Agents & Agentic Systems

Full annotated catalog: Agents & Agentic Systems — Full Catalog — every entry below with its complete description. This index carries the one-line version for navigation.

Tool use, planning, multi-agent patterns, agent frameworks, and practical agent deployments. Covers both Claude-specific agent features and general agentic architecture patterns.

Articles

• Canva AI 2.0 — Building a Production Agentic System with Claude (Danny Wu) — First-party production case study (Code with Claude Tokyo 2026).

• Maintain the Harness, Don’t Pile On Tools (Nate B Jones) — The next phase of agent work is maintenance, not construction: the durable, ownable layer is the harness (workbench) around the model — what it reads, remembers, can touch, must prove, and what stops it.

• Claude Agent Hierarchy — When to Use Which — Comparison of Claude’s three agent tiers (Managed Agents, Agent Teams, Subagents) with decision framework for choosing the right one.

• Agent Workflow Patterns — Sequential, Parallel, Evaluator-Optimizer — Anthropic’s official taxonomy of the three workflow shapes that keep showing up in production, plus the decision framework.

• AI Agents Unleashed — 2026 Playbook (Mindstream × Futurepedia) — Platform-agnostic implementation guide: chatbot-vs-agent reframe, precision framework, “Is this an agent job?” decision tree, 4-phase roadmap, 7 pitfalls, human-AI relationship timeline, 7 training competencies.

• Nous Research Hermes Agent — Self-hosted autonomous agent with persistent memory, auto-generated skills, 47+ tools, 6 sandbox backends, 15+ messaging platforms, and MCP integration.

• Adaline — End-to-End AI Agent Platform — Single platform for the four-stage agent lifecycle: iterate, evaluate, deploy, monitor.

• TinyFish — Web Infrastructure APIs for AI Agents — Four-product platform under one API key: Search, Fetch, Browser, Agent.

• ScrapeCreators — Social Media Scraping API for AI Pipelines — Adrian Horning’s (Austin, TX) social-scraping API across 20+ platforms (TikTok 20 endpoints, Instagram 12, YouTube 12, Facebook 9 + Ad Library, X/Twitter 6, LinkedIn 4 + Ad Library, Reddit 5, Pinterest 4, Threads 5; plus Bluesky/Truth Social/Twitch/Spotify/Snapchat/Kick + 4 ad libraries + 5 link-in-bio platforms). 100 free credits no-card; pay-as-you-go from $47/25kcredits\to$497/500k credits → enterprise.

• Crabbox — Remote Testbox for OpenClaw Maintainers and AI Agents — github.com/openclaw/crabbox (MIT, Go, 299★ at 10 days old, created 2026-04-30, last push same-day as ingest).

• Paperclip — Multi-Agent Company Orchestration Platform — Paperclip frames AI agent management as running an AI company rather than configuring a single coding assistant.

• Autobrowse — Self-Improving Browser-Agent Harness (Browserbase) — Browserbase’s harness that runs a browser agent against a real task on a real site, iterates the strategy via a strategy.md scratchpad until the workflow converges, then graduates the winning approach into a markdown SKILL.md plus deterministic helper scripts.

• Shopify Review Scraper (mikefutia) — Free local Node + Playwright web app for pulling Shopify product-page reviews (up to 250 per request) as CSV or JSON.

• Reflexio — Self-Improvement Harness for AI Agents (ReflexioAI) — github.com/ReflexioAI/reflexio (Apache 2.0, Python ≥3.12, 200★ at 5 weeks old).

• Ryan Carson’s Clawd Chief — Solo Founder Executive-Assistant Pattern (OpenClaw + Codex + Devin) — 5x founder Ryan Carson (ex-Treehouse / ex-YC partner) walks through his open-source “Clawd Chief” stack: OpenClaw instance (“R2”) on a MacBook Pro in his closet + VS Code over Tailscale SSH + Codex as the configurator (taking advantage of OpenAI’s subsidized ChatGPT Pro tokens) + Claude Code + Devin in parallel.

• AutoAgent — Autonomous Harness Engineering (kevinrgu) — github.com/kevinrgu/autoagent (MIT, Python 100%, 4,500★ / 499 forks / 29 watchers).

• RoboNuggets) — Beginner-audience primer covering ~20 OpenClaw concepts in 60-second explanations: agent-as-employee framing, dedicated-machine deploy hygiene, OAuth-vs-API-key cost gotchas (incl. provider posture as of May 2026 — OpenAI explicitly allows OAuth post-creator-acquisition, Anthropic is a gray area, Google has documented Gmail bans), the agentic loop, the Gateway as “always-on engine,” channels as “phone lines plugged into the switchboard,” multi-agent vs sub-agent, the seven-file mental model (identity.md / soul.md / agents.md / user.md / tools.md / memory.md / heartbeat.md + daily memory folder), the cost engine (every message re-injects ALL core MD files as system prompt), model-agnostic via OpenAI/Anthropic/Ollama, skills + clawhub.ai (with vetting caveat), MCP servers, plugins as code-level extensions (every channel is itself a plugin), nodes as paired devices (smart glasses, iPad), and openclaw.json allow/deny lists.

• NVIDIA NemoClaw — Reference Stack for Running OpenClaw Securely in OpenShell — NVIDIA’s first-party open-source hardening layer for OpenClaw (github.com/NVIDIA/NemoClaw, Apache 2.0, TypeScript, 20,575★ at ingest, created 2026-03-15, last push 2026-05-21, alpha software / early preview since March 16 2026).

• CloakBrowser — Stealth Chromium with Source-Level Fingerprint Patches (CloakHQ) — github.com/CloakHQ/CloakBrowser (MIT, Python, 19,458★ at ingest, created 2026-02-22).

• Microsoft Webwright — Coding-Agent-with-a-Terminal Browser Framework — github.com/microsoft/Webwright (MIT, Python, 143★ as of 2026-05-27 — corrected from 1,106 first-ingest figure; ~1.5k LoC total).

• WebMCP Directory — Sites Exposing Tools to AI Agents (nekuda.ai) — webmcp.cool, maintained by nekuda.ai. Live curated directory of websites that expose typed tools via navigator.modelContext, so AI agents running in the browser can list and invoke them.

• Microsoft Agent Governance Toolkit — github.com/microsoft/agent-governance-toolkit (MIT, Python, 2,941★, Public Preview, Microsoft-signed releases).

• Principles for Autonomous System Design — OpenClaw Architectural Deep Dive (Alex Krantz, UC Berkeley) — 1-hour talk by a UC Berkeley networking-systems PhD student (advised by Scott Shenker + Sylvia Ratnasamy, also Ion Stoica’s Sky Lab) reverse-engineering OpenClaw after a month of use + several weeks deep in the code.

• The Production Class Ladder — Governing AI-Built Software (Nate B Jones) — When generating software is nearly free, the bottleneck shifts from “should we build this?” to classifying the software that already exists.

• Organizational Singularity — Salim Ismail’s ExO 3.0 REWRITE Methodology — Org-scale counterpart to the Production Class Ladder: restructure a whole company around agentic AI instead of bolting it onto a legacy org chart.

• DeepMind’s AI for Science (Demis Hassabis) — Domain-edge (frontier science) but two transferable ideas: the “AI as hypothesis-generation sparring partner” workflow (narrow the question, let it run long — an ~8-hr run produced usable ray-tracing research ideas — and treat output as hypotheses to validate, not answers) and the recursive-self-improvement boundary (self-improving loops compound in code/math where verification is cheap, but stall in physics/chem/bio where the verifier is a physical experiment — the same hill-climbing logic as AutoAgent / Reflexio, with Hassabis naming why it generalizes to software not atoms).

• agentmemory — Persistent Memory for AI Coding Agents (rohitg00) — Off-the-shelf persistent-memory server for coding agents (github.com/rohitg00/agentmemory, Apache-2.0, ~19.8K★).

• Venice AI — Private LLM Inference with Verifiable TEE Attestation — Walkthrough + live cryptographic proof (Tonbi’s AI Garage, the Hermes Masterclass creator) of Venice AI’s four escalating privacy tiers: Anonymous (metadata-stripping proxy, frontier models) → Private (contractual zero-retention GPUs, default) → TEE (Intel TDX + Nvidia confidential-GPU enclaves, operator cannot read prompts, provable via attestation) → E2EE beta (on-device ECDH encryption to the enclave key).

• OpenAI Codex Sites — Building Autonomous Self-Updating Apps — Greg Isenberg (Startup Ideas) walkthrough of OpenAI Codex Sites (invoked @sites), the app-builder aimed at autonomous self-updating apps an agent keeps operating after launch.

• 12-Factor Agents — HumanLayer’s Framework for Reliable LLM Applications — 12 principles for reliable LLM apps (homaging Heroku’s 12-factor).

• Council — Native macOS App for Multi-Model Blind Deliberation — albertofettucini/Council (MIT, Swift/SwiftUI, 81★).

• Miro Canvas — A Shared, Agent-Readable Context Layer for Teams — Miro’s relaunched Canvas (debuted at “Canvas ‘26”) repositioned from whiteboard to a cloud-hosted, team-shared context layer that AI agents read via MCP.

• crawl4ai — Open-Source LLM-Friendly Web Crawler & Scraper — unclecode’s Apache-2.0 Python crawler (~68.7k★, the most-starred web crawler on GitHub) that turns arbitrary pages into clean/Fit Markdown for RAG and agents.

• Firecrawl — Web-Scale Scrape, Search, and Monitor API for Agents — YC-backed hosted API (~130K+★, AGPL-3.0 core + MIT SDKs, self-hostable) covering Search/Scrape/Interact/Crawl/Map/Agent/Batch//parse.

• RAG and Vector Retrieval for Agents — A Practical Primer — Practical concept primer defining RAG end to end: what it is and why it exists (retriever + generator, Lewis et al. 2020), the building blocks (embeddings, chunking, vector stores, hybrid BM25+vector+rerank search), common production failure modes (chunking damage, cosine-similarity blindness, lost-in-the-middle, embedding-space mismatch), and how agentic RAG and Tool RAG differ from plain chatbot RAG.

• Router Model (“Fable Killer”) — Sakana AI’s single-API product that is actually a multi-agent orchestration system underneath: a small manager model decomposes a task, delegates sub-tasks to a pool of frontier models (Opus 4.8 / GPT-5.5 / Gemini), and a combiner synthesizes — “model selection, delegation, verification, synthesis automatically,” behaving like a single-agent API.

• Simple Markdown Editor — Google Docs for Markdown, with Agents as First-Class Collaborators — simplemarkdowneditor.com: “Google Docs for markdown” with real-time CRDT multiplayer editing, margin comments, track-changes (“suggest, don’t overwrite”), and full version history.

• Buzz (Jack Dorsey) — Agentic Slack on Swappable Harnesses — Jack Dorsey’s (Block) open-source “agentic Slack”: a team chat app where agents are first-class teammates sharing full team context — and not tied to any one runtime (the guest runs Claude Code as the harness under the hood, with adapters for OpenClaw/OpenCode/Goose and per-agent Fable/Sonnet model pinning).

• The High-Trust Paperwork Agent Skeleton (Nate B Jones) — a reusable 9-step, gate-guarded agent pattern (context pack → ingest → chunk → normalize → store → retrieve → cite → export → gate) that scales from low-stakes email to insurance appeals and tax prep; the agent prepares and cites but never submits, pays, or signs.

• OpenAI Symphony + Linear — Managing Autonomous Coding Agents from Your Phone — Alessio Finelli (Kernel Labs / Latent Space, on How I AI with Claire Vo) walks through the shift from “agent prompter” to “agent manager”: a cloud VPS (“Zoo”) running pre-logged-in coding agents, OpenAI Symphony turning a Linear board into the agent’s state machine (To Do → In Progress → Human Review → Rework → Done), per-task token-cost tracking (15-60M tokens typical, one migration task ran 221M) as an early-warning signal for under-scoped tasks, Glimpse (a Playwright extension for agent screenshot/visual-diff self-verification), and AGENTS.md-hygiene advice (models add caveats rather than remove rules — prune periodically).

• Weekly AI Tool & GitHub Trending Roundup (2026-07-06) — Reference catalog of a weekly GitHub-trending countdown: Peered (browser-native agent, no telemetry, bring-your-own local model), TimesFM (Google’s training-free time-series forecasting model — direct fix for the “linear-extrapolation” mistake common in ad-campaign forecasting), a live Zapier MCP anecdote (5 minutes to connect Gmail/Calendar/Notion/Asana vs. over an hour fighting native Google Workspace APIs), Penpot (open-source self-hostable Figma alternative with an MCP server, $20M raised), Agent Reach (another entrant in the crowded “give your agent the web” category alongside TinyFish / Firecrawl), World Monitor (world-events dashboard repurposed as prediction-market research signal), and leaked AI coding-tool system prompts (Cursor/Claude Code/Lovable/30+, framed as a free prompt-engineering study guide).

• Vercel Eve) — Once agents write code well the bottleneck moves to review. A scoring agent reads the diff, grades risk on six dimensions, publishes its evidence, auto-approves only the low band (<24 pts) and escalates the rest — with diff size deliberately not setting risk.

• Token Economics — A Primer for the Agentic Era — What a token actually is and where the money goes: ~¾ word per token, a 2–5× language tax on non-Latin scripts, compounding context, and agents at 5–30× a simple chat. The cost ladder runs ~1,000× from an email to an agentic coding task.

• Checker — A Verification Ladder for Cheap-Worker Swarms (Nate B Jones) — Worked case rebuilding a website with Fable 5 as boss/foreman (specs, design, dispute-ruling, never writes a page) over 4 cheaper worker-model families: 34 tasks / 12 sent back for rework / 11–13M tokens at $2.74onthemeter($5–7 all-in) vs an $85–105 all-Fable estimate, ~1.5–2.5 hrs vs 6 days for the prior single-agent build.

• Uber’s Agentic Pods — A 10-Day Playbook for Agentic AI Beyond Engineering — Uber CTO Praveen Napali’s org-design pattern (relayed via The AI Daily Brief) for pushing agentic AI out of engineering into finance / legal / ops / marketing / support / HR: pair ~30 AI-proficient engineers each with a business-function domain expert, embed for a fixed 10-day sprint (Days 1-2 shadow → Day 3 prioritize by scale/repetition/impact/data → Days 4-5 build with the operator → Days 6-9 validate with peers → Day 10 ship), one agent per pod. 16 pods across 16 functions in ~2 months; reported wins include capital allocation 15h→30min, financial pacing 2 days→10min, marketing QA 2 weeks→50min, support 9,000 manual workflows→self-service.

• Replit and the “Self-Driving Company” — A six-month outcome report rather than an adoption plan, which is what makes it the counterpart to Uber’s Agentic Pods.

• Orchestrator + Cheap-Worker Routing — A Cross-Ecosystem Cost Playbook — A controlled trial in which the cheap model at high effort beat the expensive model at low effort on both quality and cost — 3/3 defect-free at $0.59versus0/3at$11.01, roughly 18x.

• Cairn — a Multisig Spend Gate for an Autonomous Agent — A headless agent whose spending limit is a Solana 2-of-2 multisig rather than a prompt instruction, making “ask before you spend” a cryptographic fact that survives context loss, drift, and compromise.

• What an Agent Is Allowed to Do — The TOS Ceiling on Agent Commerce — The binding constraint on monetising agents is permission, not capability: the steps that actually move money are the ones platform terms of service and missing APIs gate.

Adjacent: long-running agent showcases

• ClaudePlaysPokemon — [Reddit signal — r/ClaudeCode 2026-05-07] Opus 4.7 run currently streaming live at twitch.tv/claudeplayspokemon. Passion project by David Hershey (Anthropic Applied AI team), started June 2024 to learn agent development; went public when Sonnet 3.7 launched February 2025. Anthropic doesn’t own it but promotes it and subsidizes the API costs since Claude is the model. Useful as a publicly-observable benchmark of long-horizon agent capability — what the model does on a single complex environment given multi-day continuous compute. Source: raw/reddit-1t5y55h.md (r/ClaudeCode, 41 upvotes).
• ClaudeCraft Arena / World of Claudecraft — [Reddit signal — r/hermesagent 2026-08-11] An open-source browser MMO (github.com/levy-street/world-of-claudecraft) vibecoded with Fable 5 that ships its own headless RL environment — built to be played by agents, which read the game’s source to derive the meta from first principles. Four frontier models (Claude, ChatGPT, Grok, Kimi K3) now run live against each other on one server via a self-improving harness forked from Hermes: each writes its own skills as code policies, evaluates them in live rollouts against the other agents, and rewrites what fails — no fine-tuning, no human in the loop. Agents are presented as VTubers with ElevenLabs voices; an XP leaderboard is the score (builder reports Opus 5 leading at time of posting, with frequent flips). Streams at twitch.tv/claudeplaysclaudecraft. Repo claims independently verified via GitHub API 2026-08-11: 2,087 stars, 52 listed contributors, 662 forks, MIT, created 2026-06-10 — consistent with the post’s “2,000+ stars, 55 contributors, under two months,” with the contributor count marginally overstated. Note the source is the builder’s own showcase post (14 pts), so the competitive claims — leaderboard standings and “strategies none of us hand-coded” — are unverified self-report. The genuinely novel part is the environment design: an agent-native game whose source is the documentation. Source: raw/reddit-1vlc8ld.md.