Hello. I am a full-stack developer specializing in AI automation, agent development, and model development. I am proficient in voice AI, various LLMs, and TTS development. In particular, I can handle the entire software development process, including Web3 integration, third-party API integration, AWS, and product launches. I possess significant experience in various specialized fields, such as internal API testing using SwaggerUI, web or mobile app version management via GitHub, and DNS. If my expertise aligns with your project, please feel free to contact me at any time. Please send a DM or Telegram: @devstarfive

Most AI agents are toys for two reasons: they can't run on their own without you hitting go, and they can't safely use a real API key. About a week ago (June 9) Claude fixed both in Managed Agents. So I ran it against a real production checklist and built one live. - What it is. Managed Agents = hiring Anthropic as the landlord for an AI worker. It runs in their locked sandbox, on a schedule, using your tools, and hands back a finished result. Three words: the agent (job + tools), the environment (the safe computer), the session (one run). - What just changed. Deployments = it now runs on a recurring schedule (finest is once a minute), Anthropic fires it for you. Vaults = a tool gets your API key as an env variable, but the agent never sees it — it's swapped in only to the addresses you allow. - The build. One plain-English prompt made a "morning email brief" agent: read the last 24h of Gmail, sort into needs-reply / FYI / ignore, post to Slack. It wrote its own config, locked networking to just Gmail + Slack, and even created the Slack channel when it didn't exist. - The new part: deployments. Attach the vault, tick "I'm authorized," set the trigger to a schedule (weekdays 9am), done. No server, no scheduler to host — my inbox is triaged in Slack before coffee. - Honest verdict. Real step toward production, not set-and-forget. Logs/retries/approval gates are there out of the box; you still add your own alerting and testing. It's beta, the key trick only works for straight key-passthrough (AWS-style signed logins don't yet), and the floor is 1 minute. Daily briefs/reports: ready now. Customer- or money-touching jobs: keep a human in the loop. My take: for the simple, on-time jobs that just need to happen without you, this crossed the line from toy to worker. Cost is tiny — ~$0.08 per session-hour, idle is free, pennies a morning. 📎 Full Managed Agents guide PDF pinned below — the production checklist, the console tour, the exact build, and the cost breakdown.

This is a tiny setting most people never touch — and it's the difference between cruising all day and slamming into a usage limit by mid-afternoon. Here's why it matters 👇 Claude Code counts against your limit by tokens — basically the words going in and coming out. The trap: when you ask for a small change, Claude often rewrites the *entire* file and prints all of it back, plus a paragraph explaining what it did. Change two lines in a 400-line file and it can reprint all 400. Every reprinted line is output you pay for — for code you already had on your screen. The fix is one rule pasted into your CLAUDE.md: tell it to show only the changed lines — no full-file rewrites, no explanations unless you ask. It still reasons just as hard on tough problems. It just stops re-typing code you already have, and your token use drops off a cliff. I put together a short step-by-step guide with the exact line to paste, a no-file version for one-off chats, and an *honest* model setup (default to Sonnet, jump to Opus only when it's worth it, put Haiku on the grunt work) — about 10 minutes, no new software. 👉 Grab it here: https://flicker-celestite-7b6.notion.site/Stop-Hitting-Claude-Code-Usage-Limits-The-One-Line-CLAUDE-md-Fix-38ad180d8c80812786cdce0da53dd10f?source=copy_link What's eating your Claude limits fastest right now — long sessions or whole-file rewrites?

Happy Father's day to all the Dads

Real talk: You don't need to be a developer to make serious money building AI agents. I've personally coached complete beginners who went from zero to their first $2K+ client in under 30 days using only no-code tools. And I'm going to show you exactly how they did it. Here's what's actually happening: The barrier to entry for building AI agents just dropped to zero. The same tools that used to require engineering teams are now drag-and-drop. If you can use Canva or build a Notion page, you can build AI agents that businesses will pay thousands for. The uncomfortable truth: - Most "AI experts" are just good at using no-code tools - Your first agent doesn't need to be perfect to get paid - Businesses care about results, not how technical you are - The people making money started messy and learned fast - Waiting until you're "ready" means you'll never start But here's what separates people who actually make money from those who stay stuck in tutorial hell: ❌ Learning every tool before taking action ❌ Building complex agents before mastering simple ones ❌ Perfectionism over shipping ❌ Focusing on features instead of business outcomes ❌ Not talking to real prospects until "everything is ready" The shift you need to make: Stop consuming content. Start building and selling. One paying client teaches you more than 100 hours of tutorials ever will. Check out the video where I break down the exact no-code tools to use, the 3 types of agents that actually sell, and the 30-day plan to land your first client... Who's ready to build their first agent? Drop a comment below 👇