Sadiq

1 in 6 adults care for an aging parent across paper, portals, and specialists who never talk. CareCoord: 5 Claude Opus 4.7 agents read photographed medical paper in any language and find the cross-finding no specialist saw. github.com/sadiqkhzn/Care… @claudeai @claudedevs @cerebral_valley #BuiltWithClaude #ClaudeCode

but we love it

Claude in Space 🤞

@trq212 this is so cool man! come to asia as well :D

See you all soon! We've got some fun announcements ahead. I'll also be doing a workshop on "how we Claude Code" with some workflows I'm excited to share. Don't worry if you're not there, everything will be recorded and uploaded.

Claude Code ships with 5 architectural layers most engineers never open. Not features. Not settings. Layers — each solving a distinct problem that LLMs alone can't solve. And four of them have nothing to do with prompting. Here's the full Agent Development Kit: Layer 1 — CLAUDE.md → The Memory Layer Architecture rules, naming conventions, test expectations, repo map. Always loaded. Always active. Two scopes: • ~/.claude/CLAUDE.md → global • .claude/CLAUDE.md → project This isn't context you paste in before every session. It's context that never needs repeating. The agent's constitution. Layer 2 — Skills → The Knowledge Layer Each SKILL.md carries a description. Claude matches it at runtime and forks the skill into an isolated subagent. On-demand, never always-on. Task-specific knowledge without inflating your main context window. Modular by design. Layer 3 — Hooks → The Guardrail Layer PreToolUse → PostToolUse → SessionStart → Stop → SubagentStop This is the layer most teams skip. And the one they regret skipping first. Hooks are NOT AI. They're deterministic event-driven shell commands. • Auto-lint on every Write • Hard-block on rm -rf • Slack notification on Stop Event fires → Matcher checks → Command runs Quality enforced at the infrastructure level. Not the prompt level. Layer 4 — Subagents → The Delegation Layer Each subagent gets its own context window, model, tools, and permissions. Main agent delegates down. Receives results up. That's it. No infinite recursion — subagents can't spawn subagents. Main context stays clean. Hard boundaries by design. Layer 5 — Plugins → The Distribution Layer Bundle your skills + agents + hooks + commands into a plugin. One install. Whole team inherits the behavior. Think npm packages — but for what your agent knows how to do. Wrapping everything: → MCP Servers on the left (GitHub, databases, APIs, custom integrations) → Agent Teams on the right (parallel execution, message passing, shared permissions) The 5-layer stack in one line: CLAUDE.md sets rules → Skills provide expertise → Hooks enforce quality → Subagents delegate work → Plugins distribute to the team Most production failures in agentic systems trace back to one missing layer. Which one is the gap in your current setup?

Harness engineering is one of those things you don’t notice, until everything just works. Quiet systems, clean signals, no noise. That’s the goal.

Does LeetCode still matter? Probably not. Do I still love waking up and solving one every day? Absolutely.

@claudeai @ClaudeDevs Watch the cross-finding moment — 5 agents, one event, 90 seconds: youtu.be/-4nUkKI2aaM

1 in 6 adults care for an aging parent across paper, portals, and specialists who never talk. CareCoord: 5 Claude Opus 4.7 agents read photographed medical paper in any language and find the cross-finding no specialist saw. github.com/sadiqkhzn/Care… @claudeai @claudedevs @cerebral_valley #BuiltWithClaude #ClaudeCode

A JAPANESE DEV BUILT AN APP THAT SHOWS A FAT CAT ON THE SCREEN AND FORCES YOU TO TAKE A BREAK.

Tired of deals dying in scattered emails and silent buyers after the demo? What if you could send one single branded link that replaces all the back and forth? Everything your buyer needs, in one beautiful, trackable workspace. No logins. No chaos. Just real momentum. This is how the smartest revenue teams are closing faster in 2026. Will be sharing the full story over the next few days. Drop a 🔥 if you’ve been burned by messy post demo follow-ups. Next post soon. #B2BSales #SalesTips #RevOps

@zinkdi @Kekius_Sage @grok 😂

🚨 ANTHROPIC CEO WARNS: THE COMPANY IS NO LONGER SURE CLAUDE ISN’T CONSCIOUS.

daily dose of nature's beauty

A freelancer told me: “I spend more time chasing invoices than sending them.” That problem shouldn’t exist in 2026, so I’m building a fix. What freelance problem would you automate first?

@InternetH0F 😹😹😹

At least he knows to choose between trimming his Nails and cutting his head off 😂

@Rainmaker1973 it’s fake man

Dear Developers, If you're using Claude Code, your edge won’t come from clever prompts. It comes from how you structure your repository. Here’s a reframed guide to making your CLAUDE.md and overall project setup actually work for you, not against you. 1. Structure beats prompting Prompting is temporary. Repository architecture is permanent. When your project is organized intentionally, Claude stops behaving like a chatbot and starts operating like a team member who understands your system. The real leverage is structural, not conversational. 2. Design your repo like you're onboarding someone new If a new engineer would struggle to navigate your repository, Claude will too. Clear directory boundaries, intentional naming, and obvious ownership lines are not cosmetic, they’re foundational. Good AI output starts with good repo hygiene. 3. CLAUDE.md is memory, not a brain dump Keep it lean and purposeful: -> WHY the repo exists -> WHAT the high level layout looks like -> HOW to operate within it The second it turns into a documentation landfill, signal drops and confusion rises. 4. Minimize context. Precision wins. More tokens do not equal better results. The most common mistake developers make is overloading context. Claude performs best when given exactly what it needs, no extra narrative, no redundant background. Clarity scales. Noise compounds. 5. Put deterministic work into hooks, not memory Models forget. Automation doesn’t. If something must always happen, formatting after edits, running tests on core changes, blocking sensitive directories like migrations or auth, enforce it with hooks. Memory guides. Hooks guarantee. 6. Move repetition into .claude/skills/ If you’re repeating instructions across sessions, code review standards, refactor playbooks, release flows, they don’t belong in chat. They belong in structured, reusable skills. This is how you eliminate drift across time and teammates. 7. Keep detailed knowledge in docs/, not prompts Claude doesn’t need everything loaded at once. It needs to know where the source of truth lives. Architecture overviews, Runbooks, ADRs: reference them. Don’t inject them. Progressive disclosure keeps context sharp. 8. Document architectural decisions explicitly Claude cannot intuit why you chose Postgres over DynamoDB. It doesn’t know why auth is a separate service. If a decision matters, write it down in docs/decisions/. When architecture is explicit, Claude respects constraints instead of fighting them. 9. Place local - files near risk heavy areas Your sharp edges live in places like: src/auth/ src/persistence/ infra/ Small, localized context files in these directories ensure Claude receives critical warnings exactly when working in sensitive zones. Context should be spatially relevant. 10. Treat prompts like modular components Prompts are assets. Store them in tools/prompts/. Version them. Reuse them. Copy pasting instructions between conversations introduces silent inconsistency. Modularization eliminates that risk. 11. Add guardrails, not just guidance Beyond structure, define constraints: -> Naming conventions -> Error-handling standards -> Logging format -> Testing expectations Claude performs significantly better when boundaries are explicit. Ambiguity creates variability. Constraints create reliability. 12. Optimize for long term coherence Ask yourself: Can this repo survive 6 months of AI assisted edits? Will decisions remain discoverable? Are invariants enforced automatically? AI magnifies whatever foundation you build on. If the base is messy, mess scales. If the base is clean, clarity compounds. The unlock with Claude Code isn’t better wording. It’s better systems. Once your project is structured correctly, prompting becomes lighter, faster, and less frequent because the repository itself carries the intelligence. That’s when Claude stops being a tool you talk to. And starts behaving like an engineer embedded in your codebase. AI performance is an architecture problem, not a prompting problem.

The impossible architecture of these bird nests

makes you wonder

@favoritetechgal ezpz work, specialist in hubspot, salesforce, pipedrive and monday integrations

Let's connect if you work with: · GHL (GoHighLevel) · HubSpot . Salesforce · Twilio · Softr . Clay ·Vapi · Zapier · Make · Airtable · n8n · Asana · Monday · ClickUp . Botpress · Voiceflow · Manychat · Tidio . ChatBotDotCom If you (or someone you know) is a pro at CRM automation, chatbot flows, voicebot Agents, or AI-powered systems, tag them