Reid Burke

Felix Rieseberg:

This month, I laid the traditional coding interview to rest. As a hiring manager at Anthropic, I stopped asking candidates to do them. It had a good run: Being able to quickly define problems and find elegant solutions was a weak but useful predictor for how successful you’d be on my teams. Small coding challenges in real code did tell us something meaningful about candidates.

That’s no longer true. There’s no more point in giving you a little React challenge than there is in quizzing people about assembly; Claude is now better at both. Our most impactful builders are successful regardless of how good they are at these tests.

[…]

I’m seeing engineers who are comparatively new fly past people who are probably better coders and have been around much longer. Hunger beats tenure.

The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month.

I have a spicy, optimistic take – I think there's an opportunity for junior engineers: https://t.co/PVvpQCbQtK

— Felix Rieseberg (@felixrieseberg) October 27, 2026

Apple:

Visual productivity apps receive a new generation of intelligence features for subscribers, including an intelligent assistant, built on Apple models and OpenAI, directly within Keynote, Pages, and Numbers. The assistant understands document context to help users accomplish more without leaving their work. In Keynote, the intelligent assistant helps with designing, animating, and refining slides. In Pages, it drafts, restructures, and fine-tunes written content. In Numbers, it calculates, visualizes, and organizes data; recommends suitable chart types with a one-tap preview; and builds custom tables using world knowledge. New MCP support, built on this platform, enables external AI agents and tools to read content, perform edits, and execute automated actions directly in Keynote, Pages, and Numbers.

[…]

Keynote introduces support for Keynote Interchange Format (.keyx), an open JSON-based bundle file format designed to be readable and accessible to external tools, developer workflows, and AI agents.

Huge day for Creator Studio today.

Our new in-app assistants can help you get things done in record time. MCP allows you to bring your own agent if you want. And an open source format for Keynote (and Python library!) so you can create Keynote documents programmatically on any…

— Jesse Bunch (@bunchjesse) October 27, 2026

Anthropic:

At Anthropic, coding is no longer the bottleneck to building systems or doing research. Claude is able to autonomously iterate on research loops, micro-optimize complex programs, and build new services from the ground up at a speed and scale we haven’t seen before. The bottleneck, now, is all of the developer infrastructure built for human scale: source control, builds, and CI.

In May 2026, Anthropic averaged around 2,500 code changes merged per day; as of September, we merged over 30,000 per day.

In order to support this growth, we built Scion, an in-house version control system, and fully migrated our monorepo from git in five months.

Scion isn’t the only way to scale for agents. Cursor’s Git at any scale describes Continuity, a git store that keeps a write-ahead log in S3 as the source of truth and treats every repo on disk as a disposable cache. It came along as Tobi Lütke was frustrated with Shopify’s internal git system, so he implemented it over a weekend as walgit: an open-source Rust git server that runs as one binary in front of an S3 or GCS bucket, with no database and no leader, serving fetch, push, LFS and fast bundle-based clones even for repos larger than the machine serving them.

Git at Scale (by cursor) has been one of the most interesting blog posts i've read in a while. It came right when I was frustrated with Shopify's internal git system.

As an exercise, I've implemented it over the weekend as open source. It's a single rust binary that you can… pic.twitter.com/ckNm1RqclH

— tobi lutke (@tobi) August 24, 2026

Ryan Dahl noted what makes this pattern practical now: S3 has supported compare-and-swap since 2024, so walgit can use the bucket for both storage and coordination.

like celld, walgit depends only on s3 for storage and coordination. This has all become possible because of S3's support for Compare And Swap since 2024.

It's just a practical pattern for reliability and costs. https://t.co/OrV9ul4XpE

— Ryan Dahl (@rough__sea) August 24, 2026

Two months later, all of Shopify runs on an internal version that has diverged so far Tobi can’t maintain the public one:

I can’t maintain it. And our internal version massively diverged now

All of Shopify is running on it though.

— tobi lutke (@tobi) October 27, 2026

Mustafa Ali:

It’s tempting to just point an LLM to the React Native codebase and try to one-shot the same features in native, but it doesn’t work. Even if you ask it to gather as much information as it can up front, freeze that into specs, task files, and then implement it, you end up with a huge amount of unmaintainable code that can’t be shipped.

To solve this problem, we built a system called Helix that takes a more gradual approach. It doesn’t expect the first output to be correct, and builds a loop where an imperfect attempt simply cannot move forward until it becomes a good result.

The developer points Helix at a screen. Helix reads the React Native code and proposes a sequence of checkpoints (small, ordered slices of the work) that can be reviewed in minutes. Then, checkpoint by checkpoint, it builds: each one must prove its behavior with tests, match the running app in a visual review, survive two adversarial code reviewers, and get a human’s nod before it’s committed and the next one starts. Feedback from every review is remembered, so the loop gets more autonomous as the migration progresses.

Jessie Frazelle is making her own Home Assistant compatible hardware:

People have been tweeting ridiculous PCB images for the last few days, since Astra came out. I already knew the models were good at datasheet review before Astra. The win isn’t one-shotting a PCB. It’s getting through the work an electrical engineer would do, including the parts you hate doing.

Astra will have competition:

Grok is going to be so good at building hardware.

You need end-to-end data:
• design on computer (eg CAD)
• computer to machine (eg CAM)
• real-world part (eg CMM)

And SpaceX has that data. https://t.co/5THu1iK8Wc

— Christian Keil (@pronounced_kyle) September 7, 2026