Ask stories

What are you working on? Any new ideas that you're thinking about?

I've often been in the market for new software engineer opportunities and have found some untraditional ways of finding new jobs. But with so many job search tools, AI and ATS matching I'm curious what job search strategies are working for you today? Also, what has been a waste of time?

Ask HN,

I’m a software engineer and founder. Over the years, I’ve built backend and cloud systems and created a few internal tools to address recurring operational issues.

Before spending time building anything new, I’m trying to understand what problems are actually common today.

So I’m curious: what’s a process in your business that still costs you time every week and shouldn’t? For example: something manual, spreadsheet-heavy, or a tool you tried and abandoned.

If you’re comfortable sharing publicly, I’d appreciate hearing about it. Thanks.

Hop on an international flight, remember you had set automatic downloads for your favorite podcast show. Open the app to find the latest (or even last few) episodes are not downloaded. Why is it so hard to auto download podcasts when the phone is charging at night and connected to a WiFi? What’s the point of auto-download button?

Previously it has been using Akamai

Recently built something where simple domain-specific heuristics crushed a fancy ML approach I assumed would win. This has me thinking about how often we reach for complex tools when simpler ones would work better. Occam's razor moments.

Anyone have similar stories? Curious about cases where knowing your domain beat throwing compute at the problem.

Hey HN,

We originally were building vertical voice agents for fitness centers. During customer conversations, the idea of collecting payment during the call (via SMS link, keypad, or voice) would sometimes come up as something that might be useful.

We’re trying to understand how people have approached this in practice.

If you’ve worked on production voice systems or payments, I had a few questions: 1) Have you implemented in-call payment flows? 2) What tradeoffs or issues did you run into (compliance, reliability, etc.)? 3) Was it something customers actually used, or mostly ignored?

We also noticed a YC F24 company (Protegee) explored this space and later pivoted, which makes us curious what lessons people took away from that generation of attempts.

Appreciate any real-world experience or pointers. We’re trying to learn from folks who’ve actually shipped this.

Are you coding more or less, managing people differently, or making decisions in new ways because of AI tools? Which tools (LLMs, copilots, internal agents, analytics, etc.) have meaningfully stuck, and which turned out to be hype? I’m especially interested in concrete changes to how you plan, review work, and support teams.

I have been mostly anti AI. I did experiment a bit with aider and free models, but my results were inconsistent, and nothing to worry about.

However, recently I have purchased the max plan from anthropic and have been vibing with Claude code since then. And wow, the results are very good. With a good enough prompt, and planning step, it could generate full features in a project with 20k LOC, with very little modifications needed by me after review.

I heard even more success stories from friends who gave Claude 3-4 different features that Claude would develop in parallel.

On top of that, everyone seems to produce side project at an astronomical rate, both among my friends, and here on HN where fully complete project that would take months to develop, seem to appear after few hours with Claude code.

So, my questions is, is programming as a profession cooked? Are most of us going to be replaced with a “supervisor” who runs coding agents all day?

Just got laid off from a chill swe job. It was remote. F. What is the quickest way to get a chill remote job where I have responsibilities and autonomy?

5YOE in JS Fullstack/ Python. SF. On student visa.

First off, this thread is NOT a petition to rally against the moderation team. Considering the deluge of trash they deal with every day, I think they are doing a valiant job and are to be commended. Consider it merely a place to discuss, which is what HN does best.

That said, it's becoming more and more obvious every day that there is a tremendous amount of attempts by bots, and specifically AI agents, to inject slop into HN threads. I worry about the integrity of the discourse here and if the ever growing wave of garbage will overtake staff resources to deal with it. Is it time to implement captcha for HN? If so, should it be out of the box, or a new mechanism more tailored to the security and privacy-centric nature of the HN readership? Are captchas even still effective enough in the age of AI to warrant their use?

Context for the uninitiated or younger HN audience:

Aaron Swartz was a programmer and an internet freedom activist. He co-authored the RSS spec at age 14, and helped build Reddit, Creative Commons, Markdown syntax, Open Library, and more. But he was much more than the sum of his outstanding code contributions. He believed public information hidden behind unreasonable paywalls should be free, and fought to make it actually public.

In 2008, he wrote a script to download millions of federal court documents from the government's paywalled PACER database. In due time, he was caught by federal authorities, but the case was closed without filing charges. Aaron had violated the terms of service, but he had not broken the law as the documents were public property. The cache is now permanently hosted on the Internet Archive.

In late 2010, he started running a script to download the JSTOR archive, a digital library that locks millions of academic journals, papers, books, and primary sources behind expensive paywalls. JSTOR caught on, and started firewalling him. Aaron bypassed the firewalls by entering an unlocked utility closet in the basement of MIT's Building 16 and connected his laptop to the network switch, hiding it under a cardboard box. This did not end well.

MIT and JSTOR found the laptop and contacted the authorities, who turned this into a federal sting operation, and used a camera to catch Aaron in the act. Federal prosecutors and U.S. attorneys tried to make an example out of him. Instead of a simple trespass or civil suit, they charged him with multiple felonies including CFAA and wire fraud, threatening him with 35 years in prison and $1 million in fines (comparable to sentences for manslaughter, bank robbery, and worse crimes). Aaron rejected a plea deal that would brand him a felon.

After three years, Aaron was still facing trial and the full weight of the federal government. On January 11, 2013, he took his life. He was 26 years old.

Today, we pay tribute to a pioneering builder and thinker of the open web.

Some links:

Aaron's manifesto on freeing academic knowledge: https://ia600101.us.archive.org/1/items/GuerillaOpenAccessManifesto/Goamjuly2008.pdf

Aaron's weblogs: https://github.com/joshleitzel/rawthought/tree/master

An excellent documentary on Aaron Swartz: https://archive.org/details/TheInternetsOwnBoyTheStoryOfAaronSwartz

Aaron’s keynote “How we stopped SOPA”: https://www.youtube.com/watch?v=Fgh2dFngFsg

16 year old Aaron speaking at the launch of Creative Commons: https://www.youtube.com/watch?v=YpT_V-DB1JU

We’ve all seen the crazy “10 parallel agents” type setups, but I never saw it fitting my workflow.

What I usually do is I would have Claude Code build a plan, Codex find flaws in it, iterating until i get something that looks good. I’d give direction and make sure it follows my overall idea.

Implementation is working well on its own.

But this takes a lot of focus to get right for me, I can’t see myself doing it on the same project, multiple features.

Am I missing something?

The best phone in 2026 is a dying iPhone 12 mini. It’s the smallest smartphone still maintained by a major manufacturer (both software updates and repair parts), runs all apps securely & as designed, costs ~$150 with accessories available for dirt cheap (my favorite sleeve officially made by Apple [1] cost $129 on release but is now available for around $10). A dying battery makes the phone better - it forces you use the phone less and only when you really need it. Don’t replace your battery, just turn the phone off and you’ll feel immediately less stressed. If you don’t want to miss calls, get an old Apple Watch with cellular and use it as your main “phone”. Buy a dying iPhone mini to save the planet and yourself, and maybe if Apple sees enough active minis they will make another one...

[1]: https://apple.fandom.com/wiki/IPhone_12_Leather_Sleeve_with_MagSafe

I'm researching demand for an end-to-end encrypted social platform focused on private groups (family/friends) rather than public feeds.

Core thesis: "They don't own you" is becoming a movement. People want: - E2E encryption (platform can't read content) - True deletion (cryptographic, not just "marked as deleted") - Subscription model (no ads, no data mining) - Open source (verifiable claims)

The gap: Signal is for messaging, Discord isn't private, Facebook is surveillance capitalism. Nothing serves the "private social groups" use case with real privacy.

Before building, I need to validate if this is a real pain point or just something that sounds nice but nobody would actually switch for.

2-min anonymous survey: https://forms.gle/bfZYPfxMUBCc1iACA

Honest feedback appreciated—especially if the answer is "this wouldn't work because X."

Hey guys,

I've come all the way to SF to build a startup. But honestly doesn't feel like much has changed. Is there anything I need to do in order to leverage SF better? Or does being in SF doesn't really matter that much?

Is it just me or do you guys think Datadog pricing is crazy? I mean even to SEE APM you have to pay like $50/mo minimum. What if my app has just 10 requests per month, can I get for free? No, pay us. What if it's just me building? No, still pay us.

But hey we'll give you this metrics page for free which just basically tells you your RAM usage.

And the worst part is, there is no proper alternative for this. And people are ok with that too. Am I crazy for thinking this?

## My Implementation

I'm using a 64-bit layout:

- Bits 63-51: Quiet NaN signature (0x7FFC...)

- Bits 50-18: 32-bit payload (integers, string pool indices, etc.)

- Bits 17-3: Unused/ (15 bits)

- Bits 2-0: 3-bit type tag

So it allows me to have 5 tagged types: `TRUE_VAL`, `FALSE_VAL`, `STRING_VAL`, `CALLDATA_VAL`, `U32_VAL`

This is for a domain-specific VM I'm building for programmable task management (think "Vim for todo apps" - small core with scriptable behaviors). The VM is stack-based with:

- String pooling & instructions pooling (indices stored as NaN-boxed values) - Call stack for task instructions execution.

code is here : https://github.com/tracyspacy/spacydo/blob/main/src/values.rs

Looking for recommendations for sites similar to Downdetector

for more context, my primary language is javascript, but lately i started learning Golang,in the past i only use normal hosting providers to host my nodejs apps

Dear Americans, please don’t take this the wrong way - I love the US, have friends there, and treasure memories I made there.

However, it seems plausible that the US is turning into a rogue, authoritarian, Russia-like state increasingly more friendly towards Russia and hostile towards Europe. I am a European who grew up in a country still occupied by Russia. I am increasingly more worried about building my projects on American platforms, using an American operating system, etc.

What if the US actually attacks Greenland or finds another way to be openly hostile to Europe? I am not saying it will happen. All I am saying is that it seems prudent to prepare. How would you do it?

It is currently impossible to unhook myself from the US, but I would like to minimize exposure.

I can’t do anything about things like building an alternative to VISA/MasterCard (except wait for the digital Euro), so I will focus on things I can actually do and ignore things like my government buying F-35s and possibly giving my health data to Palantir.

* Mobile phone - there are no real European alternatives; it’s just Apple vs Google. Samsung or HTC with Android seems like a less bad option.

* Operating system - I have been using Linux for ages, getting rid of Windows seems relatively easy.

* Social networks - I grew to hate them before the current US admin, never used TikTok or Instagram, and I mostly stopped using Facebook and Twitter around the time Musk bought Twitter.

* Stripe for payments - this will be hard, but I am experimenting with our local payment processor, and so far it seems surprisingly doable, but it is not a battle-tested solution like Stripe.

* Clerk authentication - doable, but a lot of work and worrying

* AWS - I had a surprisingly bad experience with AWS and switched to a local provider with a lot less functionality (that I mostly do not need) and a lot better support

* GitHub, Cloudflare... dear God, how could we Europeans allow ourselves to be that dependent on anyone? Everything I touch is American.

* Gmail - this will be hard (two decades of emails). Any advice?

* Anything AI-related - fuuu, I am lost here.

What am I missing/forgetting? What do/would you do in my place?

I really hope you will take this as a brainstorming exercise and not an attack on America. I really do love the US and hope its democracy turns out to be more resilient than it currently seems.

EDIT: Please kindly keep responses practical. Let’s not turn this into a political discussion. You might approach it as a “what if” exercise, even if you think what the current US admin is doing is great, Europeans deserve what they get, etc.

Hi HN, sorry for using a burner account.

It seems to me that up until the beginning of the last year, we saw a couple of new "open" model release announcements almost every week. They'd set a new state of the art for what an enthusiast could run on their laptop or home server.

Meta, Deepseek, Mistral, Qwen, even Google etc. were publishing new models left and right. There were new formats, quantizations, inference engines etc. and most importantly - a lot of discourse and excitement around them.

Quietly and suddenly, this changed. After the release of gpt-oss (August 2025), the discourse has been heavily dominated around hosted models now. I don't think I've seen any mention of Ollama in any discussion that reached HN's front page in the last 6 months.

What gives? Is this a proxy signal that we've hit a barrier in LLM efficiency?

Not only is 3.9 reached end-of-life, the last release was 3.9.25

% python3 Python 3.9.6 (default, Dec 2 2025, 07:27:58) [Clang 17.0.0 (clang-1700.6.3.2)] on darwin

I’m researching patterns for edge / gateway telemetry where the network is unreliable (remote sites, industrial, fleets, etc.) and you need offline buffering + bounded disk + replay once connectivity returns.

Questions for folks running this in production:

What do you use today? (MQTT broker + ??, Kafka/Redpanda/NATS, Redis Streams, custom log files, embedded DB, etc.)

Where do you buffer during outages: append-only log, SQLite/RocksDB, queue-on-disk, something else?

How do you handle backpressure when disk is near full? (drop policy, compression, sampling, prioritization)

What’s your failure nightmare: corruption, replay storms, duplicates, “stuck” consumer offsets, disk-full, clock skew?

What guarantees do you actually need: zero-loss vs “best effort” (and where do you draw that line)?

What metrics/alerts matter most on gateways? (queue depth, replay rate, oldest event age, fsync latency, disk usage, etc.)

I’d love to learn what works, what breaks, and what you wish existing tools did better.

I have a decade of mixed experience: 10+ years in IT, 2 years on a professional motorsports team (Tony Kart, Ducati, Miata), and 4 years in software (refactoring old .NET to Spring Boot/Angular and some greenfield projects). I self-taught my way into dev and finished a CS degree while working.

I’m currently at a {big_slow_corp} and feeling the AI squeeze trying to switch jobs. My exp is not public facing so the “experience building scalable apps to disrupt the market” requirement I think is my weakness. I’ve also realized my heart isn’t in web frameworks. I’m the guy bored on a plane talking to his gf about flap software, throttle response, and suspension geometry like a kid showing a toy to his mom.

I want to move "closer to the metal", ECUs, controlling machinery, I’d love ML applied to machinery, even infotainments!, but my professional resume is strictly high-level. My tinkering experience includes building MegaSquirts and using ESP32s for signal filtering and logic, data loggers and wiring things you’d find in a race car, but I currently lack a project car to demonstrate new work.

How can I bridge the gap from Java/Angular to automotive software?

Does a decade of IT and 4 in backend experience carry weight in the "Software Defined Vehicle" world, or am I starting at zero?

What "proof of work" can I build to wow recruiters at places like Toyota Research or Tesla (any brand with US presence really) without a physical car to hack on?

I'm ready to pivot to where my passion actually is. Any advice is appreciated.

Everyone’s hyped about Claude Code, Nano Banana models, and how AI can now “build a game in 30 minutes for $ 20.”

If that’s true—why don’t we see a flood of ultra-low-cost, high-quality tower defense games (like Kingdom Rush) built with AI, raking in serious revenue?

After all:

Art? → Image generators + style locking. Code? → LLMs can scaffold Unity/Godot logic. Balancing? → Maybe RL or even manual tuning on a tiny scope. Audio? → AI voice + music tools exist.

And yet… the App Store isn’t overrun with polished, profitable Kingdom Rush–style games made by solo devs using AI. Why?

P.S. Yes, this post was AI-generated—my first attempt at market research before launching Kingdom Rush: Nano Banana Edition.

As the title implies I'm experiencing a lull.

I'm a software engineer in games and big tech for a combined 15 years. Coding is my biggest passion and I'll still do it when I retire.

However, a large part of me wants to get into an entirely different industry.

I've identified the reason to be how intellectually unstimulating coding has become (due to vibe coding).

The AI tools are incredible - but in terms of learning and self development, vibe coding as an education form lacks depth and the classic sense of mastery. I feel like I've learned 90% of everything there is to know about vibe coding. The last 10% is just marginal gains.

I live for the thrilling moments in software development - I was in the industry early enough to roll out software on our own server racks. As a game dev, I regularly implemented algorithms (such as path finding, physics integrations and rendering logic). I also got to work with Mixed Reality headsets and help define UX paradigms.

I feel like there's now a stigma around DIY coding - one should simply use an off-the-shelf solution or AI.

I get so much pleasure in doing deep work, but nowadays, any feature that takes more than 2 days to implement gets eyebrows raised.

Am I overthinking it?

If you or your organization are developing projects that advance amateur radio or digital communications, now’s a great time to apply for ARDC grant funding, with our next application deadline on February 1, 2026.

ARDC’s priority areas for funding reflect our broader vision and strategy for supporting experimentation, education, and open technology within the amateur radio and digital communications communities. We’re especially interested in projects that align with these three areas:

Research & Development (R&D): open hardware and software systems that enable learning and experimentation (e.g. SDRs, open codec technologies, new modulation techniques).

Space-Based Communications: projects that create or expand access to satellite communications for amateur radio (AR) and digital communications (DC), engaging communities in wireless experimentation (e.g. GEO or HEO programs, repurposed commercial satellites, space-based tools for learning).

Open Source Education: scalable, open educational materials and hands-on projects that make AR and DC more accessible, especially for new learners and clubs (e.g. curricula, videos).

While we welcome proposals across the full range of AR and DC, projects that align with these areas remain a priority in our grantmaking decisions.

Learn more about these priority areas at https://www.ardc.net/apply/priority-areas-for-funding/, and find information on eligibility and how to apply at https://www.ardc.net/apply/. For additional questions, contact giving@ardc.net.