Claude Code

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

Claude Code AI

I got tired of Claude forgetting everything between sessions so I built an autonomous memory system based on mempalace

I use Claude Code daily. Every new session starts from zero. You re-explain your stack, your projects, who you are. Gets old. CLAUDE.md helps but it's static. So I built something on top of https://github.com/milla-jovovich/mempalace. Fair warning: I'm a DevOps engineer. The code is vibecoded with Claude. It works, it's running in prod, but don't expect clean architecture. The idea: A bootstrap.md gets injected once per session via a Claude Code UserPromptSubmit hook — not every message, just the first one. Session IDs tracked in ~/.mempalace/sessions_seen/ so the 7k chars only land once. The bootstrap is generated by Go workers running as K3s CronJobs: - consolidator — clusters drawers into summaries - decay — scores memories by recency/access (heat map) - kg-populator — extracts structured facts into a SQLite knowledge graph - contradiction-detector, entity-normalizer, tunnel-discovery, diary-compactor — maintenance stuff build_bootstrap.py stitches it all into the injected file: KG facts about me and my projects, warmest recent memories, last diary entries. Bonus: fixed a stale HNSW index bug that crashes vector search when mempalace mine runs while the MCP server is live. PR open upstream: https://github.com/milla-jovovich/mempalace/pull/625. Does it work? Yeah. New session, Claude already knows my stack, my projects, what I did recently. No re-explaining. submitted by /u/CamilleAuLit [link] [comments]

Built a Claude Code orchestration tool and hit a brutal race condition during stress testing — 350+ sessions in 15 minutes. Full postmortem and what I fixed.

I've been building a layer that sits above Claude Code and drives it through complex multi-step project tasks automatically. The idea is simple: give it a big messy problem, it breaks it down and runs Claude Code through each piece systematically. Two weeks ago I was testing the session management logic — specifically how it handles spawning multiple Claude Code sessions in parallel under heavy load. Here's where it went wrong. In about 15 minutes, 350+ Claude Code sessions were running simultaneously. I caught it immediately and shut it down. The actual fix was simple — add a lock so only one thread can make the spawn decision at a time, plus a hard limit on total sessions running at once. Took two hours to implement. If you're building anything that runs multiple Claude Code sessions programmatically — don't learn this the hard way like I did. Lock your spawning logic, cap your sessions, and always test with a safe dry-run mode before you scale. Has anyone else built multi-session Claude Code tooling? What safeguards did you build in to keep it under control? submitted by /u/Jumpy-Ratio-1145 [link] [comments]

How to get Claude to run more autonomously

Hi! Can someone tell me how to get Claude to work more autonomously on a large task? A bit of context: I have a .NET project, it contains unit test coverage, integration tests and API tests. Recently we decided to become more strict on code style and warnings. The application has large request and response models for an external API. Currently, that model is camelCase not PascalCase. Also a lot of properties are nullable, but not explicitly. 3k warnings currently. Super tedious for a human to do, perfect task for Claude, I figured. What I run into: Claude seems to be overwhelmed by the amount of issues. It tries to tackle the problems with compound commands that do grepping and it tries to write python scripts. Both of them require user permission, which happens literally 100s of times. I would just like to run the prompt, maybe even in a git-worktree and continue my work and review once its finished. Each fix introduces more new warnings (makes sense). Instead fixing the issues in 1 file and then the new subsequent warnings, it fixes all original warnings and just adds the new warnings to an ignore list. What can I do different? submitted by /u/PrydwenParkingOnly [link] [comments]

Claude via AWS or Azure = Always the same model?

As you might know I can also consume Claude models via the big cloud providers and plug them into Claude Code or another coding assistant of my choice. In this case, will I be safe from model degradation or availability issues? The Claude inference is under full control of the cloud providers so I doubt Anthropic will be tampering with the inference parameters on a daily basis there submitted by /u/PM-ME-CRYPTO-ASSETS [link] [comments]

Tampermonkey transcript code

Whats up. Just dropping this in here. Use this to get named transcripts from claude chats in Tampermonkey on firefox. // ==UserScript== // u/nameClaude Chat Transcript Downloader v3 // u/namespacehttp://tampermonkey.net/ // u/version3.0 // u/description Download current Claude chat as a formatted transcript // u/matchhttps://claude.ai/* // u/grantnone // ==/UserScript== (function () { 'use strict'; function addButton() { if (document.getElementById('transcript-dl-btn')) return; const btn = document.createElement('button'); btn.id = 'transcript-dl-btn'; btn.textContent = 'Download Transcript'; btn.style.cssText = ` position: fixed; bottom: 80px; right: 20px; z-index: 9999; padding: 8px 14px; background: #1a1a1a; color: #fff; border: none; border-radius: 8px; font-size: 13px; cursor: pointer; opacity: 0.85; `; btn.addEventListener('click', downloadTranscript); document.body.appendChild(btn); } function extractText(el) { const tags = el.querySelectorAll('p, li, h1, h2, h3, h4, pre code, td'); if (tags.length) { return Array.from(tags).map(n => n.innerText.trim()).filter(Boolean).join('\n'); } return el.innerText.trim(); } function downloadTranscript() { const lines = []; // Collect all user message bubble containers const userBubbles = new Set(); document.querySelectorAll('[data-testid="user-message"]').forEach(el => { // Walk up to the bg-bg-300 bubble let node = el; while (node && !node.className?.includes?.('bg-bg-300')) { node = node.parentElement; } if (node) userBubbles.add(node.parentElement); // the flex-col wrapper }); // Get the main chat container — find common ancestor of all user messages const allUserMsgs = document.querySelectorAll('[data-testid="user-message"]'); if (!allUserMsgs.length) { alert('No messages found. Make sure you are on a chat page.'); return; } // Walk up from first user message to find the chat scroll container let container = allUserMsgs[0].parentElement; for (let i = 0; i 2) break; container = container.parentElement; } // Now iterate direct children of the container // Each child is either a user turn (has .bg-bg-300 descendant) or a Claude turn const turns = Array.from(container.children); turns.forEach(turn => { const userMsg = turn.querySelector('[data-testid="user-message"]'); if (userMsg) { const text = extractText(userMsg); if (text) { lines.push('─────────────────────────'); lines.push('[YOU]'); lines.push('─────────────────────────'); lines.push(text); lines.push(''); } } else { const text = extractText(turn); if (text && text.length > 10) { lines.push('═════════════════════════'); lines.push('[CLAUDE]'); lines.push('═════════════════════════'); lines.push(text); lines.push(''); } } }); if (!lines.length) { alert('Could not extract messages.'); return; } const timestamp = new Date().toISOString().replace(/[:.]/g, '-').slice(0, 19); const blob = new Blob([lines.join('\n')], { type: 'text/plain' }); const a = document.createElement('a'); a.href = URL.createObjectURL(blob); a.download = `claude-transcript-${timestamp}.txt`; a.click(); URL.revokeObjectURL(a.href); } window.addEventListener('load', addButton); new MutationObserver(addButton).observe(document.body, { childList: true, subtree: true }); })(); submitted by /u/Whole_Win5530 [link] [comments]

Agent Architecture Designer v32.16 - a visual encyclopedia for Claude Code multi-agent systems (35 agents, 42 presets, zero deps)

TL;DR: I built an educational tool for designing and understanding Claude Code multi-agent systems. Single HTML file, zero dependencies, 35 agents, 42 presets, full encyclopedia for each. I'm experimenting with inline infographics for agent entries and I'd love to know if English-speaking users want them too. Live demo: https://thejacksoncode.github.io/Agent-Architecture/ Repo: https://github.com/TheJacksonCode/Agent-Architecture What it is Agent Architecture Designer is primarily an educational and developmental tool, not a production orchestrator. It's a place where you can slow down and study multi-agent systems the way you'd study a complex machine: one moving part at a time. After using it, you should be able to understand: What every single agent actually does - its role, inputs, outputs, anti-patterns, and failure modes How agents talk to each other - who hands off to whom, which phases they live in Why a given preset looks the way it does - why it has 7 agents and not 12, why a Five Minds debate sits in the middle, why the HITL gate lives where it lives The cost and context budget of a multi-agent system before you spend a single token You can use it as a visual designer (drag agents onto a canvas, connect them, generate a system prompt for Claude Code), but the real value is the Encyclopedia behind every agent and every preset. Each entry is structured like a short lesson: who it is, how it works in phases, what it does, what it does NOT do, anti-patterns, real-world examples, when it fails, fun facts. What's in v32.16 35 agents + 42 presets - each with a 10-section bento encyclopedia entry Five Minds Protocol - structured adversarial debate (4 domain experts + Devil's Advocate) producing a Gold Solution HITL decision gates - 3 human checkpoints between phases with countdown timers Cost Command Center - per-agent / per-phase cost estimates, p50-p90 range, context window tracking, what-if sliders Custom Agent Creator Pro - 7-feature builder with a 159-icon library and live quality scoring Live simulation - agents exchange animated speech bubbles and data packets along their connections Zero dependencies - one HTML file, works offline, no npm, no CDN, no build step Bilingual PL/EN - full interface toggle Honest disclaimer - Polish version is richer I'm Polish, and the research base I had during development was mostly in Polish. That means: All 35 agent + 42 preset encyclopedia entries exist in both languages (v32.16 closed the last gap, thanks to 18 parallel translation agents) But the Polish version ships with inline infographics for a few selected agents, and the English version does not have them yet Please don't take this personally if you're an English-speaking user. The English version has full text parity, you're not missing any information, just the visual infographics. Which brings me to the actual reason for this post. The feedback I'm looking for In v32.16 I started experimenting with inline infographics inside the encyclopedia entries. Right now they only exist (in Polish) for four researcher agents: Researcher Reddit Researcher X (Twitter) Researcher GitHub Researcher Forums Before I invest the time to build infographics for the remaining 31 agents + 42 presets (and port them to English), I want to know if this is actually valuable to you or just visual noise. Specifically: If you open the encyclopedia for one of those 4 researcher agents, does the infographic help you understand what the agent does, or is the text alone enough? Would you want inline infographics in the English version too, if I built them? Is there a specific agent or preset where you got lost reading the text and a visual would have helped? Is there an agent role or pattern missing from the 35/42 catalog that you wish existed? You can switch to Polish via the language toggle in the top bar and then click Researcher Reddit / X / GitHub / Forums to see what the infographics look like. The rest of the entry is in Polish but the infographic itself is largely visual so you'll get the idea. Work in progress This is very much not the final version. I'm shipping iteratively and v32.16 is one step in a longer roadmap. If you find bugs, have feature ideas, or think a specific agent entry is weak, please open a GitHub issue or drop a comment here. Short comments and screenshots are very welcome. submitted by /u/ConceptParticular565 [link] [comments]

Mempalace , Obsidian Vault and other Memory Tools; which is actually better to use?

I have seen these two options (among others) hyped for using lower tokens and being flvery efficient and effective for new claude code sessions to have memories. But I’m confused on which to actually go for. Do they all serve the same purpose or do they serve different purposes and I can use both these tools for memory systems. I ask as I have noticed some good unique usecases for both but at the same time I feel they are both just memory systems and ultimately serve the same purpose. Let me know your thoughts if you are aware and have used Mempalace and Obsidian vault. submitted by /u/Sensitive_Judge_5502 [link] [comments]

AMD AI directors analysis confirms lobotomization of Claude

Stella Laurenzo, AMD’s director of AI, filed a detailed GitHub issue on April 2 documenting that Claude Code reads code three times less before editing it, rewrites entire files twice as often, and abandons tasks mid-way at rates that were previously zero. Her analysis of nearly 7,000 sessions puts precise numbers on how Anthropic’s coding tool has degraded since early March. PERFORMANCE DECLINE: AMD’s AI director documented that Claude Code reads code three times less, rewrites files twice as often, and abandons tasks at previously unseen rates. ROOT CAUSE: Anthropic’s March 2026 thinking content redaction reduced visible reasoning from 100% to zero over just eight days, triggering the behavioral collapse. TEAM CHURNED: AMD’s engineering team has already switched to a competing AI coding provider, citing Claude Code’s inability to handle complex tasks reliably. PROPOSED FIXES: Laurenzo called on Anthropic to restore thinking visibility and introduce a premium tier for guaranteed deep reasoning. BROADER PATTERN: Anthropic shipped 14 releases alongside 5 outages in March 2026, suggesting quality assurance has not kept pace with rapid growth. https://github.com/anthropics/claude-code/issues/42796 submitted by /u/Aggressive_Bath55 [link] [comments]

Best way to build an email assistant?

Hey! Now that the agent space is changing almost daily, most tutorials from 3 months ago aren't using the newest or best setups. So this question is to anyone who has built a system for managing emails automatically with the newest tools. What is your setup and would it be capable of what I want? Is Claude managed agents or claude code a good idea or would you focus on OpenClaw? Ideally the assistant would: - Sort through incoming and old emails into gmail labels/categories, e.g. on an hourly basis - Move the emails into the folders (including one for trashing later) - Ping me of any new important emails (only a few specific labels), so that I can choose to reply if needed. Ideally I would prefer the notification in channels I already use on my phone, e.g. telegram that has worked fine with openclaw. - Draft & send the reply when asked - Every morning go through my email and suggest emails I need to pay attention to, follow up on or respond to. I have a claude subscription and also an option to use openclaw (but with another model as sonnet & haiku started getting too expensive). I also use Composio for other stuff, so that could be used. I would prefer to use Claude models cause they have been the best in mimicing my writing style and if I can have this running with my Claude subscription, my wallet would be a lot happier. That's why I'm considering changing my current openclaw setup. Thanks for any input! submitted by /u/mana-aatti [link] [comments]

I built a notification tool for Claude Code, hit 374 downloads, then found out notifications were broken the whole time — v1.1.0 is out

Built with Claude Code, specifically for Claude Code users. Free, open source, MIT. What it does u/daik0z/claude-notify adds a Stop hook to ~/.claude/settings.json. When Claude Code finishes a task, you get a push notification — desktop, mobile via ntfy, or any webhook. The body summarizes what happened: "3 files edited · 2 commands ". npm install -g u/daik0z/claude-notify claude-notify setup What I learned from 374 downloads I sat down to stress-test it and found that every user was getting "Task complete." in every notification — never the actual summary. The transcript parser was looking for entry.toolName at the top level of the JSONL. Claude Code's actu al format nests tool calls inside message.content[] where type === "tool_use". Never matched, always fell back to the default. Fixed in v1.1.0. Also found: HTTP errors from ntfy/webhooks were silent (test said ✓ even on 401), and a webhook template bug that could double-expand variables. New in v1.1.0 — worktree IP isolation If you run parallel Claude Code sessions, each one spins up a dev server and they collide on ports. claude-notify ip prints a stable loopback IP derived from the current git worktree path — same worktree always gets the same IP: vite --host $(claude-notify ip) eval $(claude-notify ip --export) Works out of the box on Linux. One-time setup on macOS: claude-notify ip --setup. Repo: https://github.com/ddaikodaiko/claude-notify submitted by /u/Aromatic_Jaguar9574 [link] [comments]

Anthropic's New Claude "Mythos Preview" Can Find and Exploit Zero-Day Vulnerabilities in Every Major OS and Browser — Autonomously

Anthropic just published a technical deep-dive on Claude Mythos Preview's cybersecurity capabilities, and it's a significant escalation from anything we've seen from a language model before. What It Can Do: Autonomously finds and exploits zero-day vulnerabilities in every major OS and web browser — with no human intervention after an initial prompt Identified a 27-year-old OpenBSD bug and a 16-year-old FFmpeg vulnerability that had survived years of fuzzing and manual review Wrote a complete remote code execution exploit for FreeBSD — chaining it across 6 sequential RPC requests to fit within size constraints — fully on its own Achieved full control flow hijack on 10 separate, fully-patched targets in their internal benchmark (previous Claude models hit 0-1 at that severity tier) Chained 3-4 separate Linux kernel vulnerabilities together to escalate to root, autonomously The Numbers That Stand Out: Opus 4.6 turned a Firefox JS engine vulnerability into working exploits 2 out of hundreds of tries. Mythos Preview: 181 times Finding the OpenBSD bug across 1,000 scaffold runs cost under $20,000 total The full FreeBSD exploit (discovery + exploitation) cost under $1,000 and took half a day Why This Matters: Anthropic is explicitly saying this is a watershed moment. N-day exploit development — turning a known CVE into a working exploit — has historically taken skilled researchers days to weeks. Mythos Preview does it autonomously from just a CVE identifier and a git commit. They're not releasing this publicly. Instead they've launched "Project Glasswing" — a limited release to critical infrastructure partners and open source developers to patch the most important systems before similar capabilities become broadly available. The post ends with a stark warning: defense-in-depth mitigations that rely on friction rather than hard barriers may now be significantly weaker against model-assisted attackers. Link to full technical post: https://red.anthropic.com submitted by /u/goyashy [link] [comments]

6 Months Using AI for Actual Work: What's Incredible, What's Overhyped, and What's Quietly Dangerous

Six months ago I committed to using AI tools for everything I possibly could in my work. Every day, every task, every workflow. Here's the honest report as of April 2026. What's Genuinely Incredible First drafts of anything — AI eliminated the blank-page problem entirely. I don't dread starting anymore. Research synthesis — Feeding 10 articles into Claude Opus 4.6 and asking "what's the common thread?" gets me a better synthesis in 2 minutes than I could produce in an hour. Code for non-coders — I've built automation scripts, web scrapers, and a custom dashboard without knowing how to code. Cursor (powered by Claude) changed what "non-technical" means. The tool has 2M+ users now for good reason. Getting unstuck — Talking through a problem with an AI that can actually push back is underrated. Not therapy, but something. Learning new topics fast — "Teach me [topic] like I'm smart but completely new to this. What are the most common misconceptions?" is my go-to for rapid learning. What's Massively Overhyped "AI will do it for you" — Everything still requires your judgment and context. The AI drafts. You think. AI SEO content — The "publish 100 AI articles and watch traffic pour in" strategy is even more dead in 2026 than it was in 2024. Google has gotten much better at identifying low-value AI content. AI chatbots for customer service — Unless you invest heavily in training and iteration, they frustrate users more than they help. "Set it and forget it" automation — AI workflows break. They require monitoring. Fully autonomous workflows exist only in narrow, controlled cases. Chasing the newest model — New model releases happen constantly now. I've learned to stay on a model that works for my tasks rather than jumping to every new release. What's Quietly Dangerous (Nobody Talks About This) Skill atrophy — My first-draft writing has gotten worse. I outsourced that skill and I'm losing the muscle. I now intentionally write without AI some days. Confidence without competence — Frontier models give confident-sounding answers to things they don't know. If you're not knowledgeable enough to catch errors, you can build strategies on wrong foundations. The "good enough" trap — AI output is often 80% there. If you stop at 80%, your work looks like everyone else's. The 20% you add is the differentiation. Over-automation without understanding — I automated a workflow without fully understanding it first. When it broke, I couldn't fix it. Understand before you automate. Vendor dependency — My workflows are deeply integrated with specific AI tools and APIs. Pricing changes, policy shifts, and service disruptions are real risks at this point. The Honest Summary AI tools have made me more productive, creative, and capable than I've ever been. They've also made me lazier in ways I didn't notice until recently. The people winning with AI in 2026 aren't the ones using the most tools or running the newest models. They're the ones using AI to amplify genuine skills and judgment — not replace them. What's your honest take after 6+ months of serious AI use? Curious whether others have hit these same walls. submitted by /u/Typical-Education345 [link] [comments]

persistent memory system for AI agents — single SQLite file, no external server, no API keys. free and opensource - BrainCTL

Every agent I build forgets everything between sessions. I got tired of it and built brainctl. pip install brainctl, then: from agentmemory import Brain brain = Brain(agent_id="my-agent") context = brain.orient() # picks up where last session left off One SQLite file. FTS5 search. Knowledge graph. Session handoffs. Write gate that rejects redundant memories. MCP server with 192 tools for Claude Desktop/VS Code. LangChain and CrewAI adapters included. No outbound server, no API keys, no LLM calls for any memory operation. MIT licensed. Best part is I dont want any of your money. GitHub: https://github.com/TSchonleber/brainctl PyPI: https://pypi.org/project/brainctl/ Happy to answer questions about the architecture. submitted by /u/Despairil [link] [comments]

How do I process the fact that civilisation will (likely?) be wiped out in a few years?

I am 23. A week ago I thought progress in LLMs (for my applications at least) was topping out. I was wrong. It's accelerating. I can't believe how blind it was. I only use LLMs like Claude as a search engine, for proofreading, and as a sort of writing/philosphy partner and diary-ish thing. I don't code very much these days. I am sure you heard about Claude Mythos. It broke every OS it was exposed to. And yes, it was contained, great, but it's not long until a malicious actor makes a Mythos or something even more powerful and lets it out or abuses it for themselves. It would appear that the window for us to create an "Oracle" AI, safely contained, is long-gone. AI agents are now the most marketable AI product. A week ago I thought the Paperclip maximizer was a fun thought experiment. Now I genuinely think it's likely to happen very soon. Like within 2-6 years. What the hell am I supposed to do? How is everyone else in the world, on the street, acting so normally, going to work, raising kids, playing guitar? I am totally powerless. Nothing is going to stop this from happening. The forces of the market are going to edge us closer and closer to armageddon until it happens. And I will be paperclips. Or a denizen of the Matrix if I'm very lucky and the utility function is "make humans happy" or something. EDIT: I'm sorry, is this a fringe opinion? This is not a troll post. I am completely serious. EDIT 2: I am not doomscrolling the internet. I am currently on a retreat immersed among AI researchers and AI safety people. They have no incentive to tell me anything except their honest thoughts. And their thoughts are not good. submitted by /u/PhiliDips [link] [comments]

Maestro v1.6.1 — Codex now has a full 22-agent orchestration platform as a native plugin

If you've wanted Codex to handle larger multi-step work without you manually chaining prompts, Maestro just dropped native Codex support in v1.6.1. Maestro is an open-source multi-agent orchestration platform. You describe what you want to build. It classifies the task complexity, runs a structured design dialogue, generates an implementation plan with a dependency graph, then delegates phases to 22 specialized subagents — architect, coder, tester, security engineer, data engineer, debugger, code reviewer, and more. Independent phases run in parallel. A final quality gate blocks completion on unresolved Critical or Major findings. It's been running on Gemini CLI and Claude Code for a while. v1.6.1 makes Codex a first-class runtime — all 22 agents, 19 skills, MCP entry-point, and runtime guide ship as a native Codex plugin. Install (Codex): Clone the repo, cd into it, then open Codex and run /plugins. Select Maestro and hit install. git clone github.com/josstei/maestro-orchestrate What you get inside Codex: /orchestrate — full workflow: design dialogue, implementation plan, phased execution, quality gate /review — standalone code review with severity-classified findings /debug — systematic root cause analysis /security-audit — OWASP + threat modeling /perf-check — bottleneck profiling /seo-audit, /a11y-audit, /compliance-check — for user-facing work Simple tasks route to an Express workflow (1-2 questions, brief, single agent, code review, done). Complex tasks get the full Standard workflow with a design document, implementation plan, parallel execution, and hard gates on quality checks. 22 agents across 8 domains (Engineering, Product, Design, Content, SEO, Compliance, i18n, Analytics). Each agent has least-privilege tool access — read-only agents can't run shell commands, shell-only agents can't write files. Why this is worth trying on Codex specifically: Codex is great at focused code generation but you're usually the one holding the plan in your head across multiple prompts. Maestro moves the plan into a structured session with persistent state, so you can resume interrupted work, and the orchestrator is the one managing handoffs between specialized agents instead of you copy-pasting context around. The v1.6.1 rewrite also means the same canonical source tree powers all three runtimes (Gemini, Claude, Codex). Future features ship to Codex at the same time as the others, not three releases later. Repo: https://github.com/josstei/maestro-orchestrate Open source, 294 stars. If you try it on Codex and hit issues, GitHub issues are open — I'm actively maintaining this. submitted by /u/josstei [link] [comments]