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Flamingo Compliance, iOS app to track tax residency days, visas, and US presence

https://flamingo.tax/
1•caroline_clrk•43s ago•1 comments

Engineering Leaders:We heard the feedback and are offering a lighter weight tool

https://www.vereda.ai/manager-mode
1•awightman•1m ago•1 comments

GitHub Copilot's effect on collaboration has stunned researchers

https://thenewstack.io/copilot-reshapes-developer-work/
1•CrankyBear•2m ago•0 comments

15.03. 1999 (27 years ago) ICQ chat where the name Counter-Strike was decided

https://old.reddit.com/r/pcgaming/comments/1ruaj61/1503_1999_27_years_ago_icq_chat_where_the_name/
1•mirzap•3m ago•0 comments

The Controversial AI Power Plant [video]

https://www.youtube.com/watch?v=KitUtjFllbg
1•johnnyApplePRNG•4m ago•0 comments

The quiet obsolescence of generosity, and a commercial alternative

https://malus.sh/blog.html
1•dTal•4m ago•0 comments

Never Trust the Science

https://adam.rochussen.xyz/p/never-trust-the-science
1•nradov•5m ago•0 comments

Two Crypto Bros Built a Real Estate Empire. Then the Homes Started to Fall Apart

https://www.wired.com/story/crypto-bros-built-a-real-estate-empire-then-the-homes-started-to-fall...
1•impish9208•8m ago•0 comments

Make your coding models create ADRs before implementation

https://github.com/Corbell-AI/Corbell
2•mercurialsolo•8m ago•0 comments

NumClass – a Python CLI classifying integers into 200 number-theory properties

https://github.com/c788630/Numclass
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Tell HN: A company was billed $128K from one leaked GCP API key

3•daudmalik06•9m ago•0 comments

ThunderKittens 2.0: Even Faster Kernels for Your GPUs

https://hazyresearch.stanford.edu/blog/2026-02-19-tk-2
1•PaulHoule•10m ago•0 comments

Emergence Isn't Real

https://pastebin.com/pjSKPzwD
1•ffwd•10m ago•2 comments

Modern admin panels feel overengineered

1•giuliopanda•11m ago•0 comments

Midwest Humble: A Wave Is Coming

https://midwesthumble.substack.com/p/a-wave-is-coming
1•rmason•11m ago•0 comments

We built a runtime security layer for AI agents (instead of prompt filtering)

https://github.com/AriKernel/arikernel
1•Arikernel•11m ago•1 comments

Magda – Open-Source DAW with Integrated AI (C++/JUCE/Tracktion Engine)

https://github.com/Conceptual-Machines/magda-core
1•nomamonad•13m ago•1 comments

Ask HN: Why is this a bad idea?

2•ZLStas•13m ago•1 comments

$100 Oil Could Deliver $63B Cash Surge to U.S. Shale – Oilprice.com

https://oilprice.com/Energy/Oil-Prices/100-Oil-Could-Deliver-63-Billion-Cash-Surge-to-US-Shale.html
1•bilsbie•13m ago•0 comments

Meta, TikTok let harmful content rise after evidence outrage drove engagement

https://www.bbc.com/news/articles/cqj9kgxqjwjo
2•1vuio0pswjnm7•14m ago•0 comments

The feeling that you're getting closer to what's right

https://www.patricioalbornoz.com/en/articles/two-leaps-into-the-unknown
1•patoalbornoz•14m ago•0 comments

Get Shit Done: A Meta-Prompting, Context Engineering and Spec-Driven Dev System

https://github.com/gsd-build/get-shit-done
2•stefankuehnel•15m ago•0 comments

How to Thought Lead

https://www.swyx.io/lead
2•AnhTho_FR•15m ago•0 comments

QSCS – A deterministic substrate for distributed systems (architecture update)

https://spooksystems.io/
1•danieljameslee•16m ago•1 comments

Check This Out

https://pinealguardianvip.com/ds/indexvs.php?aff=steffest19757306&cam=CAMPAIGN
1•fitenergywell•16m ago•0 comments

BMad Method: Breakthrough Method for Agile AI Driven Development

https://www.bmad-method.org/
1•stefankuehnel•16m ago•0 comments

World War Watcher–real-time infrastructure war dashboard (Next.js 16, Three.js)

https://worldwarwatcher.com
2•tamarru•17m ago•1 comments

Show HN: Middleware for translating between AI agent protocols

https://github.com/kwstx/engram_translator
1•kwstx•19m ago•1 comments

Aimploy – Agentic Professional Network

https://www.aimploy.co
1•Siddhartha29•21m ago•0 comments

DigitalOcean at Nvidia GTC 2026: Building the AI Factory for the Agentic Era

https://www.digitalocean.com/blog/building-ai-factory-for-agentic-era-nvidia-gtc
1•ky0ung•22m ago•1 comments
Open in hackernews

What if your QA engineer never slept?

1•GTCHO•10mo 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•10mo ago
I think you knowing someone who does this thing might be able to clue us into how well it works.
turtleyacht•10mo 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•10mo 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•10mo 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•10mo 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•10mo ago
If your QA staff are no better than an "AI" agent, dump them and hire better QA staff.
GTCHO•10mo 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.