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Proof: Making Agents Easy

https://proof.diy
1•r_gaur•1m ago•1 comments

My university is proposing to offer shorter degrees. Others should follow suit

https://www.washingtonpost.com/opinions/2026/10/23/colleges-should-offer-three-year-degrees/
1•paulpauper•3m ago•0 comments

The Putin Whisperers

https://www.ft.com/content/dcb57f30-bbfe-418d-9e52-5df3074d1764
1•paulpauper•3m ago•0 comments

Mosaico tiling Window manager adds mouse support

https://github.com/jmelosegui/mosaico
1•jmelosegui•3m ago•0 comments

Show HN: Ledge – an open-source app that puts the MacBook notch to work

https://ledgeapp.dev/
2•egemertbalcik•6m ago•0 comments

Show HN: Comparing SF Bay Area trash rates

https://www.shasheene.com/bay-area-trash-rates/
1•shasheene•8m ago•0 comments

Crosscut – Drawing Dynamic Models

https://www.inkandswitch.com/crosscut/
1•andsoitis•9m ago•0 comments

The Power Grab of the AI Doomers

https://www.aipanic.news/p/the-power-grab-of-the-ai-doomers
2•theanonymousone•9m ago•0 comments

Hegseth warns prediction market bets warp military judgment, endanger troops

https://arstechnica.com/tech-policy/2026/10/pentagon-memo-on-prediction-markets-says-insider-bets...
1•pseudolus•9m ago•0 comments

Santree: Backlog, Shipped in Parallel

https://github.com/santree-ai/santree
1•nateb2022•15m ago•0 comments

Show HN: AI Data Footprint Tracker – audit what your AI tools hold, offline

https://theaioperatorstore.gumroad.com/l/womuyx
1•theaioperator•16m ago•0 comments

Kauldron: Modular, scalable library to train ML models

https://github.com/google-research/kauldron
2•nateb2022•17m ago•0 comments

Why the Rich Are Getting Richer and the Poor Are Further Removed from Prosperity

https://lusopt2016.blogspot.com/2026/10/a-grande-divisao-porque-e-que-os-ricos.html
4•inandout•18m ago•0 comments

It's a trap: testing coding agents on a language with surprising semantics

https://blog.csongor.co.uk/loom/
2•kcsongor•19m ago•0 comments

Show HN: Hycli – reverse-engineer websites into CLI and MCP tools for AI agents

https://github.com/Hybirdss/Hycli
1•hybirdss•19m ago•0 comments

Show HN: SQLite-on-object storage using GCS Appendable Objects

https://github.com/fatlotus/sqlite-on-gcs-rapid
1•fatlotus•21m ago•0 comments

Monarchs report their locations via cell phone

https://news.vt.edu/articles/2026/10/cmi-monarchs.html
3•geox•24m ago•1 comments

Hooke – Run agents on schedule or file changes with just one file

https://github.com/aditya-azad/hooke
1•styxnstones•24m ago•1 comments

NeuronDump: Open a local LLM as a 3D graph, cut parts, see what breaks

https://github.com/aymen94/NeuronDump
2•aymen1994•26m ago•0 comments

Google's privacy policy to use info shared through Personal Intelligence for ads

https://www.androidauthority.com/google-personal-intelligence-privacy-3727111/
2•smurda•27m ago•0 comments

Upwelling – Combining real-time collaboration with version control for writers

https://www.inkandswitch.com/upwelling/
1•andsoitis•27m ago•0 comments

Maker's Schedule, Manager's Schedule

https://paulgraham.com/makersschedule.html
1•andsoitis•28m ago•0 comments

Augmodo Raised Capital to Take Its Employee-CameraBadges Beyond the Retail Floor

https://startupfortune.com/augmodo-raised-21-million-to-take-its-camera-badges-beyond-the-retail-...
2•Baljhin•28m ago•2 comments

Eunice is almost here (William Gibson, Agency)

https://armincat.com/articles/eunice-is-almost-here
7•armcat•30m ago•1 comments

Geneva in 3D and real time with open data

https://geneva3d.ch/
2•sirpilade•37m ago•0 comments

Reclaim disk space with an AI agent

https://github.com/riza/ai-disk-cleanup
1•r1z4•40m ago•0 comments

Moderna and Merck say their mRNA cancer vaccine cut death, recurrence by 42%

https://arstechnica.com/health/2026/10/personalized-mrna-cancer-vaccine-cut-melanoma-death-recurr...
33•_Microft•41m ago•0 comments

"Study history thoroughly" Lithuanian woman to hammer and sickle waving students

https://www.baltictakes.com/italians-praise-lithuanian-womans-open-letter-encouraging-hammer-and-...
2•Teever•43m ago•1 comments

YOD4COINS – Offline-first transaction protocol with adaptive consensus

https://github.com/masondosibongakonke2-blip/yod4coins-core
1•sbongamasondo•50m ago•0 comments

Watching the Watchers

https://watchingthewatchers.github.io/watchingthewatchers/index.html
2•taubek•51m ago•0 comments
Open in hackernews

What if your QA engineer never slept?

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