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:
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.
Ganesan Anand retweeted
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.
Ganesan Anand retweeted
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.
Ganesan Anand retweeted
The MEAN Stack: MongoDB, ExpressJS, AngularJS and Node.js j.mp/16jOGU2
Ganesan Anand retweeted
I guess I'll be writing my own implementation of Latent Dirichlet Allocation (+ hLDA, sLDA) since nobody believes in commenting their code.
Ganesan Anand retweeted
Some command line tools I wrote with Crunch that make Mahout easier to use for new data scientists: blog.cloudera.com/blog/2013/…
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What was #MSL @MarsCuriosity's POV while descending to the Mars surface? Low-res video from MARDI gives a sense go.nasa.gov/OVcgfP
Ganesan Anand retweeted
Making The Web Faster: CloudFlare Adds Support For Google's SPDY Protocol techcrunch.com/2012/06/15/ma… via @TechCrunch
Ganesan Anand retweeted
It takes CERN less than a minute to produce more data than the size of the e-bay and Facebook data warehouses combined!
Ganesan Anand retweeted
Apple patent reveals face detection system with multi-user logins for iOS devices & MacBooks goo.gl/fb/dqSOK
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ReadWriteHack: Engine Yard Releases Heroku Migration Tool http://rww.to/gDUAhc
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StumbleUpon Unveils Paid Discovery, Its New "No Click" Ad Platform (@alexia / TechCrunch) http://tcrn.ch/fCBH6M http://techme.me/BIF3
Ganesan Anand retweeted
I live in Fukushima city: #reddit #flipboard http://bit.ly/hbbYvc
Ganesan Anand retweeted
LinkedIn Posts $243M In 2010 Revenue, $15.4 Million In Net Income http://tcrn.ch/gJ3A9Q by @leenarao



























