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Learn everything you need to know about Hackernoon Community via these 186 free HackerNoon blog posts.

The seven-touch sales sequence is outdated. Modern sales require context, buyer intent, and timing, not rigid follow-up cadences.

The RWA endpoints resolve each asset through a stable identifier and span the full data lifecycle. An ID map and a metadata endpoint

When I built one of my early products, I obsessed over making it perfect. Every animation was smooth. Every button looked great. The code was clean. The only problem? Nobody actually needed it. I confused building with making progress. That mistake taught me more than any successful launch ever could. Here are the lessons I wish someone had told me. Lesson 1: Validate before you build An idea isn't validated because your friends say it's cool. Talk to the people who would a...

If you're building a chess app on React Native and couldn't find the right board, we built one chessboard-native Fully controlled and declarative Full parity with react-chessboard Optimized animations & native gestures Expo, iOS and Android Repo link in the comments

I’m building a distribution product for solo founders/builders that takes care of what happens after shipping: working out who to sell to, where to find them and what to say. But I keep getting stuck on the free trial question. Should I have one at all? (Probably yes. I never use anything without a free trial.) And if I do, should it be 7, 14 or 30 days? As a new-to-market product, I think it’s very tough to ask people to take a chance on you when they have nothing to go on. Getting people to ...

I have built two substantial software platforms with the intention of them being self serving / subscription based. A large consultancy may be interested in a dedicated version or acquisition and I need independent support with technical due diligence, IP separation, commercial structure and handover planning etc. I could also do with support from someone experienced in valuing B2B software, both an existing software asset and a bespoke enterprise platform, so I can approach licensing, acquis...

We've been finding a lot of useful product feedback in our production traces, and it made me realise we hardly ever look there on purpose. The weird thing about AI features, IMO, is that users tell you exactly what they're trying to do. They tend to explain what they expected, what confused them and where things went wrong. And sometimes they add a few curse words in there to spice things up haha. I really think it’s great product feedback as much as it's debugging information. The problem is...

Anyone like C++'s module features? Feel free to try MCPP and talk with me. Comments URL: https://news.ycombinator.com/item?id=49217761 Points: 5 # Comments: 0

Article URL: https://discourse.nixos.org/t/the-nixpkgs-core-team-has-disbanded/79413 Comments URL: https://news.ycombinator.com/item?id=49217993 Points: 162 # Comments: 66

Article URL: https://www.space.com/space-exploration/voyager/nasa-figured-out-how-to-keep-its-48-year-old-voyager-2-probe-running-for-yet-another-year Comments URL: https://news.ycombinator.com/item?id=49218179 Points: 71 # Comments: 12

Article URL: https://web.archive.org/web/20260731053721/http://github.com/ancaferro/myNetwork/pull/3 Comments URL: https://news.ycombinator.com/item?id=49218707 Points: 4 # Comments: 0

Context: I've been building a system where the AI doesn't reset. It keeps a permanent memory of your conversations, and it trains a small per-user adapter that compounds — every day it's slightly more specifically tuned to you than it was yesterday. The adapter is yours and exportable. The technical part I expected to be hard was the memory retrieval. It wasn't really. The genuinely hard part was deciding what it should be allowed to forget, because a system that remembers *everything* you said ...

I am extremely anti AI. I think it’s incredibly dangerous and being built by the most irresponsible people and companies on earth. I am also keenly aware of its progress. Somewhere around mid- to late-2025, AI surpassed me, personally, on virtually all tasks. There is pretty much no longer anything I can do better than the latest models, even given significant prep time. AI is genuinely better at nearly every non-embodied task than virtually every human alive at the present moment. The few excep...

I’m working on a software-agent system and keep coming back to one design question: **Should the model/provider that performs an action be allowed to be the final authority on whether the action succeeded?** My current answer is “no,” at least for meaningful software work. I’m building Flows around a chain where execution, checks, repair, and evidence are separate concepts. Oort is the canonical library/provider layer underneath it. https://flows.oortstack.com https://oortstack.com ...

I’m not asking which one is better overall. I’m specifically curious about how people split implementation and code review between Codex and Claude. Right now, I usually use Codex for implementation because the token/cost limits feel more practical for larger coding tasks comapred to Claude ridiculous token limit, then I use Claude to review the code, look for bugs, logic issues, missed edge cases, or possible improvements. But sometimes Codex seriously impresses me with the issues it catche...

It took long enough, but now LA rapper Fenix Flexin appears to have admitted using AI for the 80s synth pop-themed song "Rubberz." His comments follow the producer Medasin's videos claiming that an AI tool called Treblo (formerly Sonauto) was used to make the song, and the company releasing an AI detector that identifies it […]

Restart, a games media website launched in late 2024 that was sponsored by Walmart, has laid off its "entire editorial team," according to a Friday post from Brandy Berthelson, the site's former editor-in-chief. Other staffers have also posted about being laid off. Restart is operated by Moonrock, a content marketing agency, though its editorial mission […]

Researchers found common points of failure, like software used to organize and display web content, could have allowed hackers to run riot through government websites.

The Movinkpad 11 a versatile little graphics tablet that can help make your wildest digital art dreams come true.

After its own AI usage wake-up call, Rippling this week unveiled AI Spend Console, a product that tracks individual and team employee AI spending.

OpenAI said it has suspended work on some aspects of its upcoming model Astra over concerns about its cybersecurity prowess.

An AI feature that nobody uses is not free. It has three separate cost lines, only one of which stops when usage does, and the largest of the three is usually the one that is never written down. Here is how to total them with your own numbers, and what could have been known before the build started. Three cost lines, not one The usual accounting for an unadopted feature is engineering time, treated as sunk and therefore ignored. That undercounts badly, because two of the three li...

A feature store exists because the same feature gets computed twice — once in a batch job for training and once in a service for scoring — and the two definitions drift apart. This page shows one feature breaking, in eight lines, and the join that stops it. One feature, two definitions The feature is avg_order_value_30d . It appears in a fraud model. The training set is built in the warehouse: -- training pipeline, run nightly over history SELECT o . order_id ,...

Federated learning trains a shared model across many devices without collecting their data on a server. That is a real and useful property. It is also routinely stated as though it were three properties, and the other two — that the server learns nothing about individuals, and that the resulting model cannot leak training data — are not true unless you add machinery that costs something. The protocol, step by step The canonical algorithm is federated averaging. One round looks li...

Short answer: don't choose an LLM API for a SaaS app from a public token-price table alone; replay a representative eval set through direct OpenAI, direct Claude API, and an OpenRouter-style routing path, then choose the smallest integration whose measured quality, billed usage, retry behavior, and recovery policy meet your release constraint. The cheapest path is workload-dependent. A low input rate can hide engineering overhead, while a chatty agent can turn one user action into several mod...

“How many examples” is two questions wearing one coat. The cost of another example is arithmetic you can do exactly. The benefit depends on what you believe examples are for — and the published evidence on that is more surprising than the advice built on it. The cost side, exactly Examples are input tokens on every single call, forever. Take a classification prompt whose examples run about 180 tokens each (input plus label plus the delimiters around them): shots prompt ...

Add WHERE tenant_id = 42 to a working vector query and one of two things happens: it gets slow, or it returns fewer rows than you asked for. Both are the same underlying fact — an approximate index and a filter cannot be applied at the same time — and the selectivity at which it becomes fatal is calculable in advance. Why the two do not compose A B-tree index and a GIN index can be combined: Postgres builds a bitmap from each and ANDs them. An HNSW index cannot participate in t...

Fine-tuning an embedding model is unusually cheap — a base model of a hundred million parameters, fifty thousand pairs and an hour on one GPU. What is not cheap is everything that happens after: a fine-tuned model is a new model, and every vector you have stored becomes incompatible on the day you deploy it. When this is worth doing Fine-tuning pays when your domain’s notion of relevance differs from the general one the base model learned. Concretely: your users search with vocab...

Almost every fine-tuning cost estimate is a GPU-hour calculation, and the GPU hours are usually the smallest of the four terms. This page is deliberately parametric: prices in this field move faster than a page can be revised, so what is offered here is the structure and the derivations, with every figure marked as an assumption you replace. The four terms ONE-OFF, per attempt (and you will make more than one attempt) 1. data curation hours, labelling, or teacher ge...