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Aakash Gupta Proposes Shared Claude Code Repo as Product Manager Operating System

Aakash Gupta Proposes Shared Claude Code Repo as Product Manager Operating System▶

Product writer Aakash Gupta argues PMs should build a shared 'Team OS' repository with a .claude folder, function-specific folders and a CLAUDE.md doc index so every team role can query context. He frames it as a way for PMs to stop being the coordination bottleneck, and links to a video on the approach.

Original post · 2 min read
The PM job used to be about holding context across your team. Now your team is 3x bigger, every role makes product decisions, and engineers are shipping without you.

The PMs who figured this out stopped being the context node. They built one.

A PM used to support 3-4 engineers. Now it's 10+ engineers, plus sales, marketing, support, and design. You cannot manually hold context at that ratio. The math breaks. So the best PMs are building what amounts to a Team Operating System: a single repo where every role on the team queries shared context directly.

The architecture is simpler than you'd expect. A .claude folder with shared agents, commands, and skills. A product development folder with subfolders for each function. A team folder for onboarding and retros. And a CLAUDE.md at the root with a doc index that tells Claude how to navigate the entire repo.

The doc index is the part worth paying attention to. It means anyone on the team can ask a natural language question and get answers from across every function's context. The new designer asks about pricing strategy and gets the answer from the product development folder. The engineer asks about a customer pain point and gets it from support docs. No PM meeting required.

This is the PM version of what happened to middle management in the 2010s. Collaboration tools made it possible for ICs to coordinate without managers as intermediaries. Team OS does the same thing to the PM's coordination function.

The PM who only coordinates is the PM this ratio will crush.
Build the system that replaces you as the bottleneck.
Aakash Gupta @aakashgupta
Every team at your company should be creating their own 'Team OS' in Claude Code on Github. Here's how:

1:45 - What is a Team OS
13:37 - Shared skills and commands
25:24 - Shared team automations
59:50 - The learning flywheel
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More in Agents & Dev Tools

Developer Rebuilds Seven Adobe Apps in Rust Using Opus 5.5

Peter Yang highlights a developer who reimplemented seven Adobe apps, including Photoshop, Premiere and Lightroom, in Rust with Claude Opus 5.5 and open-sourced them. The developer believes they can match Adobe's features within months, against Adobe's $840 yearly all-apps plan.

Original post · 1 min read
It's insane to watch AI blow apart closed source software and games.

4 examples from the past month:

1. 7 of Adobe's biggest apps, including Photoshop, Premiere, and Lightroom, have been partially rebuilt in Rust with Opus 5.5 and open sourced. It's still early, but the developer thinks they can match Adobe's features within months. Adobe's all-apps plan costs $840/year.
Miguel Ángel Durán @midudev
Todos los productos de Adobe reimplementados desde cero, gratuitos y de código abierto

→ getartcraft.com/apps
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Vercel's Guillermo Rauch Explains Turborepo's Migration From Go to Rust

Guillermo Rauch says Vercel moved Turborepo from Go to Rust, a migration that was controversial internally due to human costs. He argues that with AI agents the calculus has changed, so what is best for humans is no longer necessarily best for business.

Original post · 1 min read
DHH is fundamentally right about Rust. For context, Vercel has been undergoing a Rust-ification (carcinization, technically 🦀) for a while.

One of the first projects we migrated was Turborepo, from Go to Rust¹. The migration completed, but the RoI was actually quite controversial internally.

While Rust was in our eyes better for low-level OS access, something crucial for a build system like Turbo, the human migration costs were very sustantive.

Go is very fast. It's beautifully designed. It's easy to iterate on. We were very conflicted about the migration, because it was *humans* writing the code, *even if we knew Rust was a better choice*.

The calculus has now changed. What's "best for humans" is no longer necessarily "best for business".

FWIW, it's also quite unlikely that Rust is the end-all-be-all toolchain. I'm quite certain there's greener pasture ahead, because Rust itself was designed before the 'supersonic tsunami' of agents hit.

¹ https​://vercel.com/blog/how-turborepo-is-porting-from-go-to-rust
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Integer Multiplication Algorithm Bound Tightened Repeatedly With Astra

A post reports that a user running ChatGPT Astra in a loop is repeatedly breaking records for integer multiplication algorithms. It quotes an update to OpenAI problem #109 that tightens the constant from 2^-182 to 2^-59, a roughly 500,000-fold improvement over the previous result.

Original post · 1 min read
This guy has 6.1 Astra running in a loop and is breaking the record for integer multiplication algorithms every few hours lmaooooo.
Doug Colkitt @0xdoug
We are publishing an update to OpenAI problem #109 Integer multiplication) with another substantial further tightening:

κ = 2⁻⁵⁹ (from OpenAI’s original κ = 2⁻¹⁸²)

Approximately 500 thousand fold improvement over our previous result and a 2¹²³ fold improvement over the original OAI result.

The latest redesigned the finite network to share intermediate computations and scratch space, then tightened the recursion and Gaussian estimates.
♥ 4.1K · ⟲ 118 · 👁 167.4KView on X ↗

Boris Cherny Says Prompting Claude Should Feel Like Talking to a Coworker

Boris Cherny explains his approach to prompting Claude, advising users to give clear goals, specify effort level and verification steps rather than relying on heavy scaffolding.

Original post · 1 min read
I am surprised that people are surprised this is how I prompt Claude.

Talk to Claude the way you would a coworker. There's no secret to prompting. There's no need to be overly scaffolded or prescriptive for most tasks -- give Claude a goal, and it will figure it out.

Back in the Sonnet 3.5 days, your prompt mattered a lot. Nowadays, it's much more important to communicate to the model:

1. What you want it to do
2. How much effort you want it to spend
3. How it should verify that it did the right thing
Boris Cherny @bcherny
Prompt
♥ 12.1K · ⟲ 720 · 👁 1.1MView on X ↗

Eric Raymond Highlights Open-Source Rust Clone of Photoshop Built via LLM

Eric S. Raymond shares the photocraft GitHub project, a clean-room open-source reimplementation of Photoshop that he says was likely generated by decompiling the app, converting it to a spec and prompting an LLM for Rust. He argues this threatens closed-source software.

Original post · 1 min read
This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation.

No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust.

Adobe just got nuked. And closed source is dead, dead, dead.

github.com/storytold/photocraft
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Nat Eliason Details Fourteen Ways His Bot Setup Automates Work

Nat Eliason lists fourteen functions of his bot setup, including a chief-of-staff agent that drafts emails, specialist agents per work lane, and cloud coding agents that open pull requests from Linear issues. He notes GrokBot as a substantial improvement over his previous OpenClaw setup.

Original post · 2 min read
Things my @bot setup does that still blow my mind:

1. A Chief of Staff who opens the day pulling open loops from email & tasks and suggesting things it can knock out before 7am.

2. After every meeting, decisions get folded into Notion, Linear, and Todoist — not left rotting in Granola

3. Every email starts as a draft. The CoS bot scans my email every ~2hr and drafts replies to nearly everything — including checking my cal for availability and finding requested attachments / links

4. A specialist for each lane: curriculum, engineering, coaching, hiring, content, ops, and one for every single piece of software

5. Routines that keep running while I’m offline (e.g. monitoring Sentry errors in our apps and proactively fixing things)

6. Group rooms where 2–4 bots share one project thread instead of me copy-pasting context

7. Cloud coding agents that pick up Linear issues and open PRs after running the list of open work by me EoD — then squash-merge to main when it’s done

8. Meeting prep briefs pulled from Granola + Notion before I walk in

9. A growing shareable knowledge base in Notion + a GitHub repo that we update daily based on what happens at school

10. Student progress look-up across Expertise, Followers, and CoFounder without inventing numbers — chat anytime to see where a student is on their business work

11. Mentor Mind that coaches me on how to hold the bar without inventing doctrine

12. Todoist as a central task list where it logs things it’s blocked on for me, or from meetings / emails — and I can paste links into chat to direct it how to solve them

13. Engineering work is automatically tracked in Linear so my and the product teams’ bots don’t collide with each other

14. Presentations spun up in Gamma / Claude Design without me opening a slide tool

15. Plaud / live capture → notes the bots can actually act on

Probably more but these were the immediate ones we thought of.
Nat Eliason @nateliason
GrokBot feels like absolute magic at this point, a meaningful leg up on my previous OpenClaw etc. setups.

And with how easy it is to setup, there's really no excuse now.
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