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Pozsar's Bretton Woods III: Sometimes Money Can't Solve the Problem

https://philippdubach.com/2025/10/25/pozsars-bretton-woods-iii-the-framework-1/2/
2•7777777phil•2m ago•0 comments

Tokyo court orders Cloudflare to pay over $3.2M. over manga piracy sites

https://www3.nhk.or.jp/nhkworld/en/news/20251119_16/
1•gslin•3m ago•0 comments

Do Less

https://www.sunilshenoy.com/2025/11/19/do-less.html
1•speckx•8m ago•0 comments

Talk live with the guy who whispers "sales" to founders and startups

https://x.com/i/broadcasts/1kvJpMjqzXDxE
1•riley-i•11m ago•0 comments

Metabase 57 – Document Creation

https://www.metabase.com/releases/metabase-57
1•markwillis82•11m ago•0 comments

When grades stop meaning anything

https://www.theargumentmag.com/p/when-grades-stop-meaning-anything
2•paulpauper•11m ago•0 comments

How the Hell Are Porsches So Reliable?

https://www.jalopnik.com/how-the-hell-are-porsches-so-reliable-1709270257/
1•kerim-ca•11m ago•0 comments

Elasticity and microgrooves form aligned myotubes similar to slow twitch muscles

https://www.nature.com/articles/s41598-025-12744-7
1•PaulHoule•12m ago•0 comments

My Notes on Gemini 3

https://twitter.com/VictorTaelin/status/1990844923994886282
1•amrrs•14m ago•0 comments

Movim 0.32.1: A federated, open-source web-based social OMEMO E2EE XMPP client

https://github.com/movim/movim/releases/tag/v0.32.1
1•neustradamus•14m ago•0 comments

Datadog Is Down

https://status.datadoghq.com/incidents/cvdjtf81756n
3•markiannucci•19m ago•0 comments

DMA Collectives for Efficient ML Communication Offloads

https://arxiv.org/abs/2511.06605
1•matt_d•19m ago•0 comments

Taking prenatal supplements associated with 30% lower risk of autism

https://medicalxpress.com/news/2025-11-prenatal-supplements-autism.html
2•bikenaga•20m ago•0 comments

Calculated Risk: Trade Deficit Decreased to $59.6B in August

https://www.calculatedriskblog.com/2025/11/trade-deficit-decreased-to-596-billion.html
1•speckx•21m ago•0 comments

Our tools are failing us

https://blank.page/@mo/our-tools-are-failing-us
1•boudra•22m ago•1 comments

Pixar: The Early Days

https://stevejobsarchive.com/stories/pixar-early-days
2•tosh•22m ago•0 comments

Act-1: A Robot Foundation Model Trained on Zero Robot Data

https://www.sunday.ai/journal/no-robot-data
1•pr337h4m•22m ago•0 comments

Fine, Trade Labubu Futures

https://www.bloomberg.com/opinion/newsletters/2025-11-19/fine-trade-labubu-futures
2•ioblomov•24m ago•1 comments

Enumerating Three Billion WhatsApp Accounts for Security and Privacy

https://github.com/sbaresearch/whatsapp-census
2•filippofinke•25m ago•0 comments

Understanding neural networks through sparse circuits – OpenAI

https://openai.com/index/understanding-neural-networks-through-sparse-circuits/
1•JnBrymn•26m ago•0 comments

Gov. Abbott's office redacts pages of emails about Elon Musk

https://www.kut.org/politics/2025-11-19/texas-governor-abbott-elon-musk-emails-redacted
35•pavel_lishin•28m ago•5 comments

Nest Thermostats upload 50 megabytes to Google every day after being disabled [video]

https://www.youtube.com/watch?v=jC5wcJM8iuU
2•tartoran•30m ago•1 comments

Building with Distributed Actors: What and Why

https://withblue.ink/2025/11/19/distributed-actors-model.html
2•ItalyPaleAle•30m ago•0 comments

Europe wants to make space food out of thin air and astronaut pee

https://www.space.com/space-exploration/human-spaceflight/europe-wants-to-make-space-food-out-of-...
3•domofutu•31m ago•0 comments

What AI Is Really For

https://www.chrbutler.com/what-ai-is-really-for
4•delaugust•32m ago•0 comments

A simple UK self-employed tax calculator (instant monthly estimate)

https://selfemployedtaxcalculators.co.uk/
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Was MCP a mistake? The internet weighs in

https://www.aiengineering.report/p/was-mcp-a-mistake-the-internet-weighs
3•waprin•34m ago•0 comments

Chinese EV makers accelerate robotics drive for 'game-changing' edge over US

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4•Teever•35m ago•0 comments

Show HN: OpenHands Software Agent SDK

https://github.com/OpenHands/software-agent-sdk
1•rbren•37m ago•0 comments

Show HN: Allein - Markdown editor with AI autocompletion, completely offline

https://github.com/szilarddoro/allein
1•szdoro•38m ago•0 comments
Open in hackernews

What if your QA engineer never slept?

1•GTCHO•6mo ago
I've worked in startups and big tech. The most common bottleneck? QA. One team I know ditched the traditional approach and runs an agent that acts like an engineer, 24/7. It's synthetic, learns from bug history, and can gate PRs. Wild idea, or future standard?

Comments

duxup•6mo ago
I think you knowing someone who does this thing might be able to clue us into how well it works.
turtleyacht•6mo ago
QA receives whatever gets merged and (what they decide gets) deployed (to test); they cannot block PRs. It would be nice though to make some checks block merge, i.e. Required workflows.

Learning from bugs is amazing. Connect to production support tickets to link code changes to real incidents. When done manually by on-call, there is no other historical context.

Automate estimation with "this story reminds me of stories A, B, C, which were estimated to be X points and took Y days." A link lets folks drill down to code metrics, artifact version, etc.

A QA agent would be remarkable in that it has a complete and total timeline for everything, and can be queried in chat.

GTCHO•6mo ago
Completely agree. Linking incidents back to code changes is one of the most valuable things a team can do but it's rarely done well. In this case, the agent actually learns from that full timeline production incidents, support tickets, commit diffs. It surfaces patterns you’d never catch manually, like an issue that only appears under high concurrency.

Also yes on chat querying. One of the most useful parts was letting PMs ask questions like “Has this bug happened since April?” and getting a full trace across releases. The idea of automating grooming using historical story similarity is spot on too. This could easily save teams hours per sprint.

jakedlu•6mo ago
I think it's an interesting idea, especially if it's just running on production or staging and constantly just trying new flows/testing edge cases. I would be curious about (1) the quality of testing compared to an actual human and (2) the cost involved. Obviously compared to a human salary the cost could get quite high before it became an impediment (also depending on quality). But running an agent 24/7 seems like costs could certainly pile up.
GTCHO•6mo ago
Really good points. On quality it’s not replacing human insight, but it is exceptional at pattern recognition and coverage at scale. It catches edge cases that tend to get missed and never forgets past regressions. The best results I’ve seen come from pairing the agent with human QA. The agent does ambient monitoring and flags suspicious behavior. Humans then dig deeper.

Cost-wise, it’s surprisingly reasonable. The version I saw ran in containers that spun up based on commit activity or deploy frequency. So if no one is pushing code, it's idle. But during launches or busy dev cycles, it ramps up. Much cheaper than staffing a full team to maintain 24/7 vigilance.

ThrowawayR2•6mo ago
If your QA staff are no better than an "AI" agent, dump them and hire better QA staff.
GTCHO•6mo ago
I hear you and to be clear, this isn’t about replacing talented QA teams. It’s about offloading the repetitive and pattern-based parts of QA so human testers can focus on more strategic, exploratory, and usability-driven work.

In the case I saw, the agent handled things like regression patterns, diff analysis, and known-risk detection across thousands of past issues. The QA team actually became more valuable because they weren’t stuck rerunning the same test plan for the fifth time that week. It was augmentation, not replacement.

That said, I totally agree if a team is just rubber-stamping PRs, the issue isn’t automation, it’s expectations and leadership.