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An AI agent can take an action. An AI employee needs to know what happens next. Most AI agents look something like this: Think → Act → Observe → Repeat That's fine for short-lived tasks. But an AI employee needs to work across hours, days, and weeks. It needs to remember: What happened Who owns the work What is waiting What changed What should happen next When it should wake up When a human needs to approve something That's where graph engineering...

Your Free AI Server Will Fail Quietly. Five Gates to Make It Loud. The model can be innocent. The server cannot. Earlier this week I wrote a fail-closed checklist for AI-generated code. That list guards against the model writing something dangerous. This list guards against something duller: the server around it dying at 2 a.m. while the model stays online the whole time. Nobody sees that failure until a user does. The setup I am testing MonkeyCode for a small side build...

Free Tokens Are Not an SLO: An Ops Cost Drill for AI Batch Queues This week, two numbers trended: a harness at 100%, a model at 30%. For platform teams, a better pair is queue age and deadline slack. This article is a cost drill for the simplest AI batch path: free tokens, free server, non-negotiable deadline. Disclosure: This article was prepared as part of MonkeyCode's product outreach. MonkeyCode offers free model access and a free server option. That capacity is real. It is not an ...

Here is a test from a real, well run Node project: test ( ' server starts ' , async ( t ) => { const app = build () await app . listen ({ port : 0 }) t . assert . ok ( true , ' server started ' ) }) It reads fine in review. It runs green. Now delete the body of build() so the server never comes up. The test is still green, because the only thing it asserts is true . In the same file two more of these caught the...

Classic Machine Learning Through the Eyes of an SRE — Part 9: Isolation Forest The algorithm in one line: Isolation Forest scores how anomalous a point is by how few random cuts it takes to separate that point from everything else. No model of normal, no loss function, nothing optimized. ← Previous: Part 8 — Hierarchical Clustering Fails Beautifully · Next: this is the series finale — start at Part 1 . Every anomaly detector I had studied models what NORMAL looks like, then cal...

The review passed. The deployment failed. An engineer moved a code-review agent to a free server. The model answered correctly in every test. Then the server hit its quota at 2:47 PM on day three. Fourteen pull request verdicts vanished with the session. No state. No logs. No retry. This is the reviewer's blind spot. Teams test models obsessively. They rarely test the runtime underneath. This guide covers one decision: refusing a free server for an agent. It lists red flags, better alte...

A Windows 11 VM in Proxmox VE was showing nearly 100% memory usage in monitoring. Inside Windows Task Manager, however, actual memory usage was only around 30–50% . At first glance, that looks like a monitoring problem. It wasn't. The issue was in the VM configuration: the PVE Ballooning Device had been disabled , which meant Proxmox VE was not receiving the guest memory statistics needed to reflect the actual Windows memory state. I encountered this while monitoring a Proxmox...

Designing Systems That Contain Failure — CS Week Perú 2026 On August 13, 2026, I had the opportunity to speak at CS Week Perú 2026 , an event organized by IEEE Computer Society student chapters across Peru. My session was: “Isolation and Trust Boundaries in Production: Designing Systems That Contain Failure” The talk explored how production systems can be designed to limit the impact of failures through explicit trust boundaries, architectural invariants, and evidence-based valid...

I recently built and open-sourced Flaky HTTP , a small Java 11 library for deliberately making HTTP calls less reliable. That may sound like an unusual goal. Most of the time, we work hard to make HTTP calls reliable. We add retries, timeouts, circuit breakers, fallbacks, caches, and monitoring. But eventually we need to answer a more difficult question: How do we know any of that behavior actually works? The original idea was simple: wrap Java's standard HttpClient , add controlled...

If you've provisioned a VPC from a Terraform module without fully internalising what each piece is doing, that's fine — right up until something breaks. An instance that should be reachable isn't. A private instance can't pull a package update. And you're left checking five different resources with no clear mental model of how they connect. This post builds that mental model from the ground up. Not just definitions — the why behind each piece, so troubleshooting becomes deduction instead of...

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8/27/2026: Top 5 stories on the HackerNoon homepage!

Almost every baby-tracker app now has some kind of chat box bolted on. Ask it a question about your data, get a paragraph back.

Learn everything you need to know about Object Oriented Programming via these 58 free HackerNoon blog posts.

Langfuse and Helicone were acquired in 2026 while Opik and Phoenix stayed independent — here's what each acquirer actually promised in writing.

Why long-running coding agents keep rebuilding project context, and how persistent project state reduced cumulative input by 32–40% in controlled tests.

A hardware wallet maker can vanish overnight, but your crypto may still be safe. Discover why and learn the risks to avoid.

This week on “Uncanny Valley,” senior writer Will Knight talks his recent visit to China and the future of AI collaboration.

Grand Theft Auto VI is nigh. Here’s what the developer revealed about its highly anticipated game.

Article URL: https://www.tokyodev.com/articles/the-story-of-suica Comments URL: https://news.ycombinator.com/item?id=49466894 Points: 207 # Comments: 177

Article URL: https://calv.info/small-models-have-arrived Comments URL: https://news.ycombinator.com/item?id=49466917 Points: 517 # Comments: 236

Article URL: https://blog.google/innovation-and-ai/technology/developers-tools/build-with-gemini-omni-1-1-flash/ Comments URL: https://news.ycombinator.com/item?id=49467922 Points: 201 # Comments: 148

Article URL: https://blog.cloudflare.com/dns-cache-memory-optimization-1111/ Comments URL: https://news.ycombinator.com/item?id=49468083 Points: 589 # Comments: 169

Article URL: https://shop.m5stack.com/blogs/news/m5stack-launches-papermono-a-compact-e-ink-development-terminal-for-connected-projects Comments URL: https://news.ycombinator.com/item?id=49468593 Points: 101 # Comments: 42

Article URL: https://code.ffmpeg.org/FFmpeg/FFmpeg/issues/24290 Comments URL: https://news.ycombinator.com/item?id=49468642 Points: 193 # Comments: 152

I posted once before but wanted to share again because a lot has changed. There's now a fairly strong bot to play against (contributed by a community member) and also correspondence games. The combination of these things helps a bit in finding people to play against. Comments URL: https://news.ycombinator.com/item?id=49468816 Points: 100 # Comments: 13

Article URL: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5-transcribe/ Comments URL: https://news.ycombinator.com/item?id=49468818 Points: 178 # Comments: 50

Article URL: https://www.anthropic.com/news/model-hardware-standard-research-preview Comments URL: https://news.ycombinator.com/item?id=49468834 Points: 92 # Comments: 34

Hi HN, we built an open source model gateway. It's a single place to manage our own self hosted, frontier, and open source models in one place. It’s is rust native, built for concurrency, and implements all the config quirks across models and providers (streaming formats, tool calls, model parameters, rate limits, and different error behavior). The gateway adds under 1 ms for BYOK requests and under 2 ms when Experiential supplies the provider key. It has every major inference provider, and 1000...