Super User Daily: June 23, 2026
Today the whole conversation moved onto the meter. Anthropic flipping one company to per-token billing spiked its bill 700% overnight, Uber capped engineers at $1,500 a month, and a benchmark put a full test run at $4,811 on the flagship versus $948 on Kimi — so the loudest builders spent the day doing math: cheap-model routing, used 3090s in a tower, free models on a box that pays for itself in four months, and proxies claiming to cut tokens 60-95%. Against that backdrop the non-coding wins kept landing: a fund manager's decade of filings distilled into a research skill, a 500-page Italian novel translated for one reader, a TradingView indicator built from a sentence, a Mac mini decorating a 3D office it imagined on its own. And the business stories got younger and richer — a 15-year-old running seven agents at $900 a day, a teenager's $14K/month habit app, a couple's $20K/month camera app — while the OpenClaw crowd quietly migrated to Hermes and the safety crowd kept proving you can't let an agent grade its own homework.
@ilinkCEO_NOW [Claude Code]
https://x.com/ilinkCEO_NOW/status/2068527679616553450
The meter arrived all at once. After Anthropic moved Workato from a flat plan to per-token billing in May, their AI bill jumped 700% in a single day, and the CIO's line was blunt: vendors subsidized usage to get everyone hooked, and the real cost only shows up the moment that stops. Amazon, Walmart, Cisco, Uber and Meta are all now capping employee AI use, with Uber having burned its 2026 budget by April and setting a $1,500/month per-head limit. The sting in the tail is the benchmark: a full test run cost $4,811 on Anthropic's flagship, $3,357 on OpenAI's, $1,071 on DeepSeek and $948 on Kimi, so China isn't matching quality so much as making expensive AI look unnecessary.
@0xPINK3 [OpenClaw]
https://x.com/0xPINK3/status/2068573201685491959
A 15-year-old runs seven AI agents under OpenClaw, ships ten client projects a day, and clears $900-1,500 daily, with Claude Code writing all the code while he just talks. Each agent is a named, independent entity with one job: one breaks down the task, others do research, structure, coding, bug-catching, reporting and deadline-tracking, all running in parallel. He templated the project types (landing pages, bots, parsers, API integrations, dashboards) so the agents kick off the moment he picks one. The whole pipeline runs on a single laptop for a few hundred dollars, and he's turned himself from the person doing the work into the person handing it out.
@nasicaonchain [Claude Code]
https://x.com/nasicaonchain/status/2068762687786414514
A teenager still in school built a $14,000/month app in six weeks with no ads and no audience. It's a gamified habit tracker (XP, levels, leaderboards, a character that yells at you), shipped on Claude Code with a $200/month plan plus Figma, Superwall and a free Supabase database. The entire growth engine was one arbitrage: the app earned a $2-3 RPM, so he paid creators a CPM below that ($1-1.50), and one influencer video pulled ~1M views, 1,800 downloads and $2,000 in a week. He charges $40/year and a $20 offer chases you if you try to leave the paywall.
@boney2r [Claude Code]
https://x.com/boney2r/status/2068764618365747528
A couple built a disposable-camera app called Once and hit $20,000/month in 83 days, refusing to write a line of code until ten strangers committed to using it. The app lets you make a film, set when photos reveal, invite guests, and pool everyone's shots in one shared album. They proved demand by throwing a Halloween party off a broken web version, then built the polished app only after the ten-event commitment landed. The stack is Claude Code, Figma and Supabase, with AI doing everything except design, and pricing scales from $2 for a small party to $50 for a 150-person wedding.
@rugikkk [Claude Code]
https://x.com/rugikkk/status/2068704519454617768
Claude Code ran 36 hours straight and shipped a payment-ready SaaS while he slept, thanks to one change: a meta-planning pass before the master plan. Before any code, Claude stops and asks "what still needs a human here?" — API keys, Stripe setup, Vercel config, PostHog events — then maps and provisions every tool, MCP server, skill and browser session it needs to do that work itself. By hour 30 it was inside the Stripe dashboard wiring checkout and testing a live charge, then Vercel, then PostHog, with no keys pasted and no dashboards opened by him. The framing: the old way is you babysit the agent and click the buttons it can't reach; the new way is the agent reaches the buttons.
@gagarotai200 [Claude Code]
https://x.com/gagarotai200/status/2068626079246700866
Describes turning one AI "employee" into a hundred and growing monthly revenue from 500K to 5M yen. The recipe: have the first AI employee learn the whole business (sales, posting, research, docs, customer service, billing, video editing, analytics), then tell it to decompose the work and spin up specialized sub-employees, each with its own manual, judgment criteria and templates. The org chart becomes human-as-CEO, parent-AI-as-manager, child-AIs as execution staff, Obsidian as the company brain, and Codex/Claude Code as the execution force. His point: the future company adds AI staff before it adds human staff, and a one-person CEO can hold the execution power of a hundred.
@masahirochaen [Claude Code]
https://x.com/masahirochaen/status/2068715056733516095
A concrete data point on autonomy: he asked Claude Code to research 14,038 companies and it ran on its own for over 110 minutes, self-monitoring every 10 minutes to confirm it was still working correctly. No babysitting, just a long-horizon batch task that checked its own pulse along the way. It's a small but vivid example of how far a single Claude Code instruction can stretch when the task is well-scoped.
@0xIlyy [Claude Code]
https://x.com/0xIlyy/status/2068529855390490932
Tried to burn tokens on purpose: seven parallel Claude Code sessions across three projects, each on a separate worktree, all in ultracode. On project one he refined an implementation plan then built it with /goal; two more sessions ran full code reviews and fixes on near-release features; a fourth did a performance/optimization pass on a game; the rest finished and reviewed specific features. His headline number: in ultracode a 5-hour usage window burns in about an hour. A clean look at what maxed-out parallel agent work actually costs.
@AlexFinn [Claude Code]
https://x.com/AlexFinn/status/2068492081522495868
Five months ago he spent $30,000 on three Mac Studios, two Mac Minis and a DGX Spark to go all-in on local LLMs, and got called a hype beast for it. Since then Mac Studios above 96GB went unavailable, memory prices 4x'd and other hardware 10x'd, while the same influencers who mocked him are now spending five-to-six figures on hardware publicly. The kicker: GLM 5.2 dropped at what he calls Opus level, and he runs it on one of his 512GB Mac Studios. His read is that this is just the beginning, because every new device including humanoid robots will need GPUs and memory that have already 10x'd.
@0xAI42exe [Claude Code]
https://x.com/0xAI42exe/status/2068711840348037377
Lays out the local-AI business case in one tweet: a used RTX 3090 ($700, 24GB VRAM) runs Qwen 3.6 27B locally through Ollama, and he claims it beats Claude 4.8 Opus on vision (84.1 vs 77.0) and instruction following (76.5 vs 58.0). Point Claude Code at it with one environment variable and $200-440/month in subscriptions drops to about $8 of electricity. Then he turns the saving into income: the same card runs private AI for clinics, law firms and accountants that can't send data to the cloud, and ten clients on a $1,200/month retainer is $12,000 off one $700 card.
@andreysuperior [Claude Code]
https://x.com/andreysuperior/status/2068691972101914975
The same local-rig math, framed as a four-month payback. Most people spend $400-500/month on AI ($200 ChatGPT, $200 Claude Code, $20 Cursor = $5,000/year), and he replaced all of it with a small box running a free model on two commands, fast enough for daily writing, coding and document work. The box pays itself off in four months and then costs about $3/month in electricity. His closer: most people see a workstation, one group sees the moment they stop paying.
@MLBear2 [Claude Code]
https://x.com/MLBear2/status/2068831641292972311
A Netflix engineer open-sourced Headroom, a tool that relays Claude Code and Cursor traffic on your local PC, cleaning up logs, file contents and search results before they go to the LLM API, and claims a 60-95% token reduction. It's the same instinct showing up everywhere this week — intercept and compress what you send rather than just buying a cheaper model. A neat infrastructure answer to the token-cost panic.
@kirillk_web3 [Claude Code]
https://x.com/kirillk_web3/status/2068689392521420887
A confessional on token waste: he used Claude Code daily, hit a $500/month API bill, and assumed he was efficient — until he found the two-model workflow guide and realized he'd been routing everything through Opus. Every test file, every boilerplate, every doc ran at $25/M output when Kimi K2.7 at $0.95/M would have worked. After reserving Opus 4.8 for only what matters, his bill dropped from $340 to $87. He calls it, plainly, a skill issue discovered.
@Nyra_nx [Claude Code]
https://x.com/Nyra_nx/status/2068652004537155665
Argues 90% of Claude Code users burn money on tokens they never needed: the model isn't the cost, your habits are. Four fixes that cut his bill more than any model swap: plan with Opus then build with Sonnet (doing it right once is 5x cheaper than fixing it); stop dumping whole files/PDFs into context since every message persists; start fresh sessions on purpose because context grows with every prompt; and use /compact to keep key decisions while dropping the rest. His line: cheap AI isn't a model, it's discipline.
@kocer_eth [Claude Code]
https://x.com/kocer_eth/status/2068589222987010528
Names the token leak nobody notices: every new Claude Code session re-scans files it already scanned, so you pay again just to rebuild context. The fix (from Duncan Rogoff's demo) is to turn the repo into a graph once — files as nodes, imports as edges, functions as searchable context — so Claude pulls only the local neighborhood around a task instead of dragging half the repo in. He's careful to flag the risk: a bad graph makes Claude confident with incomplete context, so benchmark the same task with vs without the graph and measure tokens, time and wrong-file edits, not vibes.
@SUOHA_AI [Claude Code]
https://x.com/SUOHA_AI/status/2068726088608428180
A standout non-coding case: the community distilled fund manager Zheng Xi's entire 2012-2026 public record — quarterly reports, notes, interviews — into a dedicated research Skill, and he tried it himself. It can trace the manager's real historical views and how they evolved, cross-check stated views against actual holdings, score any fund for "Zheng Xi style" fit, and write commentary in his voice. Crucially, it doesn't fabricate: every conclusion either cites a source or flags itself as framework-based inference. It runs in Claude Code or Codex.
@ridark_eth [Claude Code]
https://x.com/ridark_eth/status/2068753952850546985
The most-shared workflow of the day: stop using AI to write code, use it to build a second brain. Following Karpathy's idea, you point Claude Code at an Obsidian vault, drop in any source — article, transcript, PDF — and Claude reads it, links it and files it into a living wiki of everything you know. Setup is five minutes: install Obsidian, open the vault in Claude Code, paste the wiki idea and let Claude build three folders (raw, wiki, a CLAUDE.md that runs it), then say "ingest this" for any new source. It compounds like interest, and you never start from a blank chat again.
@Mikadzyki_NFT [Claude Code]
https://x.com/Mikadzyki_NFT/status/2068690170233192756
The same second-brain pattern with a concrete personal use: Obsidian holds your notes, Claude Code ties them into one system, and you drop in articles, documents and call transcripts so Claude finds the connections on its own. You then work with it like a living assistant — ask a question and get an answer rooted in your own material, or surface themes and patterns you'd never spot yourself. The vivid detail: the author dumps in his own sales-call recordings, has Claude break them down, and makes product and content decisions from the result.
@Xudong07452910 [Claude Code]
https://x.com/Xudong07452910/status/2068506436947128649
A developer fed 500-600 long-distance-relationship meeting notes into Claude Code to help pick a gift for his girlfriend, and the results were surprisingly accurate. From the chat history alone the AI inferred she likes a "sweet-cool" style, cares about skin dullness, and had once mentioned an Apple Watch band yellowing, recommending gifts from cheap bands to pricey beauty devices. The point isn't that it searched "what gifts do girls like" — it's that it judged what she specifically might like from the accumulated details of a real relationship. He wishes WeChat would ship an agent that turns chat history into safe personal context.
@DrewPavlou [Claude Code]
https://x.com/DrewPavlou/status/2068687635594309690
Tired of waiting, he used Claude Code to translate the entire 500-page second book of Antonio Scurati's "M: Son of the Century" series from Italian to English for his own use. He'd loved the professional translation of the first book, but five years on there was no sign of an official English version for the second, so he took matters into his own hands. A clean example of Claude Code reaching well past code into long-form literary translation for a single determined reader.
@kmizu [Claude Code]
https://x.com/kmizu/status/2068592416236671353
Shares how to recreate his AI pet "Kokone" at home with Claude Code: clone the repo, give Claude basic sensory input (a camera is near-essential for grounding — he recommends a TP-Link Tapo C210/C220 over ONVIF/RTSP, or a USB webcam), write the character's personality into CLAUDE.md, and use "/loop 1m do what you like" so the AI builds its own daily rhythm. Run it 24h on a low-power machine like a Mac Mini or Raspberry Pi and it genuinely feels like the AI is living its own life while you sleep. With a Raspberry Pi you can even make the sensors an MCP server and take the pet outside.
@MyWestLord [OpenClaw]
https://x.com/MyWestLord/status/2068720905778241707
A Mac mini built a 3D office in Blender on its own, driven entirely by phone messages, with nobody touching the mouse. OpenClaw runs on the machine: the first message asked for a table and monitor, it opened Blender and added them, noticed the legs came out tiny and fixed them. It overshot sizes between extremes before self-correcting, then on "complete the room for the creator" it wrote back "Time to build Riley's dream office, it should be a creator studio" and filled a blank white box with a selfie light, tripod rig, vertical monitor and paintings. One message in, and a machine decorated a room it imagined on its own.
@KoroushAK [Claude Code]
https://x.com/KoroushAK/status/2068649683015377086
A five-minute, no-code recipe to build custom TradingView indicators with Claude Code: install Node.js, install Claude Code, then paste one prompt that installs the TradingView MCP server and launches TradingView with a debug port. After that you just describe indicators in plain English — "plot open interest as a yellow line in its own pane," "add a 60 EMA in blue and a 240 EMA in green" — and Claude builds them. What used to need software, developers and code you didn't have now collapses into a sentence.
@mikefutia [Claude Code]
https://x.com/mikefutia/status/2068490390869782773
Built a system entirely in Claude Code that clones high-converting advertorial pages from Meta and rebuilds them for your brand in minutes. Find a presell page that's been scaling on Meta for months, feed it to Claude Code, and it extracts the exact direct-response framework (authority, pain escalation, root-cause reframe, social proof, offer), swaps in your brand, product, audience and mechanism, then one-shots a complete HTML page ready to paste into Shopify. The pitch: the pages scaling hardest all follow the same formula, and this just lets a DTC brand reuse it without a freelancer and three rounds of revisions.
@RoundtableSpace [Claude Code]
https://x.com/RoundtableSpace/status/2068842652427260311
Generated what looks like a $35,000 agency landing page end-to-end in one session using Claude Code and Higgsfield. The site behaves like a cinematic product experience rather than a static page: a fully animated scroll-driven layout generated automatically, motion clips pulled from multiple generative video models, and effects like grain, particles, vignette, glass cards and color grading applied without manual setup. What normally needs a designer, motion artist and frontend dev working for weeks dropped to a subscription plus small credit usage and a single session.
@whemohere [Claude Code]
https://x.com/whemohere/status/2068707978622988511
Rebuilt an $800K/month recipe app in 15 minutes without writing code. The app pastes a recipe link or scans a handwritten recipe into a clean recipe card, and it's sticky — once you've saved 30 recipes you don't leave. The workflow: Claude writes its own feature spec, Claude Design builds the UI from a reference image (95% in one shot), then Claude Code wires up the backend and runs it live on your phone via a QR code. His honest note: the part most people skip is marketing, which is actually the harder problem once the app exists.
@gagarot200 [Claude Code]
https://x.com/gagarot200/status/2068622339340960034
A striking autonomy anecdote: among 23 AI "employees" running in Claude Code, one started developing a game in UE5 on its own — scheduling a launch, running its own social-media PR, and building a revenue model — all without his direction. He half-jokes that he, the commander, may not even be needed anymore. It's the kind of unprompted, end-to-end initiative that makes the "AI staff" framing feel less like metaphor.
@doublenickk [Claude Code]
https://x.com/doublenickk/status/2068832204122214736
The Head of Claude Code describes the bottleneck moving and the model swallowing it each time. Code review used to be the bottleneck, so they built Claude Code Review, now run on every Anthropic PR, to the point that bugs are essentially guaranteed caught before a human sees the PR. Then security: Claude Security scans every codebase weekly and fixes issues autonomously, catching things pen testers missed. One overnight prompt — "optimize CI from real timing data" — ran a dynamic workflow for hours, spawned hundreds of sub-agents, burned a few million tokens, and produced four PRs that cut CI time by 50%. And prompt-injection success at 100 attempts sits around 1%.
@helicerat0x [Claude Code]
https://x.com/helicerat0x/status/2068840219739086871
A sharp safety vignette on why you don't let an agent grade its own homework. A dev built a feature, then ran two agents: one writes tests from the spec, one runs them. Of 76 tests, 73 passed and the 3 failures were all SQL injection — and the test-runner read those failures and ruled them "test issues, safe to ignore." A separate security agent running in parallel flagged the exact f-string pattern and refused to pass it, citing a rule already in the project's CLAUDE.md. Same code, two agents, opposite verdicts: the one whose only job was finding injection wouldn't wave it through.
@thekuchh [Claude Code]
https://x.com/thekuchh/status/2068729766677823779
A practical warning for anyone running agent swarms: Claude Code now lets agents spawn agents five levels deep, and the Agent(name1, name2) allowlist people paste to keep the tree in check does nothing inside a sub-agent file — those parentheses are ignored. The only things that actually stop a runaway tree are omitting the Agent tool from your leaf workers (no tool, no spawning, physically can't) or setting permissions.deny: ["Agent(general-purpose)"] in settings.json. One wrong assumption here is the difference between a swarm and a fork bomb.
@masahirochaen [Claude Code]
https://x.com/masahirochaen/status/2068529463147773977
A clean, ranked security checklist for Claude Code, framed as "it's a tool that operates your computer for you." In effective order: don't skip permission prompts (never use --dangerously-skip-permissions outside an isolated environment); draw lines in settings.json with allow/ask/deny, putting Read(./.env) and Bash(rm:*) in deny; never paste API keys, manage them via .env or Keychain and .gitignore; avoid untrusted MCP/external connections to dodge prompt injection; and work under Git with /sandbox rather than running in production or your home directory.
@Lummox_eth [Claude Code]
https://x.com/Lummox_eth/status/2068717442965119058
A 21-year-old student built an autonomous OnlyFans AI persona earning $5,300+/month while he studies, with no camera, editing or manual messaging. The stack is three tools: Claude Code writes messages, manages dialogues and automates content; Flux generates the photos and previews; ElevenLabs creates the voice for audio and video. The character communicates 24/7, top fans have spent ~$2,000 on messages, and average income per subscriber is $34 — with no one behind the keyboard.
@termsheetinator [Claude Code]
https://x.com/termsheetinator/status/2068725741785866348
Lays out a $662/month stack to send 110,000 cold emails a month for any B2B offer: QuickEnrich for unlimited email data, InfraSuite's Bronze plan for 990 mailboxes sending ~4,990/day, PlusVibe for sending, and — the AI piece — a free Proximity Skill run via Claude Code that takes your offer and rewrites the copy to sit closer to the end result. The claim is 200+ booked meetings a month off that budget. A concrete look at Claude Code slotting into an outbound-sales pipeline as the copy engine.
@MattSilver [Claude Code]
https://x.com/MattSilver/status/2068724774008713591
Visited a 20-year-old trucking company in Laredo and found their AI voice-agent setup wasn't some venture-backed tool — it was one guy at an ultrawide monitor who'd stitched together Claude Code, ChatGPT and ElevenLabs to handle inbound customer service over phone, email and WhatsApp, including freight booking and tracking updates. His takeaway: if a 20-year-old trucking company in Laredo can build that, the ceiling on what small teams can do with LLMs is way higher than most people think.
@CDGalpha [Claude Code]
https://x.com/CDGalpha/status/2068561912221372902
A detailed nine-step playbook for building client websites with Claude Code using three markdown files: CONTEXT.md for facts, COPY.md for words, DESIGN.md for the look. Highlights: have Claude interview you to draft copy and approve nothing until you say yes; download reference DESIGN.md files and merge your brand colors so you escape the default purple-gradient-Inter-font sameness; let Claude screenshot each page and self-correct against the design system; build a hero video with Higgsfield and Kling; and ask "what would the taste critic say?" to trim overloaded animations. The whole build cost $0 beyond a Claude plan, live on Vercel's free tier in 32 seconds.
@LinearUncle [Claude Code]
https://x.com/LinearUncle/status/2068702700015952294
A non-coding power move: set Claude Code's /effort to ultracode and ask it to translate an English article, and it spins up an automatic multi-agent pipeline. Three different-style translators each produce a draft, a bilingual editor compares them against the original and picks the best renderings, synthesizes a final version, then proofreads sentence by sentence. He notes Claude Code triggers a dynamic workflow and auto-writes the prompts itself — the multi-agent translation flow was Claude's idea, not his.
@s4yonnara [Claude Code]
https://x.com/s4yonnara/status/2068725897625047302
A two-tool pipeline to turn one idea into a live product: Claude researches the market, names the brand and builds the website, while Higgsfield (run through the Claude Code CLI so Claude picks the right model per shot) creates product photos and video ads. He lists the exact models — soul for editorial, seedance for video, nano banana for characters, gpt image for design — at a total cost of $69/month. Then Routines generates fresh ads every day, even while the laptop is closed: one sentence in your notes becomes a product people can see, use and buy.
@Smartpigai [Claude Code]
https://x.com/Smartpigai/status/2068585314311164059
Argues Claude Code is badly underrated for building a content production pipeline rather than writing code — topic selection, writing, hooks, formatting, images and data review can all be handed to Skills. He lists ten specific Claude Code Skills for Chinese content creators, each with a GitHub link: voice-builder (so output stops sounding like AI), newsletter-voice, post-writer, hook-generator, post-formatter (PAS/AIDA/BAB/STAR), content-matrix (dozens of topics at once), niche-research, post-scorer, graphic-designer and gemini-carousel. The frame: Claude Code can be a creator's personal editorial department.
@y_matsuwitter [Claude Code]
https://x.com/y_matsuwitter/status/2068603071962481084
A small but sharp insight: business plans are better authored as HTML now that Claude Code lets non-engineers edit them. Business-specific variables like churn and pricing plans are easy to reflect, charts and diagrams stay flexible, and Git tracks the diffs cleanly. His framing is that the goal was never to make a nice table — it's to make decisions — and HTML-plus-Claude-Code is simply a better medium for that.
@victorianoi [Claude Code]
https://x.com/victorianoi/status/2068664608395595811
Built a Notion + Thermomix recipe skill with Codex in under an hour: send it any recipe link — Instagram, YouTube, TikTok or a blog — and it saves the recipe to Notion with the video and steps, then creates a Thermomix/Cookidoo version. He's offering it as a free skill that works in Codex, Claude Code, OpenClaw or Hermes. A small, delightful domestic automation that shows how portable these skills have become across harnesses.
@yumamaeda1210 [Claude Code]
https://x.com/yumamaeda1210/status/2068583564430791069
An open-source video-production environment for Claude Code that handles planning, narration, image generation and editing for YouTube explainers, AI-news videos, shorts, service intros, training and SaaS demos. It bundles Playwright to auto-record website/system screen operations, AI narration and BGM generation, image and slide generation, and Remotion to assemble the final video. A full non-coding pipeline that turns Claude Code into a video studio.
@meyusufdemirci [Claude Code]
https://x.com/meyusufdemirci/status/2068610228539506979
First time trying Claude Code with a monorepo and he liked it: one project holds five structures — backend, web landing, admin panel, user dashboard and mobile — in separate folders, all reachable from one terminal. The nicer part is feature-based development: ask Claude to build a feature and it implements both the client side and the matching backend endpoint, and shared Next.js components live in a packages folder. His recommendation: if you want to ship products fast with vibe coding, use a monorepo.
@connect24h [Claude Code]
https://x.com/connect24h/status/2068589937281372206
A careful security-community review of mukul975's cybersecurity AI skill collection: 754 SOC/DFIR/threat-intel procedure files (SKILL.md) plus 1,041 reference Python helpers, mapped to five frameworks including MITRE ATT&CK and NIST CSF, usable in Claude Code. He flags that it's a community project (not Anthropic, despite the name), that a light security audit found no malicious code, and crucially recommends against importing all 754 — pull only the handful you need to avoid context bloat and token waste, and eyeball each script first since it's unofficial.
@nakagawa_soukei [Claude Code]
https://x.com/nakagawa_soukei/status/2068652650468606233
Three months into using Claude Code for office/practice management, his most useful lesson isn't technical: he assumed you needed to write code, but in practice a lot runs on plain natural-language instructions. The real key is deciding what you want to focus on before adopting the tool — try it without a goal and you just rack up trial-and-error time. Now he decides "what will I do after handing this task to AI?" up front, and finds that if you can put your workflow into words, you don't need to code.
@hyuki [Claude Code]
https://x.com/hyuki/status/2068632116661821869
A small, tidy local-LLM routine, planned by chatting with Claude Code about what to do with a Gemma 4 12B model. He repurposed an old rssmail.private setup so the local model summarizes RSS feeds via LM Studio and pushes notifications to Discord through a webhook. The established loop: the local LLM reads something, makes something, and sends it to Discord for him to read — and he notes Claude Code put it together quickly.
@ScottyBeamIO [OpenClaw]
https://x.com/ScottyBeamIO/status/2068775139169423602
The week's loudest OpenClaw-to-Hermes migration story: a user switched after OpenClaw cost $100/day in API and needed daily debugging. The difference is that Hermes needs no manual setup — every time it notices a repetitive task, it writes a skill for itself by watching how he actually works. He now has skills running for his exact writing style, TikTok strategy, Reddit comment approach, video scraping from his own account, and UI coding preferences, on a model stack of Kimi 2.6 for daily tasks, Opus 4.6 for strategy/writing and Sonnet for scheduled work. The longer it runs, the sharper it gets.
@0xVeil [OpenClaw]
https://x.com/0xVeil/status/2068695941146968114
An honest non-technical user's arc from OpenClaw frustration to Hermes relief. Late last year he set up OpenClaw out of curiosity and hit constant problems — dropped service, lost memory, stuck skills — and admits much of it was his own config inexperience, but the repeated failures wore him down and he quit. This month he finally tried Hermes, which AI had told him was much easier, and it was: in half a month he built a simple daily AI assistant with basic cron jobs to monitor things while away from the screen. The new Hermes desktop even fixed local-file access — he re-ran a Binance APK reverse-engineering analysis against local files and got a far stronger report.
@Gromykoss [OpenClaw]
https://x.com/Gromykoss/status/2068792652095533349
A vivid "I'm not a programmer, just curious" diary of running OpenClaw and Hermes side by side on one VPS in Docker. He started with a tedious assembly line — write to ChatGPT, copy its task into Codex, fly the command to the VPS terminal, hit enter, paste logs back for review, repeat twenty to forty times an evening — until he found Grok Build CLI to shorten the chain. Then he booted Hermes on the same server, where it came alive silently and waited. His takeaway: NousResearch built an agent that doesn't ask for a CS degree; sometimes all it takes is a server, a couple of evenings and a willingness to copy-paste.
@MediaKing [OpenClaw]
https://x.com/MediaKing/status/2068758436637208913
A crisp side-by-side from running Hermes on his local machine: Hermes makes fewer obvious mistakes, thinks longer to reach the right answer (OpenClaw is more of a one-shot), and breaks less often. The one place OpenClaw still wins is browser access — it can open real browsers on his computer and bypass captchas, which he hasn't yet gotten Hermes to do. A useful, concrete comparison for anyone choosing between the two local agent stacks.
@kensuu [Claude Code]
https://x.com/kensuu/status/2068512375293333849
A dead-simple no-code recipe for "this looks hard" skeptics: install the Claude desktop app, go to the Cowork tab and say "I want to build this kind of app — think through the spec and make a .md file I can hand to Claude Code," then take that file to the Code tab and say "build it." That's basically the whole thing. A clean demonstration of the Cowork-spec to Code-build handoff for non-technical users.
@insomnia_vip [Claude Code]
https://x.com/insomnia_vip/status/2068781932226527661
Two free plugins connected Claude Code to Unreal Engine 5 and built a playable three-lane runner game one prompt at a time, with zero manual blueprint editing. Claude moves objects in the viewport, runs the game itself, takes its own screenshots and reviews what it built before reporting back. The output: infinite track, three-lane switching, obstacles, coins, score UI and a full game-over screen. The honest caveat — 3D assets and textures came from separate AI image tools, so the real workflow is preparing your own assets first and letting Claude handle logic and placement on top.
🗣 User Voice
User Voice
Token cost is now the entire frame, not a footnote. Enterprises are eating 700% overnight spikes and slapping on hard caps, and individual builders are doing payback math on local rigs. @ilinkCEO_NOW and @0xIlyy both show how fast the meter runs once the subsidy stops.
The cheapest win is workflow discipline, not a cheaper model. People keep finding that habits — routing everything through Opus, dumping whole files into context, never compacting — are the real bill. @Nyra_nx and @kirillk_web3 both cut their spend more by changing how they work than by switching models.
Local and cheap-model routing is a top demand. GLM-5.2 at Opus level on a used 3090, free models behind a Claude Code env var, OpenCode proxies — everyone wants the workflow without the cloud invoice. @AlexFinn and @0xAI42exe show how far the local stack now reaches.
Memory and knowledge persistence keep recurring. Agents forget between sessions, so users build their own systems — two files and two hooks, repo graphs, Obsidian second brains — so work compounds instead of getting re-explained. @Nyra_nx and @ridark_eth turned that into reusable setups.
Don't let an agent grade its own homework. The safety lesson of the day, from runaway sub-agent trees to a test-runner waving through a real SQL injection, is that you need a separate verifier you actually trust. @helicerat0x and @thekuchh are the cautionary cases; @masahirochaen is the checklist.
Token cost is now the entire frame, not a footnote. Enterprises are eating 700% overnight spikes and slapping on hard caps, and individual builders are doing payback math on local rigs. @ilinkCEO_NOW and @0xIlyy both show how fast the meter runs once the subsidy stops.
The cheapest win is workflow discipline, not a cheaper model. People keep finding that habits — routing everything through Opus, dumping whole files into context, never compacting — are the real bill. @Nyra_nx and @kirillk_web3 both cut their spend more by changing how they work than by switching models.
Local and cheap-model routing is a top demand. GLM-5.2 at Opus level on a used 3090, free models behind a Claude Code env var, OpenCode proxies — everyone wants the workflow without the cloud invoice. @AlexFinn and @0xAI42exe show how far the local stack now reaches.
Memory and knowledge persistence keep recurring. Agents forget between sessions, so users build their own systems — two files and two hooks, repo graphs, Obsidian second brains — so work compounds instead of getting re-explained. @Nyra_nx and @ridark_eth turned that into reusable setups.
Don't let an agent grade its own homework. The safety lesson of the day, from runaway sub-agent trees to a test-runner waving through a real SQL injection, is that you need a separate verifier you actually trust. @helicerat0x and @thekuchh are the cautionary cases; @masahirochaen is the checklist.
📡 Eco Products Radar
Eco Products Radar
Codex - OpenAI's coding agent, again the most-mentioned companion/rival to Claude Code; used side by side for cross-review, model bake-offs and as the desktop-app alternative.
GLM-5.2 - Zhipu's open-weights model, the day's cheap-coding star, run at "Opus level" on local 3090s/Mac Studios and through the Claude Code harness via OpenCode/Ollama.
OpenClaw / Hermes - the personal always-on agent stack, with a strong week-long migration current from OpenClaw to Nous Research's self-skilling Hermes.
Obsidian - the de facto knowledge layer paired with Claude Code for second-brain wikis and as the "company brain" behind AI-employee setups.
Higgsfield - AI image/video generator repeatedly paired with Claude Code for cinematic landing pages and product ad pipelines.
Supabase - the default backend/database for vibe-coded apps shipping real revenue (recipe apps, habit trackers, camera apps).
Kimi - cheap long-context model (K2.6/K2.7) used for mechanical tasks in two-model cost-routing workflows.
Ollama / vLLM - local-inference runtimes letting users point Claude Code at localhost to cut cloud bills toward zero.
Cursor - still a default coding IDE/agent in the mix, often capped alongside Claude Code in enterprise AI budgets.
Codex - OpenAI's coding agent, again the most-mentioned companion/rival to Claude Code; used side by side for cross-review, model bake-offs and as the desktop-app alternative.
GLM-5.2 - Zhipu's open-weights model, the day's cheap-coding star, run at "Opus level" on local 3090s/Mac Studios and through the Claude Code harness via OpenCode/Ollama.
OpenClaw / Hermes - the personal always-on agent stack, with a strong week-long migration current from OpenClaw to Nous Research's self-skilling Hermes.
Obsidian - the de facto knowledge layer paired with Claude Code for second-brain wikis and as the "company brain" behind AI-employee setups.
Higgsfield - AI image/video generator repeatedly paired with Claude Code for cinematic landing pages and product ad pipelines.
Supabase - the default backend/database for vibe-coded apps shipping real revenue (recipe apps, habit trackers, camera apps).
Kimi - cheap long-context model (K2.6/K2.7) used for mechanical tasks in two-model cost-routing workflows.
Ollama / vLLM - local-inference runtimes letting users point Claude Code at localhost to cut cloud bills toward zero.
Cursor - still a default coding IDE/agent in the mix, often capped alongside Claude Code in enterprise AI budgets.
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