Anand @spatialthinker8 - Twitter Profile

7 days ago

Claude Code just dropped "Getting Started with Loops" This is their first official document about Loop Engineering. Spoiler: prompt engineering didn't survive. Here's the full guide in one post: 1. Turn-based Every prompt you send already runs as a loop: Claude gathers context, takes action, checks its own work, and repeats until it decides the task is done or realizes it needs your input. 2. Goal-based You define what "done" looks like with /goal, and Claude keeps iterating toward it. Every time it tries to stop, a separate evaluator model checks your condition - if it's not met, Claude gets sent back to work until the goal is reached or the turn limit hits. 3. Time-based This is the /loop command: нou set an interval and a prompt fires on schedule. For example, every 5 minutes Claude checks your PR, addresses review comments, and fixes failing CI. 4. Proactive Here you set up an event once, and the loop triggers itself whenever that event happens - with zero human input. Anthropic also shared optimization advice - and this part matters most: - Loop quality depends on system quality. - Tokens are the real cost None of this is magic. It's the same familiar parts - /goal, /loop, Skills, Hooks - composed into systems that run without you. I built exactly that kind of system in my article: Loop that wakes up at 6 AM, finds work on its own, reviews itself, and leaves ready PRs for you. Step by step, from SKILL(.)md to cron trigger:

0x_kaize's tweet photo. Claude Code just dropped "Getting Started with Loops"

This is their first official document about Loop Engineering.

Spoiler: prompt engineering didn't survive.

Here's the full guide in one post:

1. Turn-based

Every prompt you send already runs as a loop: Claude gathers context, takes action, checks its own work, and repeats until it decides the task is done or realizes it needs your input.

2. Goal-based

You define what "done" looks like with /goal, and Claude keeps iterating toward it. Every time it tries to stop, a separate evaluator model checks your condition - if it's not met, Claude gets sent back to work until the goal is reached or the turn limit hits.

3. Time-based

This is the /loop command: нou set an interval and a prompt fires on schedule. For example, every 5 minutes Claude checks your PR, addresses review comments, and fixes failing CI.

4. Proactive

Here you set up an event once, and the loop triggers itself whenever that event happens - with zero human input.

Anthropic also shared optimization advice - and this part matters most:

- Loop quality depends on system quality.
- Tokens are the real cost

None of this is magic. It's the same familiar parts - /goal, /loop, Skills, Hooks - composed into systems that run without you.

I built exactly that kind of system in my article:

Loop that wakes up at 6 AM, finds work on its own, reviews itself, and leaves ready PRs for you. Step by step, from SKILL(.)md to cron trigger:

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spatialthinker8 retweeted

Movez

@0xMovez

6 days ago

Andrew Ng just dropped a 3-hour course on how to become an AI Engineer in 2026: • 00:00 - How to build agentic AI systems • 04:25 - Future of AI engineering • 23:38 - AI Prompting full course • 2:52:17 - Creating an app with AI in 30 minutes This 3-hour watch could replace 10 AI engineering courses on the internet. Watch it today, then read how to run a self-improving system in the article below.

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spatialthinker8 retweeted

ClaudeDevs

@ClaudeDevs

7 days ago

A few patterns we frequently use with Fable 5: Use Fable 5 as an "advisor." An executor (Sonnet 5) calls Fable 5 for guidance. Most tokens are billed at the lower executor rate.

ClaudeDevs's tweet photo. A few patterns we frequently use with Fable 5:

Use Fable 5 as an "advisor."

An executor (Sonnet 5) calls Fable 5 for guidance.

Most tokens are billed at the lower executor rate. https://t.co/JIiZ2gm99Y

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spatialthinker8 retweeted

Anatoli Kopadze

@AnatoliKopadze

7 days ago

Anthropic engineer: "You're not supposed to prompt Claude. You're supposed to build a system that prompts itself." In 45 minutes she breaks down how Anthropic builds agents that remember, learn from their mistakes, and get smarter with every run. Worth more than any paid course you'll find on building agents. Watch the session, then read the guide on building loops below.

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