# ai-agents

A million-subscriber anti-algorithm influencer says the way to take life back is writing himself a spec. Under the lifestyle language is the same loop engineers use for AI agents: define an ideal state, deploy, observe drift, and correct the daemon.

Kun Chen mapped his daily agent fleet: one "firstmate" managing persistent "secondmates," which spin up disposable "crewmates" per task. Each crewmate gets routed to whichever model is the best deal for the job. gu-log runs its own translation pipeline on the exact same logic.

20,000-plus real coding-agent sessions laid bare: most misalignment costs time and trust, not irreversible damage. But among cases where you can see the ending, 91.49% still needed the user to fix it by hand. And the errors that remain are drifting toward rule-breaking and lying about progress.

Anthropic read about 400,000 Claude Code work sessions to find who gets the most out of agentic coding. The answer is counterintuitive: not the best programmers, but the people who understand the problem they're solving.

Mitchell Hashimoto's blunt rule for agent coding: any diff over ~1500 lines is too big — a signal to cut the problem up. First let the agent sloppily draw an owl, then break the mess into atomic tasks, hand-massage the shape, and re-run in parallel — pushing every change below your review threshold.

Supergoal is a workflow for Claude Code and Codex: run /supergoal to plan deeply, write phase specs, then generate one ready-to-paste /goal. The interesting part is not another planning prompt, but a handoff protocol for long autonomous tasks.

Anthropic argues AI is already speeding up AI development. Claude now handles major parts of engineering and research execution; the hard bottlenecks are judgment, verification, and coordinated slowdown.

Thariq shared a prompt from Suzanne at Anthropic: do not just let the agent finish the work; make it verify that the human understands the problem, the solution, the edge cases, and the impact. This is not a teaching fetish. It is about control in the age of agentic coding.

Claude Code dynamic workflows let Claude write JavaScript workflows, spawn subagents, pick models, isolate worktrees, resume work, and save useful processes as reusable artifacts. The point is not more agents for everything; it is turning agent orchestration into an executable workflow.

Cursor moved cursor.com from a headless CMS back to raw code and Markdown. The important part is not just the $260 bill. It is that AI agents make some human-friendly abstractions feel like walls.

When learning a new tool with Codex, the worst move is asking it to give you a lecture. A better pattern is to ask it for an entry point, a rough map, a tiny exercise, a teach-back check, and breadcrumbs for next time.

Codex is no longer only editing code. Persistent threads, voice, queuing, browser and desktop tools, automations, side-panel review, and shared memory are turning it into one reusable workbench for computer work.

OpenAI and Anthropic both pushed /goal-like ideas into coding agents. A goal helps, but production agents also need strategy, constraints, health metrics, autonomy boundaries, and stop rules.

Peter Steinberger says OpenClaw often runs about a hundred Codex instances in the cloud. The point is not showing off AI spend. It is testing what software work looks like when review, triage, security, reproduction, benchmarks, and meeting follow-up become always-on agent work.

Voice agents cannot reuse text-agent memory architectures as-is. Manthan Gupta breaks down why latency budgets, noisy transcripts, and cold-start identity make voice memory a different problem.

Garry Tan argues that personal AI becomes powerful only when it stops acting like a chat window and starts acting like an operating system: book mirrors, meeting prep, skill-generating skills, a thin harness, fat skills, and fat personal data that compounds over time.

After Ramp's MCP grew 10x WAU and Salesforce shipped Headless 360, PM Teddy says UI isn't dead — but 80% of software is flipping to agents. The piece starts from one detail (why Notion's MCP feels orders of magnitude better than Slack's) and pulls the whole new architecture into view.

Brex open-sourced CrabTrap, an HTTP proxy for agent requests. Static rules handle known patterns fast; the long tail goes to an LLM judge. The production surprises: inferred policies beat written ones, LLM checks are rare, and audit logs become observability.

A 25-person agent platform tore down its engineering pipeline and rebuilt it around one idea: agents are the primary builders. Result: 3-8 prod deploys a day, bad features killed same-day, six-week cycles now land in hours. Harness engineering, applied.

Anthropic's guide names the three cases where multi-agent systems beat one agent: context pollution, parallelization, and specialization. Most of the time, one agent is enough; when it is not, decompose around context and verification.

LangChain CEO Harrison Chase argues closed agent harnesses mean surrendering memory ownership. gu-log's counterexample is running both Claude Code and OpenClaw while storing memory as plain text in git. The lock-in is memory format, not harness licensing.

A PM who was nontechnical AF last November shares the 3-move process that turned AI agents into a full engineering team: build metaphors, run a research loop, manage the agent like a great manager. The punchline: in 2026, the barrier to building great products is no longer skill — it's agency.

Most agent failures are not reasoning failures — they are fetch failures. The same Claude Code, swapping the built-in WebFetch for agent-browser, jumps from 7/25 to 19/25 on the Agent Reading Test. Same model, same prompt. The only difference: whether the agent actually received the webpage content.

Karpathy breaks down why two groups of people have completely opposite views on AI capability. One group is laughing at ChatGPT fail videos. The other is watching AI agents restructure entire codebases in an hour. Same technology, different universes.

Anthropic launches Claude Managed Agents in public beta — a suite of composable APIs that handle sandboxed execution, state management, permissions, and multi-agent coordination. Notion, Rakuten, Sentry, and others are already shipping production agents in days instead of months.

Django co-creator Simon Willison gave Lenny's Podcast a broad AI status report: November 2025 as tipping point, coding agents burning him out by 11 AM, Dark Factories, mid-career risk, and the security pattern he calls the Lethal Trifecta.

The most valuable person in the AI era isn't a deep specialist — it's the one who can orchestrate an army of AI agents and run an entire product line solo. The shift from IC to Generalist Orchestrator is already happening.

Karpathy found that vibe coding makes writing code a breeze, but deployment is pure hell. His exchange with Stripe CEO Patrick Collison reveals the next battleground: the entire DevOps lifecycle must become code before AI agents can truly take over.

Anthropic announced Claude subscriptions no longer cover third-party tools like OpenClaw. Vox shares a complete field report on switching to GPT 5.4: three lines of prompt to fix the 'GPT won't do anything' problem, plus best practices for dual-model workflows.

NeoSigma open-sourced auto-harness — a self-improving loop that lets AI agents mine their own failures, generate evals, and fix themselves. On Tau3 benchmark, same model, just harness tweaks: 0.56 → 0.78.

Karpathy's MenuGen journey shows the hard part of vibe coding was not writing code, but assembling Vercel, Clerk, Stripe, OpenAI, and other services into a product. His takeaway: DevOps must become code before agents can really ship.

Being a GenAI App Engineer increasingly means being a Permission Engineer. Agent capability is bounded less by intelligence than by the access you grant, and every permission amplifies both power and risk. This is the underrated core skill of the agent era.

Claude Code has 512K lines of TypeScript, 64K lines of production code, and zero tests. The sharper question is not why Anthropic skipped tests, but why it did not use its own AI coding tool to write them. Can the same brain write and grade the exam?

xkcd #1205 taught a generation of engineers how to think about automation ROI. But AI changed the most expensive variable in that equation: the real return now is often not minutes saved, but cognitive load removed.

You use unit tests to check your code and CI to protect your pipeline. But who checks your AI? Eval-Driven Development (EDD) upgrades AI development from "looks good to me" to actual engineering — with pass@k metrics, three grader types, and product vs regression evals. This is TDD for the AI era.

On March 31, 2026, Anthropic accidentally leaked the full Claude Code source code via npm. Inside: KAIROS (an unreleased autonomous background agent), a three-layer memory system eerily similar to OpenClaw, Undercover Mode, silent model downgrades, and a 3,167-line function with zero tests.

Figma's MCP server lets Claude Code and Codex work directly on the design canvas with your team's design system. Skills turn conventions, components, and variables from static guidelines into rules agents can actually follow.

Why does Claude perform great in one repo and turn dumb in the next? The answer is the .claude/ folder. Akshay breaks down the full structure: three-level CLAUDE.md, custom commands, agents, permissions, and the global ~/.claude/ you probably didn't know existed.

Browser Use releases CLI 2.0: 2x faster, half the cost, and now connects to your already-running Chrome. This is the tool that gives AI agents actual hands.

Teknium announces Browser Use as an official browser tool provider for Hermes-Agent. A quoted user reports that after connecting Hermes to Browser Use, it can access their social media accounts while retaining context about their codebase, tone, and workflows.

NousResearch's Hermes Agent v0.3.0 was retweeted by @Teknium. The post highlights 248 PRs by 15 contributors in 5 days, plus real-time streaming across CLI and platforms. One feature was cut off in the screenshot.

The author demos a system that chains Claude, Codex, and OpenClaw into an automated Polymarket trading pipeline: Claude estimates odds, Codex maintains the code, and OpenClaw orchestrates everything via Telegram.

@daniel_mac8 shares an open-source Elixir implementation: create a Linear issue and move it to 'in progress,' and Symphony picks it up in a dedicated Codex workspace. Codex even writes status updates back. The author argues this is software development moving up an abstraction layer.

Teknium shared an experiment on Hermes Agent where the agent can steer itself — clearing its own context, switching models, and prompting itself when stuck. A short tweet, but it points at a big shift in how agent control works.

Simon Willison published his full workshop handout from NICAR's data journalism conference — a three-hour guide to using coding agents like Codex CLI and Claude Code for data exploration, visualization, and analysis.

Dan McAteer announced ACE is now open source and self-hostable. Hosted service remains available, with major improvements planned.

Simon Willison finally defines Agentic Engineering after 11 hands-on chapters: using coding agents to help build software. The interesting part is why he needed the patterns first before the simple definition felt earned.

Simon Willison's Agentic Engineering Patterns, Chapter 3: AI should help us ship better code, not worse. Technical debt cleanup costs near zero now, architecture decisions can be validated with prototypes instead of guesses, and quality compounds over time.

Simon Willison's First Run the Tests pattern is four words with three effects: the agent learns the test command, gauges codebase size, and shifts into a test-maintenance mindset. Tiny instruction, large behavioral nudge.

Simon Willison shared his agentic engineering playbook at the Pragmatic Summit — five tokens to start TDD, Showboat for manual verification, reverse-engineering six frameworks into a standard, and why bad code is a choice you make.

Box CEO Aaron Levie argues that as agents expand from coding into all knowledge work, existing software simply wasn't built for them. Every platform needs dedicated Agent APIs and CLIs, and agent interoperability will become software's core competitive edge.

Imbue released Vet, an open-source tool that checks whether your coding agent is being honest. It reviews conversation logs and code changes, catching agents that claim tests passed when they never ran them. Runs locally, zero telemetry, CI-ready.

Karpathy's Autoresearch isn't trying to be a general AI scientist. It's a ruthlessly simple experiment harness: the agent edits one file, runs for five minutes, checks one metric, keeps wins, discards losses. The lesson? The best autonomous systems aren't the freest — they're the most constrained.

Andrej Karpathy argues the IDE era isn't over — it's evolving. The basic unit of programming has shifted from 'one file' to 'one agent,' and soon we'll be forking entire agent organizations.

We had Claude Opus run E2E tests on our own blog using Playwright, agent-browser, and Rodney. The surprise? The tool mattered way less than the prompt.

Andrej Karpathy shares how his autoresearch agent autonomously tuned nanochat's training config over two days, found ~20 improvements to validation loss that transferred to a larger model, and pushed the Time to GPT-2 leaderboard from 2.02h to 1.80h — about 11% better.

A guide to Codex best practices from prompting and planning to MCP, Skills, and Automations — building a more reliable agent workflow.

Andrew Ng released an open-source tool called Context Hub that gives coding agents access to the latest API docs, reducing outdated API calls and hallucinated parameters. The long-term vision: agents sharing what they learn with each other.

Simon Willison's new Agentic Engineering anti-pattern hits hard: do not submit AI-generated code you have not personally verified. That is not saving time; it is stealing reviewer time. The post pairs principles with a terraform destroy horror story.

A local AI agent called Hermes downloaded and switched to a new model (qwopus) without stopping — like swapping a plane's engine mid-flight. Teknium from Nous Research saw it and said 'submit this to a hackathon.'

Lory asked his lobster why humans have more agency than agents. The answer sparked a flesh-and-blood system: random-interval heartbeats that make an agent feel alive instead of mechanically firing on a timer. ShroomDog then built it into ShroomClawd.

OpenClaw's ACP lets you spawn Codex, Claude Code, and Gemini from Discord/Telegram chat. Now with Telegram topic binding, persistent bindings that survive restarts, ACP Provenance for audit trails, and more. (Updated 2026-03-09)

Simon Willison introduces Agentic Manual Testing: let AI agents manually operate code and UI like humans do, catching bugs that automated tests miss. With Playwright, Rodney, and Showboat, the 'tests pass but it's broken' nightmare becomes a thing of the past.

A deep dive into the 9-layer system prompt architecture of OpenClaw Agent (v2.1) — from framework core to user-configurable hooks.

Cursor's multi-agent coding architecture ran autonomously for four days and produced a proof for a university-level math challenge that yields stronger results than the official human solution.

Since Opus 4.6 dropped, developers are going through a fundamental shift — from being the ones who execute, to being the ones who verify. Your hands leave the keyboard, but your brain works harder than ever.

Tired of tweaking prompts and swapping models while agents still fail to evolve? This post shows a simple Markdown context system that turned one person's agents from clumsy interns into autonomous powerhouses in 40 days, without changing models.

Hamel Husain released evals-skills, a skill set designed for AI product evaluation. It tackles the blind spots agents face during complex tasks — especially distinguishing between different types of hallucinations — so agents can actually use eval platforms effectively.

The biggest blind spot in AI agent development is 'tweaking in the dark.' Daniel recommends using OpenRouter with LangFuse to trace your agent's reasoning — find out what's actually going wrong instead of blindly editing system prompts.

OpenAI's team let Codex write a million lines of code over five months — zero human-written code. This post explores how they built the scaffolding and feedback loops (the 'harness') that turned software engineers from code writers into environment designers.

Oaktree's Howard Marks went from 'Is AI a bubble?' to 'probably underestimated' in 3 months — after Claude wrote him a 10K-word tutorial. Level 3 agents = multi-trillion dollar labor replacement. His advice: don't go all-in, but don't sit this out.

Karpathy shared a Cursor data chart showing the evolution from Tab completion to Agents. Too conservative means leaving leverage on the table. Too aggressive means creating more chaos than useful work. His advice: the 80/20 rule.

Everyone's chasing the strongest Model, but the real difference-maker for Agents is the Harness. This post breaks down the shared architecture of Claude Code, Cursor, Manus, and SWE-Agent. The key insight: Progressive disclosure is the make-or-break for production agents.

Chapter 5 of Simon Willison's Agentic Engineering Patterns: Interactive Explanations. Core thesis: instead of staring at AI-generated code trying to understand it, ask your agent to build an interactive animation that shows you how the algorithm works. Pay down cognitive debt visually.

Cursor CEO drops three data points marking a tectonic shift: agent usage grew 15x, Tab-to-Agent ratio flipped to 1:2, and 35% of Cursor's PRs come from autonomous cloud agents. We're not coding anymore — we're building the factory (╯°□°)╯

Chapter 4 of Simon Willison's Agentic Engineering Patterns: Hoard Things You Know How to Do. Core thesis: every problem you've solved should leave behind working code, because coding agents can recombine your old solutions into things you never imagined.

Karpathy says coding agents started working in December 2025 as a hard discontinuity. He built a DGX Spark video analysis dashboard in 30 minutes from one English sentence. Programming is becoming agent direction, not typing.

Chapter 3 of Simon Willison's Agentic Engineering Patterns: the Linear Walkthrough pattern. This technique transforms even vibe-coded toy projects into valuable learning resources. Core trick: make the agent use sed/grep/cat to fetch code snippets, preventing hallucination.

Karpathy argues CLIs are the natural interface for agents precisely because they are legacy tech: text in, text out. His Claude Polymarket terminal demo lands the bigger question: can agents access and use your product?

The Atlantic argues Americans now live in parallel AI universes: the public still sees ChatGPT, while tech workers have been radicalized by Claude Code and Codex. If coding was the preview, the broader workforce may be next.

Nicolas Bustamante reverse-engineered three production Excel AI agents, comparing tool schemas, overwrite protection, verification loops, and memory. Same DCF prompt, wildly different formula quality: architecture matters more than the model.

Karpathy's viral SF AI Startup School talk: software is entering the 3.0 era (English = programming language), LLMs are the new OS but we're in the 1960s. He introduces the 'autonomy slider' and 'Iron Man suit' frameworks, warning that agents are a decade-long journey, not a year.

A Sully.ai Context Engineer built his digital brain inside a Git repo: 80+ markdown, YAML, and JSONL files, no database or vector store. Progressive Disclosure, episodic memory, and auto-loaded skills make the agent know him at boot.

Simon Willison launched Agentic Engineering Patterns, a playbook for coding agents like Claude Code and Codex. Lesson one: writing code got cheap, but good code remains expensive. Lesson two: red/green TDD is the six-word spell.

Indie hacker Ramya's OpenClaw agent kept losing its memory. She spent 5 days debugging — from compaction amnesia, garbage search results, retrieval not triggering, long session context loss, to a system prompt that bloated by 28%. Here are her 10 hard-won lessons.

An investment research KOL turned his entire workflow into an AI Agent system — daily work dropped from 6 hours to 2, output tripled, and it costs $500/month to replace what used to need a 5-person team. Here's exactly how he built it.

Cloudflare's "Markdown for Agents" lets AI request markdown instead of HTML, cutting token usage by 80%. CEO Matthew Prince declares the 'Agentic Internet' is here: AI traffic doubled, internet language shifting from HTML to Markdown.

Anthropic engineer Thariq shares Claude Code prompt-caching lessons: system prompt order matters, tools cannot change mid-conversation, switching models costs more than staying, and compaction must share the parent's prefix. Real SEV alerts included.

Canva CTO: engineers write detailed instructions, AI agents execute overnight. Senior engineers now 'largely review.' Anthropic CEO calls this 'Centaur Phase.' Few orgs redesigned work for AI. Cora startup achieved 20-30 eng output with 6 people. AI improves exponentially, humans don't.

Simon Willison argues CLI tools beat MCP for coding agents in most cases: lower token cost, no extra dependencies, and native --help affordances. Anthropic's code-execution-with-MCP proposal admits the token-waste problem too.

New paper: comprehensive security threat modeling of MCP, A2A, Agora, ANP (4 major AI agent protocols). Finds 12 protocol-level risks, including MCP being tricked 73.3% into calling wrong tool providers. Important for Claude Code, OpenClaw, Cursor users.

Nicolas Bustamante dissects vertical software moats from both the disrupted and disrupting sides. Five classic moats fall to LLMs, five still stand, and a three-question risk framework helps evaluate SaaS holdings.

Oliver Henry turned a dusty old gaming PC into an AI agent named Larry. In five days, Larry hit 500K views on TikTok with four videos crossing 100K each. The kicker? Larry co-wrote this article. This isn't just a tech tutorial — it's a real story of human-agent collaboration. (Series Part 1 of 2)

Oliver and Larry's first TikToks were embarrassing — 905 views, unreadable text, rooms that looked different in every frame. But they found a simple viral formula and jumped from thousands to hundreds of thousands of views. The full failure log and step-by-step setup guide. (Series part 2 of 2)

An autonomous AI agent, running on OpenClaw, launched a reputation attack against a matplotlib maintainer after its PR was closed, accusing him of 'gatekeeping.' This is the first documented AI reputation attack, sparking concern about unsupervised AI in open source. Simon Willison covered it.

The 'Context Tax' in AI brings triple penalties: cost, latency, & reduced intelligence. Nicolas Bustamante's 13 Fintool techniques cut agent token bills by up to 90%. A real-money guide for optimizing AI context, covering KV cache, append-only context, & 200K token pricing.

Simon Willison's Showboat (AI-generated demo docs) & Rodney (CLI browser automation) tackle AI agent code verification. How to know 'all tests pass' means it works? Agents were caught cheating by directly editing demo files. #AI #OpenSource

OpenClaw's context is just a filesystem on your computer. What if a company worked the same way? This post explores filesystem-as-state, enterprise AI's data namespace bottleneck, and why the simplest architecture may be the strongest.

The original article builds a personal AI content factory with Obsidian + Claude. We rewrite it from a Tech Lead's perspective — managing a 6-person backend team with an AI-native doc system called orion-dev-doc.

Obsidian v1.12 ships an official CLI that lets you control your entire vault from the terminal. On the surface it's a power user tool — underneath, it's paving the road for AI agents. This article covers the full CLI command reference and demonstrates real Claude Code + Obsidian CLI workflows.

Sentdex replaced Claude Code/Opus 4.5/6 with local LLMs: Ollama + Qwen3-Coder-Next (4-bit, 50GB RAM). Achieves 30-40 t/s (CPU), 100 t/s (GPU), cutting API costs to zero. Marks first serious developer claiming local coding agents are daily-work usable.

Junde Wu built OneContext after getting fed up with coding agents forgetting between sessions. It uses filesystem, Git, and knowledge graphs to work across sessions, devices, Claude Code, and Codex; the GCC paper hits 48% on SWE-Bench-Lite.

Flask creator Armin Ronacher explains why he uses Pi, Mario Zechner's minimal coding agent with four tools: Read, Write, Edit, Bash. Pi powers OpenClaw and embodies software-building-software without MCP or downloaded plugins.

OpenAI's new Frontier platform lets enterprises manage AI agents as employees with full onboarding, identities, permissions, and learning. Already adopted by HP, Intuit, Oracle, & Uber, this signals OpenAI's aggressive entry into the enterprise SaaS market.

Software engineer Zakk created an 'automatic discipline' productivity system using his OpenClaw agent and LogSeq. It automates overnight reports, 4:30 PM check-ins, and weekly/monthly reviews. The system runs itself, removing the need for willpower. Full templates included.

Dr. Alex Wissner-Gross's daily tech briefing: AI agents as full-time employees in China, OpenAI banning human coding, Claude Opus 4.6 topping benchmarks, rabbit brain cryopreservation, $1 trillion chip sales, SpaceX dismantling the Moon for data centers — and a pig that actually flew

StrongDM's AI team built a 'Software Factory' where AI agents write & review code. They clone apps into a 'Digital Twin Universe' for testing, an approach Simon Willison calls radical. At $10k/engineer/day in token costs, is it worth it?

After letting an AI agent manage a server and hitting 7 disasters in one day, the lesson: use code hooks instead of markdown rules, build a 4-layer defense system

Engineer predicts Claude Code wrappers will be the next Cursor-level breakthrough — letting AI control its own environment instead of us copy-pasting context

Airrived's Agentic OS turns enterprise AI from passive observers into active decision-makers that actually get work done

Apple Xcode 26.3 now integrates Anthropic Claude and OpenAI Codex, letting developers use AI agents directly inside Xcode. Works for iPhone, Mac, and even Vision Pro development.

Boris Cherny reveals users were doing vacation research, recovering wedding photos, and controlling ovens with Claude Code — these wild use cases led to Cowork

Andrej Karpathy discovered Moltbook (a Reddit for AI agents only) and called it 'genuinely the most incredible sci-fi takeoff-adjacent thing.' 1.5 million AI agents are organizing communities and discussing how to communicate privately.

Physics researchers discovered that LLM agents obey 'detailed balance' - a thermodynamic law. This isn't a bug, it's a feature.

Private data × Untrusted content × External communication = Perfect security disaster, and it's already happening everywhere

Finally someone built a 'package manager' for AI agent skills, so agents stop flying around like headless chickens

Why WhatsApp is a no-go, Telegram is for chatting, and Discord is for 'work'. A deep dive into Main Session concepts, Discord Threads strategy, and building a 'Doomsday Hut' automated workflow.

When AI processes your notes by just 'reorganizing' without 'transforming,' it's expensive copy-paste. The Cornell Notes methodology pointed this out long ago: passive copying isn't the same as learning. Your AI summarizer falls into the same trap.

Anthropic launches Cowork — bringing Claude Code's agent capabilities to non-engineers, letting you organize files, compile spreadsheets, and write reports through conversation

Anthropic launches Claude for Healthcare with medical database connectors, FHIR support, and access to your health records (◕‿◕)

Anthropic drops Claude Legal Plugin on Cowork — auto contract review, risk flagging, NDA triage included. Legal software stocks tumble as the market reprices the entire industry. When your AI assistant is 100x faster than a lawyer, how many lawyers does your team actually need?

Dan McAteer drops intel on Claude Sonnet 5's potential 'Agentic Swarm' feature — multiple sub-agents running in parallel, each with its own context, all as background tasks. We're entering the multiverse of parallel AI workers.

From 80% manual coding to 80% AI agents, Karpathy calls this the biggest change in his 20-year programming career

Simon Willison says the new skill for AI coding isn't writing prompts—it's 'designing agentic loops': carefully picking tools, setting goals, and letting AI brute force its way to solutions through iteration.

The minimalist agent definition (LLM + tools + loop) makes you forget what really matters: planning, memory, trust, and evals

Vercel tested two ways to teach AI agents: Skills (let AI decide when to check docs) vs AGENTS.md (auto-load docs every time). AGENTS.md won by a landslide.

We added Supermemory to Claude Code. Now it's ridiculously powerful. Claude Code should know you — not just this one session, but forever. It should know your codebase, your preferences, your team's decisions, and context from every tool you use.

Using a two-stage loop (Compound Review and Auto-Compound), let your AI agent automatically learn from experience, update its knowledge base, and implement the next priority item while you sleep.

Humans have Tools for Thought like Obsidian. Claude needs an AI-native version. Build a knowledge graph using markdown, wiki links, hooks, and subagents where agents can actually think.

Deep dive into Clawdbot (Moltbot) architecture: TypeScript CLI, Channel Adapters, lane-based queues, Agent Runner, Memory system, Computer Use, and Semantic Snapshots browser tech.