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TXR: An Original, New Programming Language for Convenient Data Munging

https://www.nongnu.org/txr/
1•andsoitis•26s ago•0 comments

Meta's Muse Is Better at Surveilling Than Helping Me

https://www.wired.com/story/metas-muse-is-better-at-surveilling-than-helping-me/
1•sbulaev•2m ago•0 comments

OSS, security and Funding: libjpeg-turbo

2•ternaus•9m ago•2 comments

Grit your teeth and ship it

https://www.seangoedecke.com/grit-your-teeth-and-ship-it/
3•sph•11m ago•1 comments

GoldenEye 007 Native PC Port

https://jkdansereau.github.io/goldeneye-pc-port/
2•shscs911•11m ago•0 comments

Covert Caches: When Is a Cache, a Cache?

https://parallelprogrammer.substack.com/p/covert-caches
1•matt_d•22m ago•0 comments

Mini-AGI – dynamic continual learning model trained from scratch on 8GB VRAM

https://github.com/volotat/mini-AGI/
2•volotat•26m ago•1 comments

A build graph that rolls dice

https://fzakaria.com/2026/09/20/a-build-graph-that-rolls-dice
1•ghuntley•29m ago•0 comments

Hawking by Graham Farmelo review – the dark side of genius

https://www.theguardian.com/books/2026/sep/07/hawking-by-graham-farmelo-review-the-dark-side-of-g...
1•SLHamlet•32m ago•0 comments

Investment Seer: Agentic AI-Powered Stock and Crypto Analyst

https://investmentseer.com/
1•fooctrl•32m ago•0 comments

Ant Mill

https://simple.wikipedia.org/wiki/Ant_mill
2•red369•33m ago•0 comments

Heretic removes restrictions from language models

https://heretic-project.org/
3•Bluestein•34m ago•1 comments

Meslo-Font: Customized Version of Apple's Menlo Font

https://github.com/andreberg/Meslo-Font
2•vinhnx•34m ago•0 comments

The Docker API Ceiling: Why Portainer 3.0's New Capabilities Target Kubernetes

https://www.portainer.io/blog/the-docker-api-ceiling
2•gpi•37m ago•0 comments

AI chatbots give wrong answers to financial queries 'most of the time'

https://www.ft.com/content/c0cd359d-df84-4208-a789-ffa864b43666
15•1vuio0pswjnm7•40m ago•0 comments

Ask HN: Is provider KV caching sufficient for agent swarms and long run agents?

1•mhutchw•43m ago•0 comments

Knowledge Refresh for Production RAG

2•rajkumarsamra•43m ago•0 comments

Why Do We Need Human Mathematicians Anymore?

https://poshenloh.com/posts/20260919-math-ai
4•stikit•48m ago•1 comments

RBA Faces Key Rate Decision as Inflation Pressure Remains

https://coinmarketcap.com/community/post/379410260/
1•joeymabia1•48m ago•1 comments

Faked Images of Neurons in Major Journals

https://www.youtube.com/watch?v=4g_1_AWOVpI
1•landonxjames•49m ago•0 comments

What do you think of a Java-like language that compiles to native code?

https://github.com/ironwood-lang/ironwood
1•joas_coder•51m ago•2 comments

College Is Coming Apart After Successive, Overlapping Crises

https://www.theatlantic.com/ideas/2026/09/college-education-future-ai/688655/
5•ryan_j_naughton•53m ago•1 comments

The positive effect of walking on creative thinking

https://pubmed.ncbi.nlm.nih.gov/24749966/
4•the-mitr•59m ago•0 comments

The president wanted to unleash AI. Then came Anthropic

https://www.politico.com/news/magazine/2026/09/20/anthropic-white-house-ai-01085212
9•elorant•1h ago•0 comments

Show HN: Mahabharata Characters – 307 figures with gunas and decision primitives

https://huggingface.co/datasets/gnumanth/mahabharata-characters
3•init0•1h ago•1 comments

Show HN: Less Prompts, More Guardrails

https://yasyf.com/writing/less-prompts-more-guardrails/
1•yasyfm•1h ago•0 comments

Coding Machines

https://www.teamten.com/lawrence/writings/coding-machines/
1•xk3•1h ago•0 comments

Birdle Explorer

https://start.birdle.world/
1•totetsu•1h ago•1 comments

I Investigated Coinbase a Year Ago For Forbes. The Bigger Story Now Is Its Power

https://thesignalmemo.substack.com/p/coinbase-wants-the-power-of-a-bank
3•sindhya1•1h ago•0 comments

EA Safety

https://contraptions.venkateshrao.com/p/ea-safety
3•emersonmacro•1h ago•0 comments
Open in hackernews

Show HN: API Testing and Security with AI

https://qodex.ai/
8•siddhant_mohan•1y ago

Comments

anuragdt•1y ago
Generating tests is good, but how to handle the updating tests? Also how will you handle the flakiness and side effects of AI models?
siddhant_mohan•1y ago
We handles flakiness with retries, smart waits, and isolation, while side effects are avoided using clean setups, teardowns, and state-safe mocks. Each tests scenarios are independent of each other and can be configured in a way to have prerequisite to setup the system and the post callback to cleanup the system

About updating test scenarios, we map it with your github commits and when a new commits come, we use the diff to figure out if tests failing are because of a bug or because of a new feature.

kshitijzeoauto•1y ago
It claims to plug into your CI pipeline, detect what changed, and generate relevant test cases using LLMs.

As someone who’s struggled with stale or missing tests—especially in fast-moving codebases—I find this idea quite compelling. But I’m also curious about how it handles:

Contextual understanding across large codebases (e.g., multiple modules touched in a PR) Avoiding flaky or non-deterministic tests Matching team-specific coding styles or conventions