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I’m looking for examples of high-quality engineering blog posts—especially from tech company blogs, that go beyond surface-level explanations.

Specifically interested in posts that: 1. Explain technical concepts clearly and concisely 2. Show real implementation details, trade-offs, and failures 3. Are well-structured and readable 4. Tie engineering decisions back to business or product outcomes

Any standout blogs, posts, or platforms you regularly learn from?

A friend and I were talking about a DOS POS system we wrote decades ago. It was crude, handwritten using Turbo Pascal DBF files and somehow still running in a few places since it got pirated.

We no longer have the source. No install disks. No backups. The software survived longer than our memory of it.

It made me realize how often "temporary" work outlives its creators, while the source vanishes.

What’s the most important thing you lost because you assumed you’d back it up later? Code, data, research, art, configs, anything.

Did that loss permanently change how you handle backups?

I decided to ask this question because of a rather contrived informal discussion I'm involved in with colleagues from both academia and industry, neither of which are lawyers but who share a few concerns about how we can go about creating new "things" and intellectual property in an increasingly AI-centric world.

You can take prompts as "processes", or "embodiments" or any variation on intellectual property, but I'd love to know what people think about this--my particular concern was that if you ship your software as Open Source, could someone nitpick over your prompts and claim they were taken from their IP/software? How valid would this be given that prompts are, essentially language? How detailed does a prompt need to be to be complex intellectual property that describes a process? Can we consider it as code and an embodiment of a concept?

Discuss. And Happy Holidays!

Today is the worst day of my life. We live in a country near Cambodia, and as you know, it is kind of a dream land for scammers. Today, it happened to my family.

My mother received a call from a scammer. They told her she needed to process some tax issue and prove that her bank account had enough money. In just a few minutes, they tricked her and manipulated her into entering banking OTP codes. All of her savings are now gone.

What makes this more dramatic is that last year I architected and helped a government department in my country build a big system. This system can track money flows across the whole country, to know where money comes from. I was very proud of this. It is the biggest achievement of my life. Even if nobody knows I built it, that was fine.

But now I cannot protect my own mother. I cannot protect my family. My system can track the money, but it is almost impossible to get it back.

When I went to the police, just in one small area, there were more than 20 cases in a single day. A hardworking student sent all their family's money, thinking it was for university fees or going abroad. An old factory worker lost all her retirement savings. So many people lost everything. That is when I realized that the system I built, the system I was proud of, is not enough.

All my own savings are gone too. (My mother was scammed into borrowing a lot of money and sending it to the scammers, and now it is my responsibility.) I had plans for the next few years: to do open source work, to write books about math and programming, to create a dream Go web framework, to give back to the community. Now all of that is gone.

But this is not only about me. I can still start over. I am strong enough to rebuild my life. But who will protect people like my mother? Or a poor student? Or a factory worker? Or so many others?

I can build systems. I can build distributed systems that scale to a whole country. But for what? What should I do?

I have been reading Hacker News for 12 to 13 years, sometimes posting from other accounts. I am writing here now to ask for advice and help from this community.

If anyone has experience with similar cases, or ideas on what can realistically be done, or even advice on how to move forward after something like this, I would really appreciate it. I will keep this account semi-private, because with the details above, I think some engineers from my country may recognize me.

I spent the last week chasing a "ghost" in a RAG pipeline and I think I’ve found something that the industry is collectively ignoring.

We assume that if we generate an embedding and store it, the "memory" is stable. But I found that f32 distance calculations (the backbone of FAISS, Chroma, etc.) act as a "Forking Path."

If you run the exact same insertion sequence on an x86 server (AVX-512) and an ARM MacBook (NEON), the memory states diverge at the bit level. It’s not just "floating point noise" it’s a deterministic drift caused by FMA (Fused Multiply-Add) instruction differences.

I wrote a script to inspect the raw bits of a sentence-transformers vector across my M3 Max and a Xeon instance. Semantic similarity was 0.9999, but the raw storage was different

For a regulated AI agent (Finance/Healthcare), this is a nightmare. It means your audit trail is technically hallucinating depending on which server processed the query. You cannot have "Write Once, Run Anywhere" index portability.

The Fix (Going no_std) I got so frustrated that I bypassed the standard libraries and wrote a custom kernel (Valori) in Rust using Q16.16 Fixed-Point Arithmetic. By strictly enforcing integer associativity, I got 100% bit-identical snapshots across x86, ARM, and WASM.

Recall Loss: Negligible (99.8% Recall@10 vs standard f32).

Performance: < 500µs latency (comparable to unoptimized f32).

The Ask / Paper I’ve written a formal preprint analyzing this "Forking Path" problem and the Q16.16 proofs. I am currently trying to submit it to arXiv (Distributed Computing / cs.DC) but I'm stuck in the endorsement queue.

If you want to tear apart my Rust code: https://github.com/varshith-Git/Valori-Kernel

If you are an arXiv endorser for cs.DC (or cs.DB) and want to see the draft, I’d love to send it to you.

Am I the only one worried about building "reliable" agents on such shaky numerical foundations?

- HN errored on all authenticated requests with 502 Bad Gateway. It did still respond to a limited amount of unauthenticated requests with presumably cached pages, which did not get updated. The last post on /newest claimed "0 minutes ago", but was actually much older (1:32:57 PM GMT) and not the newest post.

- This status page actually identified the outage: https://hackernews.onlineornot.com/ - Pages by Hund and Statuspal did not show the outage.

- The last post before the outage was https://news.ycombinator.com/item?id=46301823 (1:39:59 PM GMT). The last comment was https://news.ycombinator.com/item?id=46301848 (1:41:54 PM GMT).

- There was an average of ~4 seconds per comment just prior to the outage. Based on this, HN likely went down at 1:41:58 PM GMT.

It's the time of the year again, so I'd be interested hear what new (and old) ideas have come up. Previously asked on:

2024 → https://news.ycombinator.com/item?id=42373343

2023 → https://news.ycombinator.com/item?id=38467691

2022 → https://news.ycombinator.com/item?id=34190421

2021 → https://news.ycombinator.com/item?id=29667095

2020 → https://news.ycombinator.com/item?id=24947167

2019 → https://news.ycombinator.com/item?id=20899863

2018 → https://news.ycombinator.com/item?id=17790306

2017 → https://news.ycombinator.com/item?id=15148804

Greetings,

I recently came accross this thread from a few years ago: https://news.ycombinator.com/item?id=34501352

I am interested, in particular, by the comment by vidarh, that starts with:

"You've been given the answer already: Simplicity. You keep ignoring it."

I find myself highly interested in what this person would have to say about rust. Is it better than, for example, oberon, or it's descendents?

I have heard that Rust is a big language. By that definition, a simpler one must be better, right? And yet rust is a big thing, and .. oberon is ..dusty?

I will keep on searching, and maybe attempt to contact him/her/(other?) directly.

I am a long time Apple user, but their software keeps getting buggier, worse and I just want to switch. I moved all my data to self hosting solutions, so I all I need now is an Android phone which… is fun? Like Framework Computer fun.

Are there still community based OSes out which I can flash onto a phone? Last time I had an Android phone was 2013.

I'm a teacher who started making my own productivity tools. I was tired of subscriptions and paywalls. Every tool is a single HTML file. Download it, open it, data stays local. No server, no login, no API calls.

Started as a personal project but I've now shipped habit trackers, journals, planners, invoice generators, and a bunch of teaching tools.

Curious what HN thinks about this approach to software.

This question generated some very interesting discussions in another online community I’m in. I would likely pursue a career in occupational therapy or speech-language pathology. I would love to do work that directly benefits the lives of others and to spend more time interacting with people from all walks.

What are your predictions for this coming year?

I’m moving my older posts from Substack to my personal blog and I want Google to treat my blog as the primary source going forward.

Constraints:

- Substack doesn’t support canonical URLs (so I can’t point Substack → my blog).

- I don’t want to use a custom domain on Substack.

- Going forward, I want Substack only as the newsletter, and my blog as the SEO winner.

I’ve seen the “ghost post” approach (replace most of the Substack post with a teaser + link), but I don’t want to delete/gut the original Substack content because I still want readers there to have the full post.

Is there any way or a hack to get this donee??

I’m looking for ideas to build and open-source.

Curious what problems you expect to matter in the next couple of years.

Thx!

I am not sure if this is part of the Bitnami Helm Chart Fiasco, but they seem to be changing open source projects from Apache to BSL.

Was looking at chart-syncer, and found: https://github.com/bitnami/charts-syncer/issues/307

And it depends on some tooling from VMware, which has the same notice: https://github.com/vmware-labs/distribution-tooling-for-helm/issues/132

Not that I'm surprised, just stumbled across this.

When working on my projects and talking to investors, I often hear: “Just post it on Hacker News or Reddit and show that people love it.”

What I find strange is that Hacker News feels oddly opaque. I’ve never met anyone who can clearly explain how it works in practice. Not just the rules, but the dynamics: what’s repeatable, what’s luck, and what actually matters.

By using the Kevin Bacon-number idea: I can usually get within three degrees of separation of well-known technologists like Linus Torvalds, but I can’t seem to get within three steps of someone who confidently understands how HN works.

So I’m asking sincerely: Does anyone here feel they understand Hacker News? If so, what are the real levers, and what do people consistently misunderstand?

PS: This question comes from a mix of genuine curiosity and personal frustration. I’m honestly trying to understand how HN works in practice.

I’m releasing *Framework Shells* (`fws`): a standalone Python package for orchestrating long-running background processes (“shells”) with *PTY*, *pipes*, and *dtach* backends.

This is meant for environments where you don’t want to stand up a full supervisor stack (or don’t have one): quick multi-service prototypes, dev environments, constrained userlands, etc.

### What it does

* Spawn/manage shells with:

  * **PTY**: interactive terminal sessions (resize, input, stream)
  * **Pipes**: stdin/stdout/stderr streams (good for daemons/LSPs)
  * **dtach**: persistent sessions you can attach/detach to (survives manager restarts)

### CLI quickstart

```bash # list shells fws list

# run a one-off shell (no spec) fws run --backend pty --label demo -- bash -l -i

# apply a YAML shellspec (recommended) fws up shells.yaml

# terminate shells fws down

# attach to a dtach-backed shell fws attach <shell_id>

# show managed shells + procfs descendants fws tree --depth 4 ```

### Shellspec example

```yaml version: "1" shells: worker: backend: proc cwd: ${ctx:PROJECT_ROOT} subgroups: ["worker", "project:${ctx:APP_ID}"] command: ["python", "-m", "your_module.worker", "--port", "${free_port}"] ```

### Isolation + security model (simple by default)

* `FRAMEWORK_SHELLS_SECRET` derives the `runtime_id` (namespace) and API tokens. * If the secret is set, mutating API endpoints require:

  * `Authorization: Bearer <token>` (or `X-Framework-Key`).

Hard limit: if two runtimes share the same OS user/UID, the OS may still allow signaling each other’s processes. The guarantee is: no cross-count/adopt/control *through the library’s control plane*.

### Real-world usage

I use this as the substrate of a full dev environment where “apps are shells” (terminals, IDE + LSP, agent/MCP, aria2 RPC, file explorer, llama.cpp runner, etc.). Repo:

```text https://github.com/mrsurge/termux-extensions-2 ```

### Feedback I want

* Does the secret/fingerprint/runtime isolation contract feel right? * Any obvious foot-guns in the default API/CLI? * Expectations vs systemd/supervisord/tmux/dtach: where would you use this?

github.com/mrsurge/framework-shells

pip install "framework-shells @ git+https://github.com/mrsurge/framework-shells@main"

```bash fws --help ```

I was thinking about this recently as a I work on a new mail client/server. I have one personal email that has a custom domain. 1 that's a plain gmail address and then a variety of random accounts I can't even remember but I guess were legacy or tests for new providers like protonmail. Then there's email address for whatever company you work for at the time. I realise I don't really want to hand out my personal email in a public setting and my company address is mostly for internal stuff. So where's public email?

Are we missing public email accounts? One's that you can just hand out anywhere?

I feel like reading HN sometimes there is the assumption that everyone who is a programmer by default works on web stuff (front end/back end).

I'm curious to hear about what other jobs/domains exist outside of this and how it is working on non-web stuff.

I have been noticing several issues with GitHub over the last few weeks, most of which used to work flawlessly a few months ago.

The outages aside, a couple of annoying, super-recent experiences:

- Our release process involves creating draft releases before QA, and publishing them when ready. We published a new release today and team members from the US were able to see it as published while members from different countries still saw the release marked as a draft and not visible publicly. We only noticed it two hours after making our announcements. We had to unpublish and publish it again to fix it.

- Recently, a colleague noticed a number of unrelated changes while reviewing a diff on GitHub, which led to us reverting a merge, only to later notice that the commit itself had no issues and it was the GitHub UI.

Outages and major issues are fine, they are loud and addressed directly. These kinds of issues go unnoticed, and they reduce trust silently.

I no longer trust the GitHub interface and actions. We had to re-test our release assets manually to make sure GH didn't mess that up.

Could this be yet another result of trusting AI code too much without proper review and testing? While discussing internally, one of my colleagues mentioned that "the whole internet feels fragile lately".

I'm curious to hear if anyone else has been facing such weird issues with GitHub.

I use Automator (mac os app) to do this, but it seems like such a dumb thing to do so regularly. If i transfer a photo on my iphone via google drive or some other cloud service, it inevitably needs to be changed to jpg.

It seems there are many solutions for social media these days, but only one LinkedIn. Why are we still putting up with it? I’m surprised there’s not been a contender yet, or maybe I am not aware and perhaps that could be the rub; the challenge of acquiring enough traffic for the network effect to take hold.

Hi!

I run a small custom software company in Michigan.

I want to get better at outbound sales beyond just cold emailing or messaging people through LinkedIn.

We’re about to start publishing case studies and doing some outreach, so I want to take some time to study outbound sales and improve my skills.

Any recommended courses, books, or frameworks for B2B outbound sales, consultative selling, or building effective outreach pipelines?

Thanks!

After finishing my PhD in earth sciences, I pivoted to software engineering. I’ve spent the last 8 years as a full-stack developer, gaining a decent grasp of various stacks and frameworks.

I’m now at a point where I want to merge my scientific background with my engineering experience. However, I’m finding a "missing middle" in the job market. I don't ever see a position that requires and values deep expertise in both.

I enjoy development, but I feel like my scientific training is going to waste. For those who have successfully merged these two paths:

Did you find a "unicorn" role, or did you create one within a company?

How do you market yourself when your two halves feel like they belong to different resumes?

We use Claude code internally and it does a good job generating first-pass system designs when given templates and existing architecture. It often captures the obvious components and tradeoffs quickly.

Even so, system design still seems slower than expected. People spend days aligning, gathering context, and iterating on designs that feel like they could have started much closer to a workable draft.

For those who already use AI tools while designing systems:

What parts of system design remain difficult or slow? Where do AI-generated designs tend to break down?

When Excel formulas get large, I often lose track of what’s actually happening.

I’m wondering whether representing formulas structurally (instead of plain text) could make them easier to read and modify, but I’m not sure if this really helps in practice.

How do you usually handle large formulas?

They first acknowledged Dec 19 15:06 UTC, and it's still broken as I write this. https://www.cloudflarestatus.com/