Mehrab Ratul

keep editing . . .

[Mehrab Ratul @Mehrab_ratul]

The Best is Yet to Come . . . Have Faith and Patience👉

Always put out Heart and Soul 💗

[Anatoli Kopadze @AnatoliKopadze]

Anthropic engineer:

"Most people will use Sonnet 5 and Fable 5 wrong. You can set them up right in one afternoon and stop overpaying every single day."

In 31 minutes he shows how to test every model against your real use case and stop overpaying for nothing.

Watch the session, then read the guide below on the Claude features 99% of users never find.

[Avi Chawla @_avichawla]

Prompt, context, harness & loop engineering, clearly explained!

An agent is a while loop with four layers of engineering wrapped around it:

- Prompt engineering
- Context engineering
- Harness engineering
- Loop engineering

Each one wraps the last, and the model sits in the middle, so none of them compete with the others. Instead, they just zoom one level further out.

> Prompt engineering:

This defines the input the model sees on one call, often composed of a role, instructions, examples, and an output format.

The techniques here alter the internal computation and reasoning the model goes through due to the wording it sees:

- Chain-of-thought makes it work in steps before answering
- Few-shot examples define the format and the edge cases
- A JSON schema or XML tags make the output parseable by code
- Self-consistency samples a few chains and takes the majority

> Context engineering:

It's everything the model sees on a turn, not just the prompt. That includes the query, retrieved docs, memory, prior turns, and tool outputs from earlier steps.

The window is finite and fills up fast, so the engineering work is to rank inputs and cut everything that isn't pulling weight.

You do this by:

- Retrieving only the chunks relevant to the query, then reranking them
- Keeping key facts out of the middle, where accuracy drops
- Summarizing old turns, evict stale outputs, push big blobs to files

> Harness engineering:

It's the code around the model that defines the tools, parses the calls, retries on failure, and can route work to sub-agents so one handles retrieval and another handles code.

A verifier then grades the result by running tests, validating a schema, etc.

Prompt and context involve getting one call right. The harness involves everything that has to happen around that call for it to run in a real system.

> Loop engineering:

In the usual setup, you manage the outer loop, i.e, you write a prompt, read the turns the agent runs, write the next prompt, and repeat, while catching failures.

This layer hands that job to the agent itself. It kicks off on a schedule or an event, and runs many turns with no prompt in between.

A loop inherently doesn't know when it's finished. An agent can report that it's done and halt while the tests still fail. So the stop can't be the agent's word, but rather it has to be a real signal, like:

- A turn and token cap to stop stuck runs
- A no-progress detector to catch repeated calls
- A completion check to verify the goal with a separate model or a deterministic test

By this layer, you're operating on the whole run, so the engineering moves from writing each prompt to setting the goal and the stop conditions up front and letting it run.

If you want to dive deeper into loop engineering, my co-founder wrote a full breakdown of that outer loop.

It goes from the basic while loop to a run that finishes on its own, with the code behind each part, and the parts that are hard to get right, like knowing when to stop, context rot over a long run, and keeping the checker separate from the maker.

Read it below.

[Haramain Archive @muslimmakkah]

Tools for washing the Ka’bah for the year 1448 AH

[Hasan Toor @hasantoxr]

Claude Code Project Structure: The Complete Map

[Islamic Motivational Quote Image @RoShZiMu]

Ayat al-Kursi
The one verse millions recite before sleep and feels like peace when you understand it word by word 🤲

[Mehrab Ratul @Mehrab_ratul]

@Judy_ca1 @oneuios What's the name of this glass package 📦?

[Mehrab Ratul @Mehrab_ratul]

@NadzuAI AI

[Black Hole @konstructivizm]

The most detailed image of the Moon to date.

The massive image was assembled from 1,000 individual frames captured with a Nikon Z8 camera through a Takahashi TSA-120 telescope—the final resolution is approximately 40 megapixels.

[Mehrab Ratul @Mehrab_ratul]

@shauseth @grok please answer this

[Blackameer @Muktarameeer]

Indeed, the creator Allah SWT deserves to be worshipped😍💯

[مغفرة @1A_610]

ﷺ🔄

[Inside the Haramain @insharifain]

On behalf of our team we wish everyone Eid Mubarak!

[It's Ahmad @AhmadX_Official]

Complete Eid Takbeerat in a soothing, heart-calming voice.

Eid Takbeerat recited with deep humility, filling the hearts with peace and joy
Experience the true spirit of Eid with these beautiful Takbeerat that touch the soul and revive faith

Repeat:
Allahu Akbar, Allahu Akbar, Allahu Akbar, La ilaha illa Allah, Allahu Akbar, Allahu Akbar, wa lillahil-hamd

Don’t forget to share, so you may earn reward and spread joy to others 🤲

[𝐌𝐚𝐡𝐝𝐢 @Mahdii_365]

Eid al-Fitr Takbirs, Save them with you.

[Mehrab Ratul @Mehrab_ratul]

@SamsungMobile @SamsungMobile Thanks for tagging. I already have my Galaxy.

[• @Alhamdhulillaah]

اللهم إنك عفو تحب العفو فاعفو عنا

Allāhumma innāka ʿafūwwun tuḥibbul ʿafwa fa-ʿfu ʿannā

Oh Allāh, You are the Most Forgiving, and You love forgiveness, so forgive us.

[فــذكِّر @thkkkrr_]

وفي أول جمعة من شهر رمضان المبارك.

[Mehrab Ratul @Mehrab_ratul]

Do you remember when you joined X? I do! #MyXAnniversary

[Clicks @clickskeyboard]

Clicks builds phones now. Introducing the Clicks Communicator… Reserve today at https://t.co/atGOv4UblV!

[internet hall of fame @InternetH0F]

In 1966, children were asked how they imagined life in the year 2000