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Article URL: https://pam-x402.vercel.app

Comments URL: https://news.ycombinator.com/item?id=47304534

Points: 1

# Comments: 0

Article URL: https://www.philipzucker.com/thin1/

Comments URL: https://news.ycombinator.com/item?id=47304527

Points: 1

# Comments: 0

Article URL: https://www.wsj.com/tech/ai/ai-needs-management-consultants-after-all-bd28ecb9

Comments URL: https://news.ycombinator.com/item?id=47304481

Points: 1

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Article URL: https://github.com/amazedsaint/clocoloop

Comments URL: https://news.ycombinator.com/item?id=47304453

Points: 1

# Comments: 0

After repeatedly asking Claude Code to rewrite things in my coding style, I decided to write a skill to do it automatically. Articulating my coding style made me realize that beyond aesthetics, it actually serves an important function: it minimizes the distance between variable references, which means I read code much faster. This is especially useful in the new era of agentic engineering, where the bottleneck is no longer writing code but reading and reviewing it. The skill is called Tighten.

Blog post: https://inmimo.me/blog/tighten Skill: https://github.com/markrogersjr/skills/blob/main/skills/tigh...

Comments URL: https://news.ycombinator.com/item?id=47304412

Points: 1

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Article URL: https://www.youtube.com/watch?v=eQgxFuw8f1U

Comments URL: https://news.ycombinator.com/item?id=47304408

Points: 1

# Comments: 0

I built this because I invest based on product conviction and couldn't find a clean way to track whether companies are actually executing on their roadmaps.

AlphaPerch uses a proprietary pipeline that synthesizes across diverse data sources and leverages AI to extract and classify product milestones by product line and execution stage (Expected, Announced, In Progress, Shipped, Delayed, Cancelled). Each milestone traces back to its original source so you can verify it yourself.

The platform is built to track any publicly traded company. TSLA, GOOGL, and RBLX are live because that's where my personal conviction is, but the framework generalizes. There's a coverage request form on the landing page if you want to see a specific company added.

Would love feedback on extraction quality and what's missing. Let me know if you find it useful!

alphaperch.com

Comments URL: https://news.ycombinator.com/item?id=47304400

Points: 1

# Comments: 0

Hi HN,

I built Compose Launcher because I often work on multiple projects at the same time, each with its own docker-compose setup.

It became difficult to keep track of: • which compose files are running • which ports are already in use • starting/stopping environments across different folders

Compose Launcher provides a small macOS GUI where you can register multiple compose files and manage them from one place.

You can quickly see running services, start/stop stacks, and avoid port conflicts.

The project is still early and I’d really appreciate feedback from people who run many docker-compose environments locally.

Comments URL: https://news.ycombinator.com/item?id=47304385

Points: 1

# Comments: 0

Article URL: https://wbnns.com/time-travel.pdf

Comments URL: https://news.ycombinator.com/item?id=47304378

Points: 1

# Comments: 0

Article URL: https://deplicator.github.io/xkcd-time-at-your-pace/

Comments URL: https://news.ycombinator.com/item?id=47304374

Points: 1

# Comments: 0

I built a system that can learn directly from its own codebase locally and understand the entire project context from the start. Current coding agents typically spend 2–3 minutes gathering context that already exists in the repository, which wastes both time and tokens. To solve this problem, I built a system called Monocod.

I originally created Monocod to help maintain my main project, but it evolved into something much more powerful.

The core issue with current coding agents is that they are trained in language context, not system context. They generate code based on text patterns rather than actually understanding the structure, dependencies, and state of a real codebase. In many cases, they don't truly "know" the codebase they are working with.

My system changes that.

Monocod self-learns from the codebase itself, continuously updating a local model during each loop. Because it already holds the full project context, it can guide coding agents much more efficiently. It can also detect gaps in the system architecture and in the codebase, enabling it to generate solutions that truly satisfy the user's needs rather than just producing surface-level code.

In my view, current LLM systems approach coding the wrong way. The foundation needs to shift from language-driven generation to system-aware intelligence. Monocod represents that new foundation for what I believe will be the next generation of real AI development tools.

Beyond generation, the system also performs post-generation analysis and maintenance of the codebase. It evaluates and improves the project structure automatically, and in my tests it outperforms major code analysis tools. All of this is done using pure algorithms, not heavy external services.

I built this primarily because, as a solo developer, it is extremely difficult to manually review and maintain large amounts of generated code. Most coding agents simply generate code to satisfy the immediate request, without considering long-term maintainability, production standards, or proper architecture.

Most users don't actually know what production-ready code should look like. Instead of guiding them toward industry-grade systems, coding agents often trap users in a constant loop of incremental fixes and rewrites.

Monocod is designed to break that loop by ensuring that generated and maintained code aligns with real industry standards and system-level thinking, not just short-term feature completion.

Comments URL: https://news.ycombinator.com/item?id=47304359

Points: 1

# Comments: 0

Article URL: https://github.com/ttlequals0/MinusPod

Comments URL: https://news.ycombinator.com/item?id=47304345

Points: 2

# Comments: 1

Article URL: https://noreturn.blog/p/the-rise-of-the-techno-pastoral

Comments URL: https://news.ycombinator.com/item?id=47304340

Points: 1

# Comments: 0

Here are hints and the answers for the NYT Connections: Sports Edition puzzle for March 9, No. 532.

Article URL: https://webmars.nfiles.top/

Comments URL: https://news.ycombinator.com/item?id=47304310

Points: 2

# Comments: 1

Article URL: https://bl0v3.com/Blog/raymarching-in-dyalog-apl/

Comments URL: https://news.ycombinator.com/item?id=47304300

Points: 1

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Article URL: http://www.mapeditor.org/

Comments URL: https://news.ycombinator.com/item?id=47304291

Points: 1

# Comments: 0

Article URL: https://github.com/m0at/hermes-lite

Comments URL: https://news.ycombinator.com/item?id=47304267

Points: 1

# Comments: 1

Here are the answers for The New York Times Mini Crossword for March 9.

Article URL: https://japan-dev.com/blog/work-life-balance-in-the-japanese-tech-industry

Comments URL: https://news.ycombinator.com/item?id=47304261

Points: 1

# Comments: 0