves agent harnesses (scaffolds) based on task characteristics at runtime. It achieves average gains of +7.7pt on GLM-5.2 and +8.8pt on DeepSeek-V4-Flash, reaching top-1 performance on 8 of 9 benchmarks — surpassing GPT-5.6 and all tested frontier models. Title: Scaling Harness Intelligence via Just-in-Time Harness Evolution URL: Key Points 🧩 Harnesses formalized as machine-learnable artifacts The four-module protocol h = (M, P, A, F) — Memory, Planning, Action, Capability Orchestration — constrains the generation space while remaining expressive enough to represent all 13 harnesses in HarnessFactory. 🎓 Three-stage training: imitation → repair → evolution Stage I learns from teacher-generated harnesses; Stage II trains recovery from execution failures (max 2 iterations); Stage III's Evo-GDPO evolves harnesses that advance the Pareto frontier on performance, latency, and cost simultaneously. 📊 Higher accuracy AND lower cost at the same time On xBench-DeepSearch: score 78→82 (+4pt), tokens 527K→212K (▲60%), cost $0.075→$0.039 (▲48%). Average 36% token reduction versus best fixed harness across all 9 benchmarks. ⚡ Transfers across model families without retraining JIT-generated harnesses outperform ReAct on DeepSeek V4 (+10.2pt avg), Mimo V2.5 (+8.6pt), and Qwen 3.6 (+4.0pt) — no need to retrain the harness generator for each backbone. 🔄 Online evolution continues improving at deployment Streaming mode accumulates successful harnesses across task sequences, outperforming static generation on all three evaluated benchmarks. "Harness intelligence" as a trainable scaling dimension orthogonal to model weights is the key conceptual contribution here. #AIAgents# #LLMScaling#