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Curl removes bug bounties because of AI slop

2026-01-21 @ 06:07:03Points: 72Comments: 10

Libbbf: Bound Book Format, A high-performance container for comics and manga

2026-01-21 @ 04:27:08Points: 37Comments: 11

Disaster planning for regular folks (2015)

2026-01-21 @ 03:38:57Points: 95Comments: 56

Anthropic's original take home assignment open sourced

2026-01-21 @ 02:54:32Points: 183Comments: 67

Who owns Rudolph's nose?

2026-01-21 @ 00:21:13Points: 32Comments: 14

California is free of drought for the first time in 25 years

2026-01-20 @ 22:39:26Points: 343Comments: 173

Lunar Radio Telescope to Unlock Cosmic Mysteries

2026-01-20 @ 22:36:23Points: 36Comments: 2

Provably unmasking malicious behavior through execution traces

2026-01-20 @ 22:18:53Points: 37Comments: 5

Which AI Lies Best? A game theory classic designed by John Nash

2026-01-20 @ 22:09:49Points: 102Comments: 49

The challenges of soft delete

2026-01-20 @ 21:36:34Points: 129Comments: 76

Show HN: Agent Skills Leaderboard

2026-01-20 @ 21:22:19Points: 69Comments: 25

Our approach to age prediction

2026-01-20 @ 19:34:48Points: 87Comments: 157

Instabridge has acquired Nova Launcher

2026-01-20 @ 19:06:56Points: 179Comments: 116

IPv6 is not insecure because it lacks a NAT

2026-01-20 @ 19:03:38Points: 125Comments: 178

Maintenance: Of Everything, Part One

2026-01-20 @ 19:01:30Points: 97Comments: 18

A 26,000-year astronomical monument hidden in plain sight (2019)

2026-01-20 @ 18:16:09Points: 441Comments: 90

The Unix Pipe Card Game

2026-01-20 @ 16:48:59Points: 208Comments: 66

Show HN: Mastra 1.0, open-source JavaScript agent framework from the Gatsby devs

2026-01-20 @ 16:38:56Points: 146Comments: 48

Almost a year ago, we first shared Mastra here (https://news.ycombinator.com/item?id=43103073). It’s kind of fun looking back since we were only a few months into building at the time. The HN community gave a lot of enthusiasm and some helpful feedback.

Today, we released Mastra 1.0 in stable, so we wanted to come back and talk about what’s changed.

If you’re new to Mastra, it's an open-source TypeScript agent framework that also lets you create multi-agent workflows, run evals, inspect in a local studio, and emit observability.

Since our last post, Mastra has grown to over 300k weekly npm downloads and 19.4k GitHub stars. It’s now Apache 2.0 licensed and runs in prod at companies like Replit, PayPal, and Sanity.

Agent development is changing quickly, so we’ve added a lot since February:

- Native model routing: You can access 600+ models from 40+ providers by specifying a model string (e.g., `openai/gpt-5.2-codex`) with TS autocomplete and fallbacks.

- Guardrails: Low-latency input and output processors for prompt injection detection, PII redaction, and content moderation. The tricky thing here was the low-latency part.

- Scorers: An async eval primitive for grading agent outputs. Users were asking how they should do evals. We wanted to make it easy to attach to Mastra agents, runnable in Mastra studio, and save results in Mastra storage.

- Plus a few other features like AI tracing (per-call costing for Langfuse, Braintrust, etc), memory processors, a `.network()` method that turns any agent into a routing agent, and server adapters to integrate Mastra within an existing Express/Hono server.

(That last one took a bit of time, we went down the ESM/CJS bundling rabbithole, ran into lots of monorepo issues, and ultimately opted for a more explicit approach.)

Anyway, we'd love for you to try Mastra out and let us know what you think. You can get started with `npm create mastra@latest`.

We'll be around and happy to answer any questions!

Show HN: TopicRadar – Track trending topics across HN, GitHub, ArXiv, and more

2026-01-20 @ 14:47:50Points: 27Comments: 7

https://apify.com/mick-johnson/topic-radar

What it does: - Aggregates from HackerNews, GitHub, arXiv, StackOverflow, Lobste.rs, Papers with Code, and Semantic Scholar - One-click presets: "Trending: AI & ML", "Trending: Startups", "Trending: Developer Tools" - Or track custom topics (e.g., "rust async", "transformer models") - Gets 150-175 results in under 5 minutes

Built for the Apify $1M Challenge. It's free to try – just hit "Try for free" and use the default "AI & ML" preset.

Would love feedback on what sources to add next or features you'd find useful!

Unconventional PostgreSQL Optimizations

2026-01-20 @ 14:23:44Points: 321Comments: 47

IP Addresses Through 2025

2026-01-20 @ 13:51:03Points: 172Comments: 132

Ask HN: Do you have any evidence that agentic coding works?

2026-01-20 @ 12:45:57Points: 184Comments: 174

Is there real evidence, beyond hype, that agentic coding produces net-positive results? If any of you have actually got it to work, could you share (in detail) how you did it?

By "getting it to work" I mean: * creating more value than technical debt, and * producing code that’s structurally sound enough for someone responsible for the architecture to sign off on.

Lately I’ve seen a push toward minimal or nonexistent code review, with the claim that we should move from “validating architecture” to “validating behavior.” In practice, this seems to mean: don’t look at the code; if tests and CI pass, ship it. I can’t see how this holds up long-term. My expectation is that you end up with "spaghetti" code that works on the happy path but accumulates subtle, hard-to-debug failures over time.

When I tried using Codex on my existing codebases, with or without guardrails, half of my time went into fixing the subtle mistakes it made or the duplication it introduced.

Last weekend I tried building an iOS app for pet feeding reminders from scratch. I instructed Codex to research and propose an architectural blueprint for SwiftUI first. Then, I worked with it to write a spec describing what should be implemented and how.

The first implementation pass was surprisingly good, although it had a number of bugs. Things went downhill fast, however. I spent the rest of my weekend getting Codex to make things work, fix bugs without introducing new ones, and research best practices instead of making stuff up. Although I made it record new guidelines and guardrails as I found them, things didn't improve. In the end I just gave up.

I personally can't accept shipping unreviewed code. It feels wrong. The product has to work, but the code must also be high-quality.

Building Robust Helm Charts

2026-01-19 @ 09:19:45Points: 58Comments: 2

Are arrays functions?

2026-01-19 @ 06:30:49Points: 107Comments: 63

The life of a playboy publisher who shaped 20th-century literature

2026-01-18 @ 00:41:51Points: 12Comments: 2

Apples, Trees, and Quasimodes

2026-01-17 @ 16:44:45Points: 41Comments: 2

Show HN: I built a tool to assist AI agents to know when a PR is good to go

2026-01-17 @ 09:55:56Points: 41Comments: 32

It would poll CI in loops. Miss actionable comments buried among 15 CodeRabbit suggestions. Or declare victory while threads were still unresolved.

The core problem: no deterministic way for an agent to know a PR is ready to merge.

So I built gtg (Good To Go). One command, one answer:

$ gtg 123 OK PR #123: READY CI: success (5/5 passed) Threads: 3/3 resolved

It aggregates CI status, classifies review comments (actionable vs. noise), and tracks thread resolution. Returns JSON for agents or human-readable text.

The comment classification is the interesting part — it understands CodeRabbit severity markers, Greptile patterns, Claude's blocking/approval language. "Critical: SQL injection" gets flagged; "Nice refactor!" doesn't.

MIT licensed, pure Python. I use this daily in a larger agent orchestration system — would love feedback from others building similar workflows.

Fast Concordance: Instant concordance on a corpus of >1,200 books

2026-01-16 @ 21:37:51Points: 44Comments: 4

The GDB JIT Interface

2026-01-16 @ 15:27:46Points: 23Comments: 3

Proof of Concept to Test Humanoid Robots

2026-01-15 @ 21:07:30Points: 11Comments: 9

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