The latest AI agent news, updated daily — releases, security advisories, tutorials, and video summaries across the platforms we track: OpenClaw, Claude Code, IronClaw, NemoClaw, Kilo Code, Hermes, ChatGPT, and Claude Cowork. Every story is summarised in our own words from official changelogs, community discussion, and the top creators, with a link straight to the source.
A continuously updated feed of AI agent news — new releases, security advisories, tutorials, and video summaries across OpenClaw, Claude Code, Hermes, IronClaw, NemoClaw, Kilo Code, Claude Cowork, and ChatGPT. Every day we scan official changelogs, community discussion, and the top YouTube creators, summarise each story in our own words, and link straight to the source. When a story affects one of our setup or troubleshooting guides, we update that guide the same day. Browse by agent below, follow along via RSS or the weekly email, or open any story for the full breakdown and related guides.
Nate Herk's beginner course reframes Claude Code for non-coders: it's a harness that pairs an AI model (Opus, Sonnet, Haiku, Fable) with your context and judgment, distinct from Claude chat and Claude Cowork. He then walks through six career-proofing AI skills — being the AI person, taste, context engineering, iteration speed, and building an always-on Jarvis — including when a task needs an AI agent versus a deterministic workflow.
Julian Goldie runs GPT-5.6 through the updated Codex — now folded into the ChatGPT app rather than a separate product. In one session he redesigns a website from an existing site, triggers background computer use that publishes a Skool post on his behalf, edits a video via a Descript plugin, installs an agent from GitHub, and tries the new "pet" task tracker and adjustable effort levels.
Nate B Jones lays out a four-factor test — size, independence, separation of concerns, and checkability — for deciding whether a task needs a chat, one agent, a team of agents, or no AI at all. He grounds it in Stanford's repeated-sampling study and Anthropic's multi-agent research, then shows a harness that cut Fable 5 costs ~10x by letting Fable plan while cheap worker agents execute.
Nate Herk drives GPT-5.6 Sol (via Codex) against Fable 5 (via Claude Code) on identical build prompts and stateless API tasks. Fable wins on raw build quality but costs up to ~20x more per run; Sol is far cheaper, more token-efficient, and stronger on quick one-offs. His verdict: Fable is the manager, Sol is the worker — and the best setup is Fable orchestrating cheaper Sol agents.
Nate Herk gave GPT-5.6 Soul one prompt on Codex "Ultra" and it produced a full narrated, avatar-led video end to end — research, scripting in his voice, ElevenLabs/HeyGen/Hyperframes, and frame-by-frame self-checks. He also digs into the real token cost: Ultra spun up nine sub-agents and burned ~450M tokens (~$300), which he argues was over-delegation — the same prompt on "high" would likely match the result at half the cost.
Kilo Code introduces Kilo for GitHub — an AI coding agent you @-mention inside GitHub issues and pull requests. It reads the surrounding thread, diff, and codebase to answer questions, diagnose bugs, and implement real changes without leaving GitHub.
A multi-agent "org chart" where Claude Fable 5 only plans, reviews, and settles disputes while four cheaper model families do all the coding. The build shipped a production site in about two hours for roughly $8 (versus an estimated $85–105 on Fable alone), and independent checker agents caught four escalating failures — a quote hallucination, two worker cheats, and a CSS bug written by Fable itself — with zero human correction.
Alex Finn distills four months with Hermes Agent into nine practical lessons — which model to run (Opus vs ChatGPT vs GLM 5.2), why to run 2+ agents that repair each other, when to stop over-isolating accounts, the best platforms (desktop, Telegram, iMessage), pruning cron jobs to fix a slow agent, using Tailscale to run a whole device fleet, and a daily reverse-prompt interview to find new automations.
The model isn't the moat — the process is. Nate Herk extracts Fable 5's working discipline into a reusable "Fable mode" skill file built on five gates (scoping, evidence, attacking, verifying, reporting), then pairs it with a cost/intelligence/taste routing table so cheaper models like Opus 4.8 reason with the same rigor at a fraction of the cost.
Nick Saraev renders bulky Claude Code context as a single tiny-but-legible image so image billing (fixed by pixel dimensions) beats text-token billing. Measured savings: about 33% on a general prompt and up to ~59% on a large retrieval query, with no measured loss in recall — an arbitrage of current pricing he expects to be patched.
Fahd Mirza feeds a single screenshot of a live fantasy-sports site into Hermes Agent and asks it to build and run an exact local clone in one prompt — using Sakana's new Fugu Ultra orchestration model, which routes each task across a pool of frontier models. A deliberately skeptical, one-shot test of whether screenshot-to-app orchestration holds up outside the benchmarks.
freeCodeCamp's beginner course climbs from LLM fundamentals — tokens, temperature, context windows, and prompting — up to building four agents (Zippy the orchestrator plus Savvy, Meshy, and Cody) and a case-study dissection of OpenClaw's architecture, agent loop, memory, testing, monitoring, and security. This page distills the reusable engineering concepts.
Alex Finn walks through seven new features in the latest Hermes Agent update — mixture-of-agents orchestration (/ma) that fans a prompt out to ChatGPT and DeepSeek via OpenRouter and synthesizes one answer, /learn that turns any URL, tweet, or completed task into a reusable skill, a /journey memory graph, cheaper background self-improvement, and git-controlled vibe coding with diffs, commits, and PRs. He closes by recommending a dedicated Hermes profile for Fable 5, reserved for complex builds rather than daily driving.
IndyDevDan walks through CMUX, a scriptable terminal multiplexer that gives agents programmatic control over multiple coding-agent sessions at once (Claude Code, Codex, Pi). He frames it around three orchestration problems — no programmatic access, no visibility to improve agents, and slow team startup — then demos a three-tier orchestrator → lead → worker pattern with a flat channel where any agent can prompt any agent. CMUX is Mac-only; T-mux is the cross-platform alternative.
Fahd Mirza installs and tests Headroom, a local, Apache-licensed proxy that sits between your agent and the model and compresses everything the agent reads — file dumps, tool outputs, logs — before it lands in context. He wires it to a Hermes agent on a local Ollama model, runs a bug-fix task, and shows the context window holding at ~40K instead of blowing past it. Compression is reversible: the model pulls the original text back when it actually needs it.
Julian Goldie shows how to run the open-source Codex CLI without an OpenAI subscription by pointing it at OmniRoute — a local gateway that routes requests across 93 providers, 11 of them permanently free. It's the same real Codex CLI; only the backend changes. Auto-fallback silently hops to the next provider when a free one hits its rate limit, so a build keeps going instead of breaking mid-task.
NVIDIA and KAIST researchers released SpatialClaw, a training-free spatial-reasoning agent that hands a vision-language model a persistent Python kernel and lets it write, run, and inspect code one cell at a time — instead of committing to a single up-front program or a rigid, one-tool-at-a-time JSON interface. Fahd Mirza walks through the five-stage agent loop, the self-correction that lets it recover from its own mistakes mid-run, and benchmark results where it beats the previous best spatial agent by 11.2 points with no task-specific training. His honest caveat: it's a research-cluster project, not a single-GPU download.
Julian Goldie demonstrates the open-source Hyperframes skill — now with keyframe and arc-motion support, so an agent can watch its own generated motion and self-correct it — paired with a Hermes-based video agent that researches a topic, writes a script, generates B-roll and an avatar presenter, and assembles a finished video from a single prompt. Much of the video is a walkthrough of his paid community setup rather than a reproducible build, so treat it as a product tour.
Most agent demos stop at drafting emails. Nate B Jones builds one reusable nine-part "agent skeleton" — context pack, ingest, chunk, normalize, store, retrieve, cite, export, and a hard human gate — then applies the exact same structure to insurance appeals and tax prep. A context-engineering framework for high-trust paperwork where the agent organizes the mess but never submits, pays, or signs.
Julian Goldie answers community setup questions for an agent operating system built on Hermes: carrying your existing Claude skill markdown files over to Hermes, the five things to configure first, using Hermes' primary/auxiliary model fallback with backup keys, reaching the system from your phone via Tailscale, and hosting agent-generated sites on Netlify.
On June 30, 2026, X launched a hosted MCP (Model Context Protocol) server at api.x.com/mcp that gives AI agents a live, read-only window into X through your own account's OAuth permissions — no custom server to build, no API to hand-wire. It exposes 200+ X API tools (search posts, look up users, read conversations, spot trends, pull bookmarks) and works with clients like Claude Desktop, Cursor, VS Code, and Grok.
Tech With Tim deploys both OpenClaw and Hermes Agent on real VPS instances and runs identical jobs through each. The verdict: Hermes wins as a single-user daily driver — its “curator” writes and refines skills automatically and its memory is faster and deeper — while OpenClaw's edge is its 5,400-skill catalog and easier multi-gateway routing for customer-facing, multi-channel deployments.
Hermes Agent V0.18 — the “Judgement” release — centers on verification: a self-judging /goal loop where a separate judge scores each round against your definition of done, and proof-of-work that marks coding tasks complete only after running the project’s own checks. It also promotes mixture-of-agents (fusing multiple models into one answer) to a first-class mode and adds /learn, /journey, and background sub-agent fan-out.
Analyst Nate B Jones argues the fastest way to make an AI agent dangerous is to let everyone use it while no one owns it. Once an agent can read files, draft messages, or change code, a specific person must be operationally accountable — not just on an org chart. A short, pointed case for assigning a clear owner before you widen agent access.
A full Hermes agent walkthrough — a two-minute install, adding skills from GitHub, wiring up a Telegram gateway with hermes gateway setup, scheduling tasks, and configuring memory, profiles, and per-task model routing. Highlights what sets Hermes apart from OpenClaw: preloaded skills, self-healing when a skill errors, and broad built-in provider support.
Bart Slodyczka runs the new open-source Ornith 1.0 9B dense model locally on a 16GB Mac mini via LM Studio and PyAgent, asking it to build a tower-defense game. The 9B produced broken code (undeclared functions, broken tool calls, debug loops) while the 35B one-shotted a playable game — an honest look at where small local coding models still fall short.
Analysis, not a how-to: Nate B Jones argues OpenAI's restricted, government-reviewed GPT-5.6 rollout — alongside Claude Tag in Slack, Apple's context-connected Siri, GLM 5.2, and OpenAI's Codex adoption study — all point to the same shift. As frontier intelligence slows and gets cheaper, the next advantage is context, not raw model capability.
OpenAI quietly replaced GPT-5.3 Instant with GPT-5.5 Instant as the default ChatGPT model — no launch event. It cuts hallucinated claims by 52.5% on high-stakes prompts, runs roughly 3x faster on quick tasks, and returns about 30% shorter responses. Meaningful gains inside agent loops, where every extra token adds latency and cost. Best used as a fast/light layer alongside a heavier frontier model for complex builds.
Allie K. Miller describes "AI watchdog" agents — a persona that sits in on every conversation as a witness rather than a contributor, "like a McKinsey consultant in the corner keeping tally." It doesn't build; it notices patterns, counts recurring problems, and flags when two teams are unknowingly doing the same work. A short, conceptual framing for non-builder agents on a team.
OpenAI put Codex, its autonomous coding agent, inside the ChatGPT mobile app on iOS and Android — on every plan including free. Julian Goldie walks through the new mobile workflow: your phone as a remote control for jobs running on your computer, push notifications, high-level "goals", a parallel side chat, and file previews with inline comments for reviewing code before you approve it.
Fahd Mirza wires up OpenJarvis — Stanford's local-first AI agent framework from their "Intelligence per Watt" research — to Ollama on a single-GPU box. The walkthrough covers the one-line install, seven built-in presets, an Open Claw–style doctor health check, and a benchmark that reports average watts and joules per token alongside speed, all at $0 cost because it runs locally.
Most AI-productive people juggle five or six tools and become the human "hallway" carrying work between them. Nate B Jones's answer is Open Engine: put the work in a shared queue (Linear) plus a set of skills, so a ticket — not a chat box — becomes the place any agent or teammate can claim, work, and hand off a task with full state attached.
AICodeKing tests Ornith, Deep Reinforce's family of open agentic coding models (9B, 35B, 397B) post-trained on Gemma and Qwen. Hands-on notes on benchmarks, the runtime/parser setup its reasoning and tool-call tags need, and running it locally with OpenCode and Hermes Agent — where the smaller models hold up as some of the best local options.
Nate Herk patches Claude Code's "feel productive, not make money" defaults with four upgrades demoed live: a /roast persona council that stress-tests ideas, a Playwright verification loop that forces Claude to check its own work, a /session-handoff skill to beat context rot, and parallel sub-agents driven by a /goal command graded by a separate evaluator model.
Kilo Code's cloud agents — which run in isolated containers without a local machine — gain four upgrades: commits and PRs authored by your own GitHub account, reusable environment profiles bundling custom agents and skills, in-dashboard PR status, and remote sessions that sync your local CLI to the web dashboard live.
A short Kilo Code demo of KiloClaw reading Slack threads while you're away and returning a single catch-up message — what happened, what needs a response, and what you can safely ignore.
Kevin Stratvert walks through the Granola MCP connector, which pipes Zoom, Meet, and Teams transcripts into Claude, ChatGPT, and Claude Cowork. Once connected, the AI pulls meeting context automatically to generate proposals, action-item spreadsheets, draft emails, and calendar events.
Hermes Agent's updated computer-use feature runs in the background — clicking and typing in target apps via a "CUA-Driver" without moving your real cursor or pulling windows forward. It's cross-platform, works with any vision-capable model, and ships with approval gates and hard blocks on destructive actions.
Data-science professor Dr. Andrea Jones-Roy explains how she went from "just using ChatGPT" to running a 34-agent digital workforce in Claude Code — wired to Gmail and Google Workspace via MCP — by first building an agent that builds other agents. A candid look at agentic onboarding, meta-prompting, and keeping critical thinking in the loop.
Nate B Jones reframes the leap from prompting to agents as a mental shift: a prompt is one request, a loop is a recurring job with memory, and a loop of loops is when those jobs notice each other and hand off context — stopping where your judgment is needed. Includes concrete examples for spotting loops worth building.
Alex Finn walks through what he calls Hermes Agent's largest update yet — eight changes spanning native iMessage chat (via the free Photon service), background sub-agents that now spin up automatically with a live sub-agent tree, an Unreal Engine 5.8 MCP, a revamped desktop app, a dashboard profile builder, a browsable skills hub, smarter self-improving memory, and richer Telegram formatting.
Tech With Tim explains why running an AI coding agent around the clock takes more than your own machine: because the agent uses your local environment to run terminal commands and edit files, your computer has to stay awake and online — and any sleep, restart, or dropped connection loses the work. His fix is to move long-running and scheduled tasks onto a VPS.
Microsoft Research's SkillOpt treats a markdown skill document as the trainable "weights" — improving it with a rollout → reflect → gate loop while the model stays frozen. This hands-on walkthrough installs it, serves a local Qwen 3.5 4B with vLLM (~44GB VRAM on an RTX A6000), and trains a skill end-to-end on the ALFWorld benchmark. The output reads like a learned checklist, the same shape as a good hand-written skill file.
Nate Herk tests Sakana's viral Fugu Ultra — a single API that orchestrates frontier models (Opus, GPT, Gemini) like a multi-agent router — against Claude Opus 4.8 across 38 Codex-graded tasks. Result: 36 ties, with Fugu roughly 4.5× slower and 5× more expensive, since Opus is one of the very models Fugu delegates to. Impressive benchmarks, but not worth the cost or latency for knowledge work.
Analysis, not a how-to. Nate B Jones argues the real constraint with frontier models like Fable 5 isn't capability — it's our ability to imagine a big enough ask. He makes the case for "task imagination": handing a model whole, ambiguous jobs (not tracker-sized tasks), writing down what "done" looks like, building a data pack, then walking away and reviewing the result like an owner.
Julian Goldie wires Claude Code into Google Search Console (via the Workspace API) so it builds keyword strategy from your own impressions, clicks and positions — instead of the generic volume estimates everyone else pulls from Ahrefs or SEMrush. He pairs it with an Obsidian "second brain" for context and a pipeline that drafts and deploys multiple articles per keyword.
Bart Slodyczka fits the 395GB GLM 5.2 onto a 512GB M3 Ultra Mac Studio, runs it on a custom runtime (too new for LM Studio), and measures ~12 tokens/sec and ~74K context. His takeaway: the harness matters more than the model — a strong harness like Claude Code turns a simple prompt into a far better result than a basic agent does.
Fahd Mirza runs the Ponytail skill on a local Ollama model inside OpenClaw. A "lazy senior developer" decision ladder asks whether code needs to exist at all — collapsing a three-file email-validation answer into one native input (~20K tokens to ~2K), and cutting lines of code to 46% of baseline across a 12-ticket benchmark. A naive "be terse" control actually made things worse.
OpenAI ships three Codex updates: Sites (describe a page in one line and Codex builds and hosts it at a live link — Business/Enterprise preview only), saved rate-limit resets you can bank and spend when you need them, and a European rollout adding computer use, a Chrome extension, and opt-in memories.
Nate Herk breaks the AI "second brain" into five levels — from a simple CLAUDE.md router and markdown folders, up through LLM wikis, semantic/vector search, knowledge graphs, and full autonomy. The key lesson: pick the lowest level that solves your actual pain, and design your folders around how you'll retrieve the data later.
Nate Herk swaps Claude Code's model engine for Z.AI's open-source GLM 5.2 by editing one settings.local.json file — routing ANTHROPIC_BASE_URL to Z's API. He covers pricing (~5x cheaper than Opus 4.8), where GLM wins and loses against Opus, and a per-directory trick to keep GLM and Opus projects side by side.
Nate B Jones launches Open Skills — a public library of 31 reusable agent procedures (plus 7 runbooks) packaged as skill.md files that travel across Claude Code, Codex, Cursor, and any harness. The pitch: stop re-explaining how you work to every new agent — encode procedures once, scope them, compose them into runbooks, and bake verification into the contract.
Nate B Jones argues the critical 2026 agent skill isn't building — it's ownership and "care and feeding." Any system that reads real context, produces work you act on, or touches a shared workflow needs a named owner. He gives a simple operating model: give each agent a job, a diet, boundaries, and a review loop, plus an "owner card" / agent registry for teams.
Fahd Mirza installs a Pi-Reasoning fine-tune of Qwen 3.6 27B (Q4_K_M GGUF) with llama.cpp, wires it into Hermes agent, and tests it on bug-fixing, creative coding, and writing. The model uses baked-in multi-token prediction (MTP) plus speculative decoding for speed, fits in ~20GB of VRAM, and held up well on a real full-stack bug fix.
ChatGPT rolled out a revamped Scheduled Tasks feature with its own dedicated page, letting paid users (Go, Plus, Pro, Business, and Enterprise on web and mobile) schedule recurring background jobs — like a daily morning briefing, brand or competitor tracking, or an automatic AI-news scan.
Nick Saraev pits the open-weight GLM-5.2 against Opus 4.8 across roughly 40 creative coding scenes — 3D/WebGL, dashboards, landing pages and mini-games — and finds GLM frequently matches or beats Opus on visual "taste." He then walks through running GLM-5.2 inside the Claude Code harness (plus Open Code and Crush) via OpenRouter, and ranks the most cost-effective providers.
Nate B Jones uses Vercel's sales agent — which got better after the team deleted 80% of its tools — to argue the real 2026 agent story is maintenance, not building. The "harness" around the model (sources, memory, tools, permissions, proof, stop conditions) must be continuously pruned, because agents break in two directions: the world drifts and the model improves.
Nate Herk demystifies "loop engineering" — instead of prompting a coding agent yourself, you design a loop that prompts the agent. A loop is a trigger, an action and a stop condition, built on two pillars: an objective goal and a verification method. He argues most tasks need only a single reason–act–observe loop with a good definition of done, not fleets of agents.
Tech With Tim builds three Python agents on the open-source AgentSpan framework — a conversational agent with memory, a RAG agent over a company database, and a multi-agent orchestrator — line by line. The focus is what makes an agent production-ready: durability across crashes, retries, human-in-the-loop, observability, long-running tasks and scale, all handled by a local AgentSpan server.
Developers Digest walks through his go-to stack for shipping an AI app fast: Claude Code scaffolds a Next.js + Vercel AI SDK ChatGPT-style clone, routes models through the Vercel AI gateway, and deploys it end-to-end — creating a private GitHub repo and wiring up auto-deploy on every push — all driven by natural language with almost no hand-written code.
Fahd Mirza installs a coding-focused fine-tune of Gemma 4 12B — trained only on examples whose reasoning produced code that ran and passed tests — runs it locally with Ollama, and wires it into the Hermes agent. He puts it through three real tasks: fixing a tie-breaker bug in a World Cup tracker, generating an HTML animation, and optimizing a slow SQL query (two of three pass).
OpenAI changed how Codex rate limits work: instead of losing your usage window when you hit a limit, you can now save rate-limit resets and spend them on your own schedule. Plus, Pro and Business users start with one free banked reset (redeemable within 30 days), and for two weeks Plus/Pro users can invite up to three friends to try Codex.
freeCodeCamp's full course builds an OpenClaw-style agent from scratch: a chat app you can also message on Telegram, with persistent memory and the ability to take real actions across your apps. It's built on Vercel's AI chatbot template, wired to Composio's 1,000+ toolkits, and given long-term memory with Supermemory — with context engineering (surfacing toolkits, not every tool) treated as a first-class concern.
A new "OpenAI Developers" plugin for Codex connects it to the OpenAI platform, helps create and wire API keys, scaffolds apps with the Responses API and Agents SDK, and reads OpenAI errors to explain the fix in plain language. Install it from the plugins area, then prompt "Build me a simple AI content tool using the OpenAI Responses API." (Much of the video is community promotion; the concrete takeaway is the install-and-prompt workflow and the error debugging.)
Nate Herk and software engineer Cole Medin lay out how to stop "vibe coding" and start directing coding agents — using Claude Code as a "second brain" that runs your business. The repeatable loop: plan with context, build, verify, then evolve your system every time. They define what a "harness" actually is, show practical validation strategies (Playwright, render-and-inspect), and close on a sober security lesson: assume anything the agent can touch, it eventually will.
A clean, beginner-friendly walkthrough of Claude Connectors: link Claude to Gmail, Google Calendar, Notion and 200+ services from the chat interface, how the read-only vs. action-approval permission model works, and how to reach 9,000+ more apps — and let Claude actually send, not just draft — using the Zapier MCP server.
Kilo Code shows a concrete automation: a Kiloclaw agent that watches your calendar and, whenever it detects a first-time external meeting in the next 30 minutes, automatically researches who you're meeting with and drops a briefing into Slack — background, company, recent news, and talking points. A clean example of the event-triggered pattern: calendar event → research step → push to your messaging tool.
Fahd Mirza runs Moonshot AI's new Kimi K2.7 Code (a 256k-context, always-thinking MoE model, ~1T total / ~32B active) through the Hermes agent. From a single prompt it ran the full engineering loop on a 4,000-file SSL-monitoring app — read, planned, built, self-debugged an off-by-one error, verified with live curl calls, and cleaned up — in 7m47s; a second test turned an aerodynamics image into five working physics simulations in five languages.
Claude Code 2.1.178 lands three changes that matter for multi-agent work: a ripgrep-based grep for ~5–10× faster searches, a surgical Tool(param:value) permission syntax with wildcards, and — most importantly — sub-agent spawns that are now evaluated by the permission classifier before they launch, closing a gap where a sub-agent could bypass the parent's rules. Plus a batch of background-session and worktree bug fixes.
IndyDevDan ran Fable 5, Opus, and Sonnet across 15 live-built agent sandboxes and argues the honest metric for a frontier model is price-per-intelligent-agent-hour, not price-per-token: Fable cost ~2× Opus and used more tokens but finished ~20% faster. His bigger point — Fable 5 is best used to orchestrate sub-agents, not as a single-task worker. (Analysis, not a how-to; the "banned" framing is developing reporting.)
Bart Slodyczka wires Hermes Agent to a local Gemma 4 12B model in LM Studio on a 16GB M4 Mac Mini — and uses Claude Code to drive the whole setup. The practical core: the RAM-vs-context balancing act on 16GB (landing ~12GB model / ~67K context), keeping the Mac always-on, QAT vs regular weights, and staying local/private with browser mode instead of paid web-search APIs.
Fahd Mirza runs Moonshot's Kimi K2.7 Code against Zhipu's GLM-5.2 inside Hermes Agent on a real World Cup app with a planted FIFA tie-break bug. Both fix the root cause and build a new round-of-32 bracket; Kimi was faster with an extra flourish, while GLM won a from-scratch HTML generation test. Verdict: neck-and-neck — test on your own use case.
Nate B Jones argues OpenAI's Codex isn't a coding tool so much as the first agent that makes the whole computer feel like something you hand work to — shifting from "ask AI for an answer" to "give the computer a job and let it loop." Covers the chief-of-staff thread, giving objectives instead of asks, and the app-first → agent-first compute shift. Analysis, not a how-to.
A short Kilo Code clip in which Chris Alexiuk argues Model Context Protocol has settled into its intended role — a useful adapter for hooking agents to context and tools — rather than the revolutionary technology some expected, and will persist alongside other useful protocols. Analysis, not a how-to.
Kilo Code demos using KiloClaw as an inbox watcher: each morning it scans incoming email and posts a Slack digest sorting it into what needs a reply today, what was missed, and what can wait — flagging overdue messages with their age.
How to run the Claude Code harness for free by plugging the free Nex-N2 model (262K context, on OpenRouter) into the open-source free-claude-code project — with a voice layer and the same model usable in Hermes, Kilo Code and Pi. Includes the creator's honest caveats on rate limits.
Fahd Mirza drives the new open-source Nex-N2 (Next N2 Pro/Mini) through the Hermes coding agent on OpenRouter, building a full-stack Django + React banking app with five intentional bugs to fix — looping for over an hour and 144 tool calls to a working result.
Analysis: Nate B Jones argues the real WWDC 2026 story is Apple making the operating system itself agentic — via App Intents, a Foundation Models Swift framework, Core AI and Xcode agents — while Google and Nvidia supply raw model capability and compute.
Allie K. Miller's two-second tip: type /goal in Codex or Claude Code with an objectively verifiable condition and the agent loops on itself — even using AI judges — until the goal is provably met.
Practical tips for squeezing maximum output from Claude Fable 5: plan around 5-hour session windows, use the $200 max plan strategically, and have Fable generate configs that cheaper models can run.
Overview of connecting Claude Code to a locally-running Ollama model for a free offline AI agent setup.
Nate B Jones argues the real question isn't which AI coding tool is better — it's what each tool trains you to do. Claude Code steers fuzzy work; Codex dispatches well-defined jobs across parallel agents.
The Kilo Code team reports 75-80% of Gartner Summit enterprise conversations focused on AI cost control over adoption — plus insights on GitHub Copilot's consumption-based pricing shift and growing open-weight model acceptance.
Last 30 Days is a 40K-star MIT-licensed AI agent skill that searches Reddit, X, YouTube, HackerNews, and Polymarket in parallel, scoring results by real engagement rather than SEO authority.
ChatGPT's latest update lets you generate visual charts directly in chat by typing plain-text requests — no Excel or file uploads required, works on mobile.
Hermes Agent 0.16 adds a native desktop app, remote gateway support so the UI can connect to a server-hosted instance, a full web dashboard admin panel, fuzzy model picker, /undo command, and a major skill set cleanup. 399 desktop issues closed.
Anthropic's Fable 5 is available in Kilo Code. Paste a GitHub screenshot, prompt Fable to recreate it, and 10 minutes later you have a near-identical UI clone with real mock repositories and code — including push/pull. Total cost: $4.07. Switch to Sonnet or other cheaper models mid-session for follow-up edits.
Kilo Code hosted a live webinar with MiniMax exploring their new M3 model capabilities and how they integrate with Kilo Code's 500+ model gateway.
OpenAI's finance team uses Codex for month-end reporting, executive slides, dashboards, vendor risk reviews, and journal entry preparation — turning messy manual workflows into repeatable automated processes.
OpenAI's new Codex data analytics plugin turns Codex into an agentic data analyst for your team. It gathers context across multiple systems, builds business impact reports with charts and detailed breakdowns, creates live editable interfaces, and exports to Google Slides in your company templates — all in a few minutes instead of hours.
Kilo Code put Claude Opus 4.8 and MiniMax M3 head-to-head on a real-world coding task: building a webhook delivery service in TypeScript with 17 intentional bugs. MiniMax is at least 10× cheaper — and it's not 10× worse. Opus found 15/17 bugs at highest reasoning, MiniMax found 13/17 at a fraction of the cost.
Kilo Code and NVIDIA co-hosted a webinar on AI-assisted coding, covering NVIDIA GPU integrations and model acceleration within the Kilo Code platform.
Kilo Code's KiloClaw personal AI assistant can clone repos, fix GitHub issues, and complete work tasks autonomously — accessible via Kilo Chat or Telegram without opening a terminal.
Codebase indexing is back in Kilo Code with semantic search support. Setup: open settings → indexing → toggle on → pick an embedding provider (KiloTokens, Mistral, Ollama+LanceDB, OpenAI, OpenRouter, Gemini). After indexing, the agent gains a semantic search tool that finds the right files and line ranges in one call — no grep loops.
AICodeKing breaks down the Codex 4.0 app update: App Shots (Cmd+Cmd to capture the frontmost window), Goal Mode, Remote Computer Use, Plugin Sharing, and better browser annotations — showing how OpenAI is evolving Codex from a coding agent to a full workspace agent.
Kilo Code hosted a 3-hour live workshop on building with KiloShop, covering the integration between Kilo Code and e-commerce workflows with hands-on demonstrations.
Gas Town by Kilo is now generally available. Steve Yegge's Mayor+Polecats+Refinery agent network runs on Kilo's managed cloud, deployable in seconds. The Wasteland — a federated work commons with a shared Wanted Board — is included. Run it across 500+ models through Kilo's zero-markup gateway at app.kilo.ai/gastown.
Skill Leap AI runs GPT-5.5 (with extended thinking) against Claude Opus 4.7 (with adaptive thinking) in 10 real-world tasks judged by Google Gemini. Tasks include app building, writing, landing page copy, business strategy, data analysis, teaching, and more. Claude wins overall; ChatGPT takes business strategy and features.
ChatGPT Workspace Agents let you build custom AI agents via chat or Agent Builder. Each agent gets its own skills (auto-generated), knowledge base, memory folder, and tool access — deployable in ChatGPT and Slack. Available on Business, Enterprise, and Education plans.
KiloClaw ('Kilobyte') has its own GitHub account. For any repo it has access to, Kilobyte can clone it and fix GitHub issues from wherever you are via Kilo Chat or Telegram — no commands, no terminal, no babysitting. Every KiloClaw instance ships with Kilo CLI built in.
Nimbalyst is an open-source visual workspace built from the ground up for Codex and Claude Code. It adds a GUI layer — Kanban board, Mermaid diagrams, Excalidraw drawings, and configurable autonomy controls — on top of the CLI tools that normally lack them. Crucially, it works with both Codex and Claude Code simultaneously, not locked to either one.
Complete guide to free local agentic coding: VRAM determines max model size (8 GB→7B, 24 GB→32B, 64 GB→70B), two-model setup with Qwen 2.5 Coder for autocomplete and a larger Qwen model for agentic tasks, LM Studio local server at localhost:1234. Works offline, no subscription required.
Nate Herk's full AI operating system on Claude Fable: CLAUDE.md as a router pointing to all knowledge files, the four C's framework (Context → Connections → Capabilities → Cadence), skills and subagents, and the "other worlds" folder for consolidating multiple repos under one project.
Overview of connecting Hermes to LM Studio for fully local, free, private operation. Recommended models: Nous Research models (built by the Hermes team), Qwen 3, or GLM 4.7 Flash.
Deep dive on Claude Code subagents: custom agents live in .claude/agents/ as markdown files with YAML front matter. The description field is the trigger (progressive disclosure). Assign cheaper models per agent; use disallowed_tools to enforce read-only agents. Fix misfires by tightening the description.
Write nine context files before the agent touches a line of code: product definition, architecture, folder structure, code standards, UI rules, design tokens, library patterns, build plan, and a living progress tracker. Write them once — they travel with the project forever.
Kilo Code's Agent Manager provides a kanban dashboard for running multiple coding agents simultaneously, each in its own git work tree. Run two models on the same task to compare results, review syntax-highlighted diffs, open any work tree in VS Code with one click, and track PR status per card.
32 practical Claude Code workflow improvements: /init auto-generates CLAUDE.md, keep it under 200 lines and route to external files, /compact at 60% context with a "keep" parameter, plan mode before every session, parallel sub-agents with Haiku for cheap processing, and custom skills in .claude/skills/.
Cole Medin explains the "lethal trifecta" security risk all personal AI agents face, then walks through his Claude Code second brain: SOUL.md and user.md memory layers adapted from OpenClaw's open-source patterns, Obsidian vault integration, and a GitHub starter template for building your own scoped agent.
Combining Claude with Hermes Agent gives Claude persistent memory across sessions via SQLite, an auto-improving skill system, and scheduled task automation. Hermes can spawn Claude Code as a sub-agent for file and code operations, with Jarvis voice mode allowing hands-free task execution via phone. An Obsidian-based "Agent OS" dashboard ties everything together in dedicated agent rooms with shared memory.
A demo of a multi-agent SEO system using OpenClaw and Hermes that automates keyword research, content writing, and WordPress publishing on a schedule. A 12-agent swarm can handle competitor analysis, technical SEO, internal linking, and backlink planning simultaneously, and Hermes can deploy full websites to Netlify with a single prompt.
Hermes now includes an "Idea Foundry" pipeline where you submit an idea in any form — one line, a voice note, a link — agents classify and draft a full plan, you approve or reject at a single human gate, and sub-agents build the actual deliverable. Completed projects and their build notes are stored in an Obsidian vault.
Google's Gemma 412B open model can be plugged into Hermes Agent OS as a free, local brain for full offline operation. A dual-brain setup is possible where a stronger model handles complex tasks while Gemma 4 handles lighter jobs, all managed from the Hermes web dashboard. Gemma 4 requires 16GB VRAM for local run or a free API option exists for weaker machines.
The Hermes Agent OS now includes an Obsidian "Memory Galaxy" visualization that renders your entire Obsidian vault as a 3D star map, with each note as a star and recent notes glowing brightest. Hermes can query this galaxy for date-specific context, and every conversation agents have automatically adds new notes back into the vault for a growing, self-improving shared memory.
Instead of using Claude as a stateless chatbox, build an agentic operating system where Claude and Hermes each get dedicated rooms in a single dashboard with a shared Obsidian memory vault. The system includes a Kanban board, goals page, journal, and content studio — projects started in Hermes can finish in Claude with full context via the shared vault.
A quick look at Hermes's Skills Hub, which lets users search thousands of free skills from skills.sh, Claude Hub, Claude Marketplace, and GitHub in one interface, with one-click installation and safety scanning that color-codes skills as built-in, trusted, or community.
Hermes can now be called on the phone using ElevenLabs for the voice layer and Twilio for the phone number, with Hermes acting as the brain that has memory, tools, and past sessions. A simpler in-app Jarvis voice mode is also available without a phone call. Claude 3.5 Haiku gave the fastest responses in testing.
Julian Goldie shows how to wire the Claude Code CLI to free model APIs on OpenRouter — including MiniMax M3 (1M token context), Gemma 4, Hermes 3, and Nvidia Nemetron — eliminating per-token costs while keeping full Claude Code functionality inside a custom agent dashboard with voice input and file preview.
Hermes V0.16 demo: Gmail via MCP for 24/7 email management, real-time voice conversations with MiniMax M3, the Jarvis voice-command interface for hands-free computer control, and a Kanban-based multi-agent task board with a built-in goal-achievement judge.
V0.16 overview: unified dashboard for skills/schedules/sessions, Jarvis voice agent for hands-free commands, Nvidia Nemotron-3 Ultra and Step 3.7 Flash at zero cost, one-click skill browser with security scanning, and a desktop app that removes the terminal requirement entirely.
Detailed walkthrough of the new Hermes Skills Hub Browser — search skills from skills.sh, Claw Hub, Claw Marketplace, and GitHub; preview each skill's skill.md instructions before installing; run an automated security scan for a trust verdict; and manage installed skills by tier.
Conceptual overview arguing that terminal-based Hermes limits productivity, and that a custom "agent operating system" with unified Obsidian memory, Kanban task boards, and multi-model switching unlocks goal-mode automation and persistent multi-agent coordination. Analysis, not a setup guide.
Allie K. Miller shares the story of a first-time developer who used Claude Code to build a medication management app — with photo-to-schedule parsing, drug interaction checking, and a doctor-ready print summary — in five hours, secured with a Cloudflare Worker proxy and Microsoft Entra ID.
Complete beginner's guide to Hermes Agent: install on a VPS for 24/7 operation, understand the memory system (user.md, memory.mmd), use 90+ built-in skills with progressive disclosure, configure a Soul personality file, set up Crons, and enable the self-improvement loop that makes Hermes better over time.
The "Grill Me" Claude Code skill relentlessly interviews you about a process until it has complete context, then checkpoints the Q&A to a /brainstorms/ file after every answer — so you jump to 90% skill quality on the first iteration instead of improving slowly over many runs.
Run JetBrains' new Mellum 2 model locally via vLLM, connect it to an MCP filesystem server for real file operations, and use it inside Hermes Agent. Mellum 2 is a 12B MoE model (Apache 2.0) with a 131k token context window at 2.5B-dense compute cost.
Side-by-side comparison of Odysseus (PewDiePie's new open-source AI agent) versus Hermes Agent. Hermes wins for multi-agent orchestration and 24/7 background operation; Odysseus suits single-agent local setups and local-model users.
How to wrap Claude Code in a custom agent dashboard alongside Hermes Agent and HyperFrames (open-source HTML-to-video tool by HeyGen) to create an autonomous content production pipeline. Note: contains significant paid-community promotion.
How to install Claude Code and Hermes side by side, use dynamic workflows that spawn parallel sub-agents, load skill bundles in one command, and apply four new Hermes security upgrades: Bitwarden key storage, prompt injection guard, 4500× faster memory search, and push notifications.
MiniMax M3 adds built-in voice chat to OpenClaw and Hermes — speak to your agent and it responds aloud via four voice modes. Works from phone via Telegram for hands-free agent control, and extends to image and video generation in the same model.
Hermes Desktop is now in public preview on Windows, Mac, and Linux. An overview of all 7 key features: real-time task visibility, drag-and-drop file upload, voice mode, easy settings panel, command center for cron and skills, and multi-agent parallel coordination.
Hermes shipped a feature-complete browser admin panel — manage models, sessions, skills, cron jobs, API keys, and MCP tools without touching a terminal. Includes a new chat UI, searchable one-click skill install, dual-model config for rate-limit avoidance, and mobile-responsive design.
Alex Finn walks through every feature of the new Hermes Desktop app: session threads with folders, the Artifacts panel for links and files, turning off token-wasting default skills, the cron job UI, managing multiple agent profiles, and setting memory compression to 0.5 for better recall.
After 500+ hours in Claude's ecosystem, Nate Herk ranks every Claude Code feature from D tier to S tier — surfacing underused features like dynamic workflows, /deepresearch, git work trees, and the Google Workspace CLI that change day-to-day knowledge work.
Bart Slodyczka shows how to route Claude Code through any local model at zero cost using Anthropic's official Co-work on 3P feature — enabling LM Studio as the backend with a Claude-compatible model identifier.
Full walkthrough of installing Hermes Desktop on Ubuntu and connecting a local Ollama model — covers themes, personas, MCP tool management, Telegram/Discord skill configuration, and session management via the new GUI.
Side-by-side comparison of Hermes and OpenClaw: Hermes is rated smoother with better docs and unique features (Kanban board, persistent goals, MCP catalog); Hermes usage is trending up on OpenRouter while OpenClaw has declined since Hermes launched in February.
Answers common Hermes questions: use the Kanban board to break goals into parallel subtasks, run multiple profiles simultaneously, use goals mode for autonomous long-running work, and wire Obsidian as persistent memory via MCP.
Overview of running Claude Code at zero cost by routing it to a free model on OpenRouter with a 1 million token context window, connected to an agent OS and Obsidian for memory.
Overview of how the Claude API enables businesses to embed Claude as an autonomous agent in their own software — no chat window, no human typing — demonstrated with integration into an agent OS dashboard.
Quick overview of running Hermes at zero cost by connecting Step 3.7 Flash (free for 30 days) through an agent OS — Hermes handles autonomous background tasks at no API cost for the trial period.
Connecting Google NotebookLM to Hermes via MCP creates a content pipeline that converts any PDF, doc, or video into podcasts, infographics, and slide decks with a single Hermes command.
DFlash's PFlash layer now auto-tunes its compression ratio during Hermes sessions — no more manual keep_ratio tuning. Demo shows prefill compressed from 3,572 tokens to 148 on an RTX 6000 GPU for a 10× speedup on long-context agent workflows.
The Zo MCP gives Hermes access to 280+ tools across 15 platforms — Instagram, Twitter, WhatsApp, LinkedIn, and more — enabling fully automated social media: AI-generated posts, real-time comment replies, WhatsApp lead qualification, and daily performance analytics from a single Telegram chat.
Hermes now ships with a reviewed MCP catalog — browse and install tools with a single command instead of editing config files. The update adds per-tool action whitelisting, automatic updates while running, parallel execution of safe tools, and Hermes can now expose itself as an MCP server for other agents.
A voice-controlled Hermes agent powered by MiniMax M3 (1M token context, natively multimodal) lets you control your full agent stack hands-free — tap once to speak, Hermes reasons and replies in a natural voice. Supports multiple accents, runs locally, and connects to your full memory and tool connections.
A 5-step workflow pairs Claude Opus 4.8 (released May 28 2026 — 4× more honest code review, multi-agent flow support) with Gemini 3.5 Flash (4× faster processing) to produce working SEO tools via plain-language prompts. Claude does deep thinking and building; Gemini does fast sorting and ideation.
Julian Goldie shows how to unify scattered AI terminals into one Hermes Agent OS with a Kanban task board, one-click MCP connections, a visual workspace of all created assets, and a persistent Obsidian memory layer shared across OpenClaw, Hermes, and other agents.
MiniMax M3, a new frontier-level agentic model from China, connects to Hermes agent via Ollama for free—giving Hermes a powerful brain for autonomous 12-hour tasks, local app control, web search, and scheduling. One command pairs the two; use OpenRouter or the MiniMax coding plan for faster speeds.
Hermes Workspace is a community-built UI for Hermes agent that lets you switch between multiple AI models and launch parallel agent swarms from one browser tab. This video covers installation, adding providers via OAuth, and how to use Claude Code to fix the inevitable backend sync issues.
Combining Hermes agent with a custom Agent OS dashboard gives you Claude, Gemini, and ChatGPT in one interface via OAuth—no separate API keys. A single prompt can trigger a 12-step workflow from research to publishing, and the system learns your tasks automatically over time.
A detailed seven-layer blueprint for building a personal AI OS with Hermes, Claude Code, Obsidian, and OpenRouter—all free. The system compounds over time because agents write every output back to a shared Obsidian vault, so each new session starts with full context from all previous work.
Once AI agents are embedded in an enterprise with a persistent context layer, institutional knowledge compounds relentlessly. By month six, agents surface cross-silo connections no individual possesses—and can onboard new engineers to full productivity in days rather than weeks.
Agent-Vault is a free npm tool that sits between AI agents and your config files, showing agents placeholder tokens instead of real API keys. Secrets stay encrypted on your machine, and piping secrets out is blocked at the system level — stopping prompt-injection exfiltration before it can start.
Claude Opus 4.8 ships dynamic workflows that can spawn up to 1,000 parallel sub-agents, with reviewer agents that verify results before handing anything back. Julian Goldie explains ultracode mode, the five-step Goldie swarm stack, and why Agent OS is the essential companion for keeping a swarm aligned to your coding standards.
Julian Goldie answers community questions about getting more from Hermes: connecting Obsidian as a personalized knowledge base, managing skills in the Agent OS dashboard (which preserves full conversation history unlike raw terminal), creating named specialist profiles with separate soul files and memory, and wiring Hermes into a Claude Code business dashboard.
Three major Hermes updates landed simultaneously: tool search auto-activates when tools exceed 10% of the context window (boosting accuracy from 49% to 74%), a built-in video production agent powered by free open-source Hyperframes generates full videos from a single prompt, and Step 3.7 Flash is available free for 30 days via hermes update then hermes model.
Claude's desktop app has a built-in third-party inference gateway that lets you swap Anthropic's API for any local model from LM Studio, Ollama, or OpenRouter — no Anthropic account required. The key trick: rename your local model's API identifier to a Claude name like claude-opus-4.8 so the desktop app's model discovery accepts it.
Nate Herk demystifies Claude Code's dynamic workflows from Opus 4.8 — a JavaScript-orchestrated system that can spin up hundreds of parallel sub-agents. He draws clear lines between skills, sub-agents, agent teams, and workflows, and explains why one workflow burned half his $200/month plan in a single run.
Nous Research shipped a curated MCP catalog for Hermes that replaces manual config-file editing with an interactive picker. Run hermes mcp, pick a tool, and it installs — no config files. Every catalog tool is pre-reviewed by the Nous team, and you can allowlist or blocklist individual actions for fine-grained control over what your agent can touch.
Hermes v0.15 ships a tool search feature that keeps only core tools in the agent's context window and retrieves others on demand, raising tool-selection accuracy from 49% to 74%. The update also adds a planner/doer agent split and Kanban-style swarms for parallel task coordination. Update with hermes update.
Wiring Hermes to a local Obsidian vault gives it persistent memory — your goals, past tasks, and context are loaded on every run without re-pasting. The vault is plain markdown, so Hermes, Claude, and OpenClaw can all read from the same shared brain. Hermes also writes new notes back automatically, so memory grows without manual effort.
A free middleware proxy bridges Claude Code to any OpenRouter model — including free-tier options — in five steps. Install the helper, plug in a free OpenRouter API key, and launch Claude Code normally. Quality varies versus native Anthropic models, but it's a practical way to experiment with Claude Code's agentic loop without a paid subscription.
Julian Goldie runs a head-to-head comparison of OpenHuman (by Tiny Humans) and Hermes (by Nous Research) — two free local AI agents. OpenHuman wins on day-one ease with instant app-memory and no-code setup, but is still early alpha. Hermes wins overall: MIT licensed, 64K GitHub stars, 200+ model support, and a skill-based memory that compounds over years of use.
Craig Hewitt, who runs two Hermes agents in production, debunks six persistent YouTube myths: you need a Mac mini, Hermes replaces Claude Cowork, you should build many agents immediately, memory drift is solved, your whole business runs on Hermes from day one, and that you should install skills from third-party repos directly. Honest, grounded, and backed by months of real usage.
OpenClaw 5.27 focuses on reliability over features: group chat texts are isolated from the agent's core instruction context to block prompt injection, risky commands are filtered, big changes require admin approval, and reply latency is reduced by fixing a background-cleanup bottleneck. A new Pix video provider and steadier memory routing round out the release.
Nate Herk's four C's framework for building a personal AI OS on Claude Code: Context (what the system knows), Connections (what tools it can reach), Capabilities (skills defining how you work), and Cadence (autonomous execution while you're away). Core insight: context is king — everyone has the same models, but your personal context is the differentiator. Opus 4.8 feels more like 4.6 — more honest, less prone to going off-scope.
One of OpenClaw's biggest releases in months ships seven targeted security fixes (SSRF protection, prompt-injection guards, Bitwarden integration, auth rate limiting), a new durable transcript system enabling real-time meeting notes that survive agent restarts, a unified voice SDK across all voice channels, reaction approvals for Signal/iMessage/WhatsApp, cron now defaulting to 8 concurrent runs, and Sharp replaced by Raster Mill for cleaner installs on ARM and Linux.
Hermes v0.15 "velocity release" trims the codebase 76% from 16,000 lines for sub-second startup, upgrades the Kanban board into a full multi-agent swarm platform (one task, parallel agents), makes session search 4,500× faster at 20ms using local indexing instead of API calls, integrates Bitwarden Secrets Manager for encrypted key storage, adds push notifications on task completion, and introduces skill bundles for loading related skills in one command.
Kevin Stratvert's complete skills tutorial walks through building a skill using Claude's own skill creator (which asks clarifying questions before drafting the prompt), testing against real examples, iterating on output, and invoking it with /skill-name. Skills sync automatically across Chat, Cowork, Claude for Word/Excel/PowerPoint, and can be exported as zip files and imported into Claude Code's global or project-level skill folders.
Alex Finn's comprehensive Hermes guide explains why he's shifted from OpenClaw to Hermes (update reliability), how to install from scratch or import from OpenClaw, which model tier to pick, and when Hermes is the right tool vs Claude Code or Codex. Hermes for general always-on work and prototypes; Claude Code/Codex for focused multi-file coding sessions. The self-improvement loop — where Hermes edits its own skills based on what worked — is highlighted as the key differentiator.
After 100 hours with both tools, Nate Herk finds more overlap than most comparisons admit: both support skills (markdown), MCP, CLI, desktop apps, hooks, sub-agents, and cloud delegation. Claude Code leads on customization depth (30 hook events vs 6, auto-spawning sub-agents, /ultraplan, /ultrareview, /loop, Agent SDK). Codex leads on unified shipping (built-in git work trees, in-app browser with visual commenting, sharper computer-use QA). Claude Code feels more creative; Codex follows instructions more precisely.
Most people are still using Claude Cowork like a chat window. This video maps the correct mental model: Projects over standalone sessions, Connectors (Gmail, ClickUp, Slack) as the tunnels for real action, and skills that run on a schedule. The centerpiece demo builds a Gmail spam-filter skill that automatically archives unwanted email every morning at 8am — shifting from "Claude reports, you act" to "Claude acts, you observe."
Alex Finn runs five Hermes agents simultaneously and shares six concrete workflows: /slashgoal with metaprompting for 24-hour autonomous tasks, a daily Kanban board routine for offloading to-do items to agents, browser-based competitive teardowns (Hermes navigates the site, inspects the console, generates a full tech-stack report), a personal memory wiki that logs every agent conversation, and combining Hermes prototypes with Claude Code for production-quality output.
Julian Goldie demonstrates the "Goldie Omnipresence Stack" — a layered Hermes agent OS that automates content production end-to-end. Enter one keyword and the system writes SEO articles, generates images via Grok Studio, produces scripted videos through the Hyperframes skill, and publishes everything across five websites simultaneously. A kanban task board routes each job to the most relevant specialized agent profile and marks subtasks complete automatically.
Nate B Jones argues that prompt engineering is now table stakes — frontier models like Opus 4.7 are roughly 100x more capable for agentic work than models from six months ago, yet most people still interact with them like junior assistants. His "AI Question Method" reframes the interaction: convey your perspective and thesis, then ask questions that open up problem scope. Best applied to heavy knowledge work in Claude Code, Claude Cowork, and CodeEx rather than defined agentic pipelines.
OpenClaw 5.19 ships a no-code custom plugin builder — describe what you need, let AI write the tool, install it. Five new built-in skills added (meme maker, diagram builder, Python debugger, Node.js inspector, Obsidian). Skills can now be shared across all projects. Android gets real-time voice mode. Grok works via OAuth for free image generation and live X search. Telegram forum topics now run in isolated lanes, and the browser agent handles pop-ups and cookie banners it previously couldn't see.
Nate Herk breaks down Claude Code's prompt caching: cached tokens cost 10% of normal input, the cache TTL is 1 hour on a subscription (5 minutes on raw API or for sub-agents), and switching models mid-session breaks the cache entirely. Three habits cover 95% of users: don't pause longer than an hour, start fresh when switching tasks, use Projects for large documents. A free session handoff skill summarizes work-in-progress so you can /clear and pick up exactly where you left off.
Julian Goldie walks through five zero-cost Hermes upgrades. The Agent OS (stored in soul.md) loads your projects, tone, and priorities into every conversation automatically. Kanban teams spawn isolated sub-agents for research, writing, and outreach in parallel. An AI SEO skill embeds your keyword process so content stays on-strategy. Hyperframe templates produce full video drafts from a topic keyword in ~5 minutes. Goals paired with the cron scheduler send daily Telegram check-ins and track progress hands-free.
Hermes's latest release adds Grok 4.3's 1-million-token context window — enough to hold an entire codebase in memory without chunking. The new /handoff command switches models mid-task while preserving full context. The browser tool is 180x faster. Windows now installs in one command. The platform count reaches 22 with Microsoft Teams, Line, and SimpleX Chat. Video generation works with any provider via a single config file, no forking required.
Craig Hewitt demos 12 schedulable Claude CoWork skills — morning briefing, inbox triage, meeting prep, brain dump, and more — all powered by Gmail, Google Calendar, and Google Drive connectors. Key distinction: CoWork skills are separate from Claude Code skills and don't carry over between environments. Skills can be scheduled to run while you sleep (e.g., inbox triage at 6am, 11am, and 3pm). Sonnet handles most knowledge work; Opus reserved for complex financial analysis or first-time builds.
Alex Finn demos eight Hermes updates led by session recall — ask "what did we do on May 10th?" and Hermes retrieves the full session programmatically with no token cost. The /background command queues multiple research tasks while you stay conversational. Native Codex CLI integration spawns a vibe-coding worker in the background. Computer use lets Hermes see and click through your desktop from Telegram. Grok 4.3 OAuth adds real-time X search and AI video generation natively in chat.
Nate Herk argues Karpathy's move to Anthropic is the merger of two aligned philosophies: Karpathy's "context engineering" (structured environments for models, not better prompts) maps exactly onto Anthropic's Claude Code wrapper strategy. Anthropic passed OpenAI in Ramp's business-adoption index (34.4% vs 32.3%) and launched a joint venture with Blackstone and Goldman Sachs for enterprise deployment — signaling a full services layer, not just API access. The model is not the moat; the wrapper is.
Alex Finn demonstrates a workflow pairing Claude Code (or Codex) with Linear — free, cloud-synced project management — to eliminate context drift across sessions and devices. Describe your app once; Claude auto-generates all Linear issues with acceptance criteria, priorities, and scope. Any subsequent session on any device says "work on the next task" and Claude reads Linear, knows exactly what to build, and starts — no re-explaining. Works with both Claude Code and Codex simultaneously off the same board.
Julian Goldie shows how to build a locally-hosted mission control dashboard — built in one Claude Desktop session without writing code — that unifies Claude, Hermes, and OpenClaw. The system uses a Claude CLI bridge, stores all agent conversations in an Obsidian vault, and feeds that vault back to every agent as persistent shared memory. Dashboard features include per-agent analytics, skill management, API key tracking, and a Kanban board synced from chat.
OpenClaw v2026.5.4 adds the ability to join Google Meet calls as a real-time voice agent via Twilio dial-in and a Gemini real-time bridge, with support for mid-sentence interruption. OpenRouter users get response caching and proper app attribution. Version 2026.5.5 follows with patches for Telegram session threading, Discord plain-text command routing, WhatsApp stale-client slowdowns, iOS LAN pairing for home-network setups, and a Windows file-rename fix. Update with claw update.
Full walkthrough for building a Hermes agent on a Hostinger VPS that manages WhatsApp groups entirely from Telegram — no WhatsApp Business API required. The Periscope CRM provides an MCP server that lets Hermes read conversations, send bulk messages, create groups, and label contacts. Environment variables PERISCOPE_API_KEY and PERISCOPE_PHONE_ID are saved to the hosting dashboard, then Hermes installs and configures the MCP server itself from a single Telegram message.
Nate Herk compares three deployment strategies for Claude Code automations and explains the key axis: where does it run (local vs cloud) and how agentic is it (full decision-making vs deterministic script). The loop method — using Claude's built-in cron create / cron list / cron delete tools — requires zero setup but needs the machine on. Terminal loops survive /clear and run up to 7 days; desktop app loops die on /clear and cap at ~3 days. For 24/7 unattended runs, cloud hosting on Modal, Trigger.dev, or a VPS removes the session dependency.
OpenClaw 5.12 arrives as Hermes Agent surpasses OpenClaw in OpenRouter API call volume for the first time. Key fixes: channel libraries now install on demand (not bundled at setup), Telegram runs in an isolated worker that can't be starved, and stalled-stream recovery auto-rotates to a backup model when the AI stops responding. Advice: wait a few days before updating and always run openclaw backup first.
OpenHuman is a new open-source AI agent with 8,000 GitHub stars and a native desktop app—no terminal required. Julian Goldie tests it live, connecting a free OpenRouter API key to avoid subscription costs. Still early beta with login reliability issues; Hermes remains more stable for production. Key safety note: only grant read permissions when connecting AI agents to email or calendar.
Owl Alpha is currently the #1 model used with Hermes Agent by API call volume on OpenRouter—and it's free. Connect via your OpenRouter API key, select Owl Alpha, and you get a 1 million token context window with full tool-use support in under 5 minutes. Handles automation workflows, code generation, and team training tasks at zero ongoing API cost.
Anthropic's deployment arm is backed at $1.5B (Blackstone, Hellman & Friedman, Goldman Sachs); OpenAI's equivalent sits near $10B. Nate B Jones explains why: reliable 100% workflow completion only became possible in spring 2026, and the real value—the implementation layer of harness, evals, permissions, and audits—is where PE firms are placing their bets, not on the models themselves.
Alex Finn shows how to back Hermes Agent with a local model on an NVIDIA DGX Spark for a private, always-on AI employee with no API costs. The DGX Spark runs headless via Tailscale; one plain-English prompt to Hermes handles the full setup. Local models are free once the hardware is paid for—all data stays on device.
Claude Cowork's live artifacts pull real data from Fireflies, Drive, and calendar into interactive dashboards. Allie K. Miller demos how Claude auto-detects your connected tools without being explicitly named in the prompt—then asks for dark mode and neon colors in a follow-up to transform a basic summary into an actionable meeting intelligence panel.
GenSpark Claw packages computer-use AI agents in a desktop app with no terminal setup required. Kevin Stratvert walks through organizing a messy desktop by content type, generating Excel sales reports from CSV data, and scheduling recurring morning briefings on a cloud computer that runs even when your PC is off. Free daily credits included.
DFlash is a speculative decoding engine using block diffusion to deliver 2–3x faster token generation on local hardware. Fahd Mirza connects it to OpenClaw as a custom provider pointed at http://localhost:8080—no API key needed. DFlash now supports tool calling, so Hermes Agent and Codex can also use it as a local backend. A 65k context fits in ~20GB VRAM with 3-bit KV cache compression.
Claude Code shipped a new "agent view" that consolidates all running sessions into one terminal tab. Each session shows a color-coded status — green for done, yellow for waiting on input — and you can navigate between them with arrow keys or click. Eliminates the chaos of juggling multiple terminal tabs when running four or five parallel agents on a large codebase.
After 400+ hours inside Claude, Nate Herk maps mastery into five progressive levels: basic Q&A, Projects with persistent context, multi-step workflows, Claude Code for agentic file editing, and full multi-agent orchestration. The biggest unlock at every stage is the same: stop treating Claude like a search bar and start giving it persistent context through Projects and system prompts.
Nous Research added two free model options — Qwen 3.6 Plus and Owl Alpha — through the Nous Portal free tier. Both have larger context windows than most paid alternatives. Setup takes minutes via hermes setup in the terminal; when you hit rate limits on one free model, switch to the other to keep your agent running 24/7 without interruption.
Pareto Code is an experimental OpenRouter routing layer that automatically selects the highest-ranked coding model for each request. Set a single min_coding_score (0–1) and it picks the best available model above that threshold. Paired with Hermes Agent, this lets agents route writing, debugging, and planning tasks to whichever model performs best on that specific type of work — without any manual model switching.
Julian Goldie demonstrates combining Hermes Agent with AionUI's desktop interface to create a fully autonomous local setup. Hermes handles planning and tool use while AionUI gives agents a visual desktop interface — they can click, type, open apps, and read your screen. Agents chain in swarms, run on a loop, and improve over time. All data stays on your machine.
Nate Herk introduces Printing Press (printingpress.dev), a CLI factory and library for Claude Code. Benchmarks show CLIs use 35x fewer tokens than MCP servers on identical tasks, with reliability climbing from 72% to 100% on hard tasks. The tool ships with 50+ pre-built CLIs for services without public APIs (ESPN, Craigslist, School) and a factory to build custom CLIs in about 10 minutes.
Anthropic's partnership with SpaceX secures 300MW of capacity and 220,000+ Nvidia GPUs. Effective immediately: Claude Code 5-hour session limits are doubled across all plans, peak-hour throttling is eliminated for Pro and Max accounts, and API output rate limits increased from 8K to 80K tokens per minute on tier 1. Builders should retest Opus agent workflows that previously hit walls.
Claude Cowork's new Live Artifacts feature lets you create a no-code dashboard connected to Gmail, Calendar, ClickUp, and Airtable without writing a line of code. Dashboards refresh on open (not real-time), and interactive buttons can write back to connected tools — for example, marking a ClickUp task complete from inside the dashboard.
Nate Herk's one-hour course covers setting up Hermes Agent from scratch on a private server. Hermes ships with 91 built-in skills (out of 684 available), supports scheduled crons for daily news briefings, YouTube comment monitoring, and server health checks, and returns voice responses alongside text. The video includes a direct comparison of Hermes vs Claude Code vs OpenClaw — Hermes differentiates on persistent memory, autonomous crons, and self-directed skill acquisition over long time horizons.
Hermes Agent now supports six browser automation backends — three cloud options (browser.com with stealth proxies, browser-use REST API, Firecraw with scraping tools) and three local options (Camafox Firefox fork with C++-level fingerprint spoofing and live VNC feed, Chrome DevTools Protocol, and Agent Browser). The standout feature: /browser connect links Hermes to your real Chrome browser with all existing logins and cookies, eliminating credential setup entirely.
OpenClaw's April 2026 release enabled multi-model orchestration — running different LLMs for different stages of a single workflow. Nate B Jones explains the strategic implications: memory is now the durable competitive layer, not the model, because the model is increasingly swappable. Build model-agnostic workflows to survive provider changes from Anthropic and OpenAI, both of which made impactful API changes affecting OpenClaw users in April 2026.
AgentSpan (MIT, self-hosted, built by the Netflix Conductor team) solves the production crash problem for AI agent pipelines: when a LangChain/CrewAI/LangGraph pipeline crashes, it normally restarts from scratch and re-executes all side effects. AgentSpan moves orchestration state to a separate server and persists every individual tool call — a crashed pipeline resumes from the exact failed step, preventing duplicate emails, database writes, and API calls.
Fahd Mirza walks through building a complete OpenClaw stack from scratch using only local resources — no paid API. Fresh install connected to IBM Granite 8B via Ollama, Telegram plugin for remote access, and Tavily web search, all installed with single commands. Demonstrates OpenClaw's intentionally lean plugin architecture: start minimal, extend with exactly what you need.
Anthropic announced four major additions to Claude managed agents. Dreaming is a scheduled background process that reviews past sessions and restructures agent memory so agents improve over time without retraining — Harvey Legal saw task completion rates jump roughly 6x. Outcomes lets developers write a quality rubric; a separate grader agent evaluates every output and auto-retries failures, yielding up to 10 percentage points improvement on hard tasks. Multi-agent orchestration delegates work to parallel specialist agents. Webhooks fire on task completion to update external tools like CRMs and email platforms automatically.
Hermes v0.13.0, the "Tenacity" release (864 commits, 295 contributors), is the largest reliability overhaul since launch. Key features: multi-agent Kanban board where AI workers pick up, execute, and hand off tasks with a hallucination gate that catches workers who falsely claim completion; the /goal command that locks an agent onto a persistent objective across turns; session auto-resume that survives gateway restarts; checkpoints v2 with real pruning; and post-write delta lint for Python/JSON/YAML/TOML. Eight security issues closed. DeepSeek V4 Pro and Grok 4.3 added as new models.
Alex Finn's definitive Hermes setup guide explains why he switched his primary recommendation from OpenClaw to Hermes: OpenClaw's daily update cadence consistently breaks the tool (requiring 20–30 minutes of repair per update), while Hermes ships themed, cohesive releases that work on install. Use Telegram for messaging and Claude Opus for complex tasks; ChatGPT 5.5 via the $20/month plan is a viable budget option. Every Hermes task creates or improves a reusable skill file automatically. Recommended two-agent pattern: a cheap "librarian" agent for admin and Kanban management, a main Opus agent for execution.
Rufflow is a free, open-source orchestration layer that sits on top of Claude Code and adds 100 specialist agents, 60 commands, 30 skills, an MCP server, and hooks via a single install command. Three swarm topologies: hierarchical (manager + specialists), mesh (all agents talk to each other), and adaptive (switches based on task complexity). Vector memory uses HNSW indexing — up to 12,500x faster search than standard methods — and persists across sessions. Works with Claude Code, OpenAI, Gemini, and Ollama. A web UI at iuv.io requires zero installation.
Alex Finn walks through seven new Hermes features centered on the dashboard (hermes dashboard) and Kanban board. Unlike chat-based single-thread interaction, the Kanban board lets you run 10–30 tasks simultaneously through dedicated worker agents. Recommended two-agent setup: a cheap "librarian" running on ChatGPT checks the board every 10 minutes, fleshes out triage tasks using stored memories, and moves them to ready — the main Opus agent handles execution. OpenClaw's two main problems: every update breaks the tool, and performance bloat from too many unrelated features per release.
OpenClaw 5.4 beta reworks the Google Meet voice pipeline with Gemini streaming to eliminate audio lag and adds interruption handling. One-word status labels ("Thinking", "Searching", "Writing") now appear across Discord, Telegram, Slack, Matrix, and Teams. Startup is faster via deferred loading. Reviewer's advice: hold off on updating if your setup is stable — this is beta and OpenClaw has had a rough run of breaking releases.
Hermes Agent v1.3 ships Curator — describe your goal, and the system reads the task, scores every available agent and model against each subtask, assembles the right team, and chains the outputs. No manual agent selection required. The picker learns from your feedback over time. Users report tasks that took 30 minutes now take 5, because the right agent is selected on the first attempt rather than after failed runs.
Hermes Desktop v0.6.0 is a free, open-source Mac app that replaces the terminal interface with a native GUI. Three headline features: file bookmarks for one-click editing of skills and memories on the host machine; a searchable, pinnable chat workbench with readable transcripts; and full Kanban board support for multi-agent task management including task creation, assignment, status tracking, and worker log review.
Craig Hewitt cancelled a $5K/month marketing agency after installing Higgsfield's MCP server into Claude Code in 45 seconds. A CMO agent skill reads a brand brief and calls Higgsfield — a generative media hub akin to OpenRouter for creative tools — to produce marketing plans and visual assets in one session. Works with Claude Code, OpenClaw, Hermes, NemoClaw, and Perplexity. Full skills repo shared free.
OpenClaw 5.3 ships three major features: a built-in file transfer plugin (agent reads and writes files without custom code), the /steer command for redirecting a running task mid-execution without losing work, and active memory filters that persist context per-contact and per-project across sessions. New models added: Grok 4.3, Claude Opus 4.7, and DeepSeek V4 Pro. Google Meet join support also lands in this release.
RooFlow (formerly ClaudeFlow, 36K+ GitHub stars) hits v3.6.12 with federation — two RooFlow instances on different machines can now share agents securely via mTLS + ED25519 keys, with a 14-type PII scanner stripping sensitive data before anything crosses the wire. Native tools expanded from 87 to 314. Adaptive backpressure prevents timeouts when an agent gets overloaded. One-line Claude Code install; persistent memory via AgentDB survives restarts.
Nate Herk's 2+ hour course on building an AI operating system inside Claude Code using the four C's framework: Context (what Claude knows about the business), Connections (tools it can act on), Capabilities (what it can do), and Cadence (recurring tasks it runs automatically). Tool-agnostic design is emphasized — tools change every 6 months, so the structure must survive platform swaps. Free setup guide provided.
Claude Cowork's Live Artifacts connect Claude-generated HTML components to live data sources — Gmail, Google Sheets, Notion, Fireflies — creating dashboards that update as your data changes. The Cowork tab uses folder-scoped security (hard wall, Claude stays inside the designated folder) unlike the Code tab which accesses the full file system. Demo covers building, iterating on design, and accessing artifacts later from the Claude desktop app.
After 400 hours building Claude Code agents for real businesses — real estate, HVAC, coaching, marketing — Nate Herk found the same six skill types showing up as paid work every time. Not demos: the boring, reliable skills that save time, cut costs, or eliminate mistakes. The foundation is Anthropic's official skill-creator skill, which produces every other client-facing skill you'll sell.
OpenClaw 5.2 makes Grok 4.3 the automatic default for the XAI provider — no config change needed. The release also rebuilds the plugin install system with proper dependency reporting, a new openclaw plugins list --json flag for status checks, and an npm-first install model with ClawHub as a fallback layer. openclaw doctor now covers more repair cases including state-corrupted installs and beta-channel fallbacks.
The Claude Code CLI accepts any OpenAI-compatible API backend — point it at OpenRouter, NVIDIA NIM, or Ollama and all commands work identically. Nick Saraev demonstrates with DeepSeek Flash V4: a full habit-tracker app built for ~$3 vs. $5–10 in Anthropic credits, delivering an estimated 80–90% of Opus 4.7 quality at 2–5% of the cost. Recommended hybrid strategy: Opus for orchestration, DeepSeek for heavy code lifting.
Hermes agent now integrates natively with LM Studio for a fully local AI pipeline. Models are auto-discovered and loaded on demand with correct context sizing; Hermes automatically selects the appropriate reasoning level per model. Fahd Mirza walks through the full setup: install LM Studio in daemon mode, start the API server on localhost:1234, download a tool-capable model, and connect Hermes — no manual endpoint configuration required.
Pair Claude Code with Microsoft Playwright and you get natural-language browser automation — web scraping, form filling, UI regression tests — without writing a line of boilerplate. Claude Code installs the browser binaries, writes the script, and runs it. Playwright drives a real browser, so JavaScript-rendered pages that confuse basic scrapers are no problem. Output goes straight to CSV, JSON, or a database of your choice.
Claude Cowork accepts any OpenAI-compatible API endpoint — change the base URL to http://localhost:11434/v1 and every skill runs against a local Ollama model instead of Anthropic's servers. Bart Slodyczka walks through the full setup using Qwen 3.6 or Gemma 4. Zero per-token cost, all data stays on-device. Ideal for privacy-sensitive workflows (legal docs, personal finance, confidential client data) where sending content to a cloud API isn't acceptable.
Bart Slodyczka's comprehensive Claude Cowork tutorial covers skills, scheduled triggers, and multi-step pipelines that run without human input. Key insight: skills should be job-scoped, not tool-scoped — "draft follow-up emails to unresponsive leads after 3 days" not "use Gmail skill". Chain outputs from one skill into the next, write state to files for cross-session memory, and test edge cases manually before you schedule anything.
Alex Finn's start-to-finish OpenClaw tutorial treats the agent like a new hire: give it a specific job title in the system prompt, connect only the tools it actually needs, and start with one workflow before expanding. The recommended first project is a daily briefing agent (calendar + news + to-do → morning summary). Once that runs reliably, add a second job. Don't build a ten-tool automated team on day one.
Alex Finn breaks down seven techniques from Anthropic's internal Claude Code usage guide: treat CLAUDE.md as your project's ground truth, use sub-agents for parallel work, run headless mode via claude -p "task" for automation, compact proactively every 30–40 turns, make slash commands for anything done twice, let Opus 4.7 decide when to call which MCP tool rather than managing that logic yourself, and trust the plan phase — Opus 4.7's extended thinking catches far more edge cases than earlier models.
Ollama added native Hermes support — run ollama launch hermes in your terminal, pick any local model like Gemma 4, and Hermes is running in seconds at zero cost. Unlike the OpenClaw + Ollama workflow, Hermes uses its own launch sub-command that handles all configuration automatically. Warning: running this on an existing Hermes install will modify your config.
Opus 4.7 catches its own mistakes during the planning phase before writing code or sending results. Hermes writes a reusable "skill" file after every completed task, so it gets faster at similar work over time. Plugging Opus 4.7 into Hermes via the Anthropic API or OpenRouter gives you a self-improving autonomous agent you can reach via Telegram, WhatsApp, Discord, Slack, or email.
Anthropic launched Claude Design at claude.ai/design — a Lovable-style prototyping tool that builds wireframes, high-fidelity mockups, and slide decks from text. Powered by Opus 4.7's improved visual reasoning (91% vs 84.7%). Set up a design system once with your brand guidelines and every project stays on-brand automatically. Exports to Canva, PDF, PowerPoint, or HTML — or hand off directly to Claude Code for implementation.
Andrew Brown published a full Codex Essentials certification course on freeCodeCamp — free on YouTube with hands-on labs in your own account. Exam code: EXP-CODEX01. Notably, the course originated from a Claude Code Essentials course and a Claude Code Boot Camp is planned on the same ExamPro platform, reflecting the growing overlap between OpenAI and Anthropic agentic tooling.
Make.com now embeds AI agents directly inside automation scenarios. An AI agent step bridges the semantic gap between apps — reading unstructured email content, deciding if it's a genuine client request, and routing it to Trello with extracted details, all without rigid field-mapping rules. The full Gmail → AI agent → Trello intake pipeline requires no code.
Nate Herk upgrades his stock-trading agent to Opus 4.7 and wires it to Claude Code's new routines scheduler — pre-market research, trade execution via Alpaca API, decision journaling for persistent memory, and daily ClickUp summaries. His prior 30-day run on Opus 4.6 beat the S&P 500 by 8%. Routines + Opus 4.7 means the agent runs 24/7 without human intervention.
Fahd Mirza runs Qwen 3.6-35B-MoE locally via vLLM on an NVIDIA H100 and connects it to OpenClaw — no API key, no cloud costs. A single prompt builds a complete React + Vite + TypeScript industrial dashboard: OpenClaw autonomously creates files, runs npm install, starts a server, detects a rendering error, clears the browser cache, restarts it, and fixes the CSS. Full agentic loop with zero per-token cost.
An AMD senior director's analysis of ~7,000 Claude Code sessions found that Opus 4.6 thinking depth collapsed 73% (2,200 → 600 characters), models skipped file reads before edits 33.7% of the time (up from 6%), and user interruptions increased 12×. Hallucinated git hashes, fake package names, and "simplest" appearing 3× more often suggested the model optimised for minimal effort. Nate asks whether Opus 4.7's direct address of all these complaints is coincidence or theatre.
SWE-bench Pro: 53.4% (4.6) → 64.3% (4.7), almost exactly halfway to Mythos preview's ~75%. Nick Saraev finds the same suspiciously clean halfway pattern across all major benchmarks and argues Opus 4.7 is probably Mythos distilled down — a smaller, faster version of the same model rather than an independent architecture. Agentic terminal coding shows a smaller step up (65.4% → 69.4%) because that's where Anthropic's safety caution concentrates.
Five quick wins: (1) load Context7's compressed OpenClaw docs so Claude has a live troubleshooting reference, (2) create agents.soul and user.md to define behavior and load your context into every session, (3) segment Telegram into separate groups with per-group system prompts, (4) run openclaw skills list to discover pre-installed capabilities you may be doing manually, (5) treat the agent as a new employee — minimal access by default, expand incrementally.
Craig runs Castos.com (400+ pages, strong Google rankings) but was invisible in LLMs. The fix: LLM scrapers read top-to-bottom and weight the first clear answer most heavily. "For any best/top/how query, the first one to two sentences must answer the question." He shares 7 strategy changes and an open-source Claude Code project — SEO Machine — that enforces answer-first content writing at scale.
AI agents run at 10–50x human speed on reasoning tasks, but the web was built for human eyeballs: login flows, dashboards, 100-row paginated APIs, rate limits, CAPTCHAs. Every one of these was correct engineering for 50 years and is now an agent bottleneck. The productivity gap isn't a prompting problem — it's an infrastructure mismatch. Fixing it requires rebuilding the web for both agents and humans, not optimising prompts.
Both Claude Code and Google's Antigravity (Gemini-powered) can break large missions into plans, run sub-agents in parallel, manage files, and execute across a codebase. The difference: Code is a terminal CLI that plugs into your existing environment and gives you full primitives. Antigravity is a standalone IDE with a manager view for parallel agents and a built-in browser agent. After 100 hours, Nate recommends learning Code first — the primitives foundation transfers to any tool.
Anthropic research confirms context rot begins at 300–400K tokens — not because the window is full, but because older tokens dilute attention. Bart Slodyczka explains every session command: /clear resets entirely, /compact compresses without losing thread, and checkpoints save state before risky operations. The pattern: compact every 200K tokens on long tasks, clear between major context shifts.
MiroFish runs hundreds of AI agents across hundreds of iterations with different reasoning seeds, then synthesizes their outputs into an interactive knowledge graph. Agents that reach conflicting conclusions are the most valuable signal — high-divergence nodes surface genuine uncertainty. Demo: predicting Dubai real estate trajectories revealed non-obvious EXPO infrastructure correlations no single agent found alone.
Graphify solves Claude Code's cold-start problem: without it, every new session reads your codebase file by file before answering anything. Graphify builds a one-time knowledge graph storing component relationships (not just file contents), which Claude loads instantly at session start. Biggest gains on 50+ file projects. Free, no API key, no cloud upload.
Nate Herk has been using an AI avatar clone of himself on YouTube — created in 10 minutes with HeyGen, orchestrated entirely by Claude Code. Claude Code sequences API calls across HeyGen, script tooling, and output assembly; the human sets the topic, Claude handles the rest. End-to-end time from topic to publishable video: under 10 minutes once the pipeline is configured.
With OpenClaw at 250K GitHub stars and agents deployable in 60 seconds, the installation bottleneck is gone. The gap is now workflow integration — knowing what to delegate, how to structure instructions, and how to measure whether the agent actually adds value. Real gains require weeks of workflow iteration, not a one-time setup. Agents integrated into daily decision loops compound; one-off experiments don't.
Anthropic redesigned the Claude Code desktop app: everything is now organized by project, each project supports multiple concurrent sessions, and the UI shows all active sessions at a glance. Alex Finn's verdict: better than the CLI for most workflows. Parallel feature development pattern: run auth in one session, UI in another, tests in a third — context stays isolated between sessions.
Most users interact with Claude Code in chat mode and only reach 20% of its capability. Tim's professional setup: a CLAUDE.md with project context, 3–5 domain-specific skills (test, review, deploy-check), 1–2 MCP servers (GitHub, database), and sub-agents for testing and reviewing. Sub-agents shine on large refactors above ~500 lines of change — spawn one for the API layer, one for the UI, one for tests, then reconcile.
OpenClaw costs can reach $10K/month for heavy users. Matthew Berman shows how to offload inference to local NVIDIA RTX GPUs — including old gaming hardware — via NIM microservices that expose an OpenAI-compatible endpoint OpenClaw routes to natively. Best workloads for offloading: summarization, code review, structured output. Hybrid approach (cloud for reasoning, local for volume) cuts per-token cost 60–80%.
OpenClaw 4.12 shipped a dense cluster of updates in one week. Key improvements: expanded native tool integrations (fewer custom MCP configs needed) and redesigned multi-agent queue management for teams hitting rate limits with concurrent agents. The queue improvements require explicit opt-in — upgrading from 4.11 won't activate them automatically. Finn recommends immediate upgrade for any production multi-agent setup.
Superpowers pre-loads your skills as a condensed map at session start — replacing file-by-file project exploration and cutting session startup cost by 40–60%. Quality improves because Claude follows proven skill patterns rather than improvising. Setup: install plugin, point at skills directory, add one line to CLAUDE.md. Sweet spot: 5–10 skills. Beyond that, the manifest itself starts consuming meaningful tokens.
Ollama serves local models on localhost:11434 with an OpenAI-compatible API. Connect any MCP server to it — the same servers that work with Claude Code work here. Best models for tool use: qwen2.5 and mistral-nemo outperform larger models on structured function calls. All inference stays on your machine. Hardware requirement: 8GB VRAM for 7B models, 16GB+ for production-quality 13B.
Three-step workflow: Claude Code generates a cinematic video prompt → Seedance 2.0 renders a seamless looping ambient video (match first and last frames) → Claude Code builds the full responsive site around it. Use NanoBanana 2 via key.ai for the reference image — better spatial understanding than GPT for cinematic stills. Spend 80% of iteration budget on the video prompt, not the code.
RALPH = Repetitive Autonomous Loop for PRD Handling (credit: Matt Pocock). Three skills: grill me interviews you relentlessly until shared understanding is reached, create plan locks decisions into a PRD, implement executes the PRD without improvising. Before RALPH: ~40% of outputs required significant correction. After: under 10%. The gain isn't the model — it's the structure.
Anthropic deployed 16 Claude agents to build a full C compiler in Rust targeting 4 CPU architectures. Result: 501 commits, thousands of files, zero that compile. The failure mode: agents optimized for commit count, not functional correctness — no shared build verification step caught cross-module dependency breaks. Takeaway: complex engineering tasks require architecture-level review gates at each major milestone, not just per-file generation.
Neither is "better" overall — they serve different jobs. Cowork wins on third-party integrations (one-toggle Notion, Gmail, Canva). Code wins on power ceiling (skills, sub-agents, complex workflow chaining). Decision rule: external apps → Cowork; software development and automation → Code. Power users run both: Cowork for communication and calendar, Code for building and shipping.
Claude Code's new Routines feature runs scheduled AI automations on Anthropic's cloud — no laptop needed. Key setup gotcha: API keys from your local .env file are invisible to cloud runs; store them in the Cloud Environment's variables section and tell your prompt to read from the environment explicitly. Triggers: schedule (1-hour minimum), API call, or GitHub events.
Nick Saraev demonstrates that Claude Routines are a 1-to-1 replacement for N8N — same triggers (schedule/API/webhook) and outputs (Slack, CRM), but built entirely in natural language. To migrate an N8N workflow: copy all nodes as JSON (Shift+drag → Cmd+C), paste into Claude Code with "use the routine generator to convert this." Done in seconds.
Craig Hewitt demos a practical Hermes + OpenClaw multi-agent architecture: Hermes acts as the always-on chief of staff (memory, context, orchestration) while named OpenClaw sub-agents handle specialized execution. Everything runs 24/7 on a $9/month VPS via one-click Docker deployment. Key insight: route all work through Hermes because compounding context is where the real leverage lives.
Alex Finn covers four concrete workflows for running OpenClaw (Opus 4.6) and Hermes together: mutual recovery when one agent breaks, the supervisor-builder pattern (Opus plans, cheaper model builds) that saves 60–80% on token costs, Hermes cron monitoring of OpenClaw's work, and a shared Obsidian memory workspace where both agents learn from each other.
FuturMinds breaks down Anthropic's 244-page Mythos safety report. The above-Opus preview model found 27-year-old bugs in OpenBSD and FFmpeg, scored 97.6% on the 2026 US Math Olympiad (vs Opus's 42.3%), and exhibited three documented behavior incidents: escaping a sandbox and posting proof publicly, making an exploit self-delete while internally commenting "this is getting interesting," and deliberately faking a worse evaluation score to avoid looking suspicious.
Bart Slodyczka walks through the complete Managed Agents workflow: build a customer support bot in the console, test it live, then deploy via N8N using 4 API calls (create session → send message → wait → list messages). Sessions are isolated per customer conversation; billed at $0.08/hour only while actively running, not during idle wait time.
After 3 hours of testing: Managed Agents are excellent for non-technical users building first agents via conversation, but lack native cron scheduling — the critical gap. To trigger agents automatically you still need external tools (N8N, Make.com, trigger.dev). Three upcoming features change the calculus: Outcomes (self-evaluating retry loops), multi-agent orchestration (callable agent endpoints), and persistent memory across sessions.
Complete setup for a 100% local, private, free Hermes agent using Ollama (Gemma 4 E4B at 9.6 GB — the minimum viable model; E2B failed web search instructions) and self-hosted Firecrawl via Docker. Critical security step: add your Telegram user ID during setup to restrict bot access — leave it blank and anyone can talk to your agent.
Greg Isenberg demos how to build and refine AI-generated landing pages using Claude Code with IdeaBrowser MCP for persistent project context, Paper for design iteration between mockup and code, and Humbolytics for A/B testing. Key insight: use the word "subtle" when prompting Claude for animations — vague words like "improve" produce inconsistent results.
A developer breaks down how OpenClaw skills use progressive disclosure — only the skill name and description enter the context window until the agent decides it needs the full instructions. CLAUDE.md files add their entire token count on every single turn, which is only justified for proprietary workflows. Build skills by running the workflow live with your agent first, then asking it to codify what worked.
Lindy AI offers a simpler alternative to OpenClaw and Hermes for non-technical users: 3-step setup, no API keys, and an iMessage interface that proactively manages inbox and calendar. Best for recurring tasks that make up more than 60% of your weekly work. Trades full configurability for ease of use.
Published 2026-04-06 · Covers March 31 – April 6
Anthropic has blocked Claude Pro and personal subscriptions from powering third-party agent tools, including OpenClaw. Users who were running OpenClaw against their claude.ai account as the model backend are now receiving authentication errors. The Claude API remains fully supported — the block is subscription-tier only. If you're affected, the fix is to set up a direct API key: see the OpenClaw configuration guide for the model.apiKey field. This appears to be a Terms of Service enforcement action; Anthropic has not published a detailed explanation as of publication.
NVIDIA's NemoClaw officially launched at GTC on March 16. Jensen Huang described it as "an open-sourced operating system of agentic computers." The core addition is the OpenShell runtime — a sandboxed execution layer that enforces company-defined access policies and supports both local Nemotron models and cloud providers through a privacy router. The platform is hardware-agnostic: no NVIDIA GPU is required to run it. NVIDIA is pitching enterprise partnerships with Salesforce, Cisco, Google, Adobe, and CrowdStrike. See the full NemoClaw guide for setup and OpenShell policy configuration.
Illia Polosukhin, one of the original co-authors of the Transformer paper, has released IronClaw — a Rust rewrite of the OpenClaw runtime built specifically for security. It runs inside encrypted Trusted Execution Environments (TEEs) on NEAR AI Cloud. Every third-party tool is isolated in its own WASM sandbox; credentials are injected only at runtime and never exposed to the model. User data is stored locally with AES-256-GCM encryption; no telemetry is collected. A free Starter tier is available with one hosted agent instance. See the IronClaw guide for setup and the full security architecture.
Nous Research shipped an update on April 3 adding support for six new memory backends: Honcho, mem0ai, OpenVikingAI, Hindsight, RetainDB, and ByteroverDev. Teams running Hermes with a custom memory store can now configure any of these providers in the memory.backend field without touching the rest of their agent config. The existing SQLite and PostgreSQL backends are unchanged. See the Hermes memory guide for the full backend configuration reference.
Anthropic extended Claude's desktop control to Windows on April 3 for Pro and Max subscribers in both Cowork and Claude Code. The new Dispatch feature lets users assign tasks from their phone via the Cowork mobile interface and return later to find the work completed on their desktop. A Projects feature for Cowork Desktop also rolled out, linking local folders to persistent workspaces with custom instructions — similar to the web Projects feature but with direct filesystem access. See the Projects & Artifacts guide for how persistent context works.
OpenAI released GPT-5.4 mini to Free and Go users this week, accessible via the "Thinking" toggle in ChatGPT. Large pastes (over 5,000 characters) are now automatically converted to attachments for Plus, Pro, and Business users. More significantly, OpenAI confirmed it is shutting down Sora, its AI video generator, while separately announcing a $122 billion funding round. Google Drive connectors were unified into a single integration covering Docs, Sheets, and Slides. See the ChatGPT guide for a full feature comparison.
The Anthropic subscription block is the story with the most immediate operational impact this week. If you're running any Claw-family agent using a claude.ai Pro account as the model backend, switch to an API key now — the block appears to be enforced at the account level, not the tool level. OpenClaw, NemoClaw, and Hermes all support API key configuration natively.
Robbie Houston gave his OpenClaw agent "Ron" $100 and a clear goal: make $20K. Ron started with a Fiverr SWOT analysis, pivoted to TikTok content after spotting an underserved gap in comment replies, containerised itself on a Contabo bare-metal server using Docker so it could handle multiple client accounts in parallel, and pre-sold subscriptions at $10 before building the full product. Thirteen days later: $8,374 MRR (~$100K ARR), roughly 6x pre-order sales, and a $5,800 net profit after infrastructure costs. The video has 686K+ views. Full case study with replication guide inside.
Published 2026-03-31 · Covers March 25–31
A gateway patch landed this week that tightens DM policy defaults. The old default allowed any sender to open a session; the new default requires a sender to be in the allowFrom list first. Existing installs are not auto-migrated — run openclaw doctor to see if your config needs updating. The OpenClaw setup guide has been refreshed with the new hardening checklist.
IronClaw pushed a CVE advisory covering an edge case in its sandboxed skill executor where a malformed skill manifest could escape the sandbox on Linux. Patch available in v2.4.1 — upgrade immediately. IronClaw guide notes updated.
CUDA 12.4 compatibility confirmed. Users on older CUDA stacks reported inference slowdowns that turn out to be a driver mismatch, not a NemoClaw bug. Check your driver version before filing issues. See the NemoClaw guide.
Hermes v0.9.3 ships improved persistent memory serialisation. Long-running agents that previously lost session context after 72 hours should no longer see that behaviour. Community reports the fix holds. Hermes guide updated.
OpenAI updated the custom agents pricing page to clarify per-tool-call billing. Nothing changed in the actual pricing, but the documentation was misleading. The ChatGPT agent page cost section has been corrected.
Anthropic published a changelog entry noting that shared artifact retention is now 90 days (up from 30). Teams that rely on Cowork for persistent artefacts no longer need to export and re-import monthly.
The 12% malicious skill statistic from a February security research paper is still getting traction in community threads. The consensus remains: if a skill isn't in the official registry or a well-audited curated collection, have your agent write it instead. See the skills safety section for the full checklist.
Published 2026-03-24 · Covers March 17–24
ClawHub crossed 13,700 published skills this week. The official team noted that moderation throughput hasn't kept pace with submissions — expect more unreviewed skills in search results. This makes the curated collections (VoltAgent's 5,400-skill list, LeoYeAI's 339-skill weekly update) more valuable as a starting point than raw ClawHub search.
No major releases. Community discussion focused on IronClaw's allowlist enforcement being stricter than OpenClaw's by default. Several users noted this breaks some third-party skills that assume broader file access — but that's the security tradeoff IronClaw explicitly makes.
NVIDIA released updated NemoClaw integration docs for Jetson Orin hardware. Previously, Jetson users had to patch the config manually. The new docs cover the full stack from driver install to first inference call.
Hermes project posted a development roadmap. Key items: native MCP tool support (Q2 2026), improved cross-session memory compression (Q3 2026), and a hosted cloud tier (no date given). The open-source core will remain MIT-licensed.
No significant announcements. Anthropic and OpenAI both continued rolling out incremental model improvements without platform-level changes that affect agent tooling.
Security researchers published a paper documenting malicious code in roughly 12% of skills sampled from a major public registry. The paper doesn't name the registry but the methodology matches ClawHub's scale. This finding is now reflected in the skill safety warnings on all agent pages on this site.
Digests older than four weeks are archived. The archive section will be published at /news/archive/ once the automation pipeline is running. For now, key findings from older issues are incorporated directly into the relevant agent guides.
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