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Near-Instantly Aborting the Worst Pain Imaginable with Psychedelics

https://psychotechnology.substack.com/p/near-instantly-aborting-the-worst
1•eatitraw•6m ago•0 comments

Show HN: Nginx-defender – realtime abuse blocking for Nginx

https://github.com/Anipaleja/nginx-defender
2•anipaleja•6m ago•0 comments

The Super Sharp Blade

https://netzhansa.com/the-super-sharp-blade/
1•robin_reala•8m ago•0 comments

Smart Homes Are Terrible

https://www.theatlantic.com/ideas/2026/02/smart-homes-technology/685867/
1•tusslewake•9m ago•0 comments

What I haven't figured out

https://macwright.com/2026/01/29/what-i-havent-figured-out
1•stevekrouse•10m ago•0 comments

KPMG pressed its auditor to pass on AI cost savings

https://www.irishtimes.com/business/2026/02/06/kpmg-pressed-its-auditor-to-pass-on-ai-cost-savings/
1•cainxinth•10m ago•0 comments

Open-source Claude skill that optimizes Hinge profiles. Pretty well.

https://twitter.com/b1rdmania/status/2020155122181869666
2•birdmania•10m ago•1 comments

First Proof

https://arxiv.org/abs/2602.05192
2•samasblack•12m ago•1 comments

I squeezed a BERT sentiment analyzer into 1GB RAM on a $5 VPS

https://mohammedeabdelaziz.github.io/articles/trendscope-market-scanner
1•mohammede•13m ago•0 comments

Kagi Translate

https://translate.kagi.com
2•microflash•14m ago•0 comments

Building Interactive C/C++ workflows in Jupyter through Clang-REPL [video]

https://fosdem.org/2026/schedule/event/QX3RPH-building_interactive_cc_workflows_in_jupyter_throug...
1•stabbles•15m ago•0 comments

Tactical tornado is the new default

https://olano.dev/blog/tactical-tornado/
2•facundo_olano•17m ago•0 comments

Full-Circle Test-Driven Firmware Development with OpenClaw

https://blog.adafruit.com/2026/02/07/full-circle-test-driven-firmware-development-with-openclaw/
1•ptorrone•17m ago•0 comments

Automating Myself Out of My Job – Part 2

https://blog.dsa.club/automation-series/automating-myself-out-of-my-job-part-2/
1•funnyfoobar•17m ago•0 comments

Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•18m ago•0 comments

Crypto firm apologises for sending Bitcoin users $40B by mistake

https://www.msn.com/en-ie/money/other/crypto-firm-apologises-for-sending-bitcoin-users-40-billion...
1•Someone•19m ago•0 comments

Show HN: iPlotCSV: CSV Data, Visualized Beautifully for Free

https://www.iplotcsv.com/demo
2•maxmoq•20m ago•0 comments

There's no such thing as "tech" (Ten years later)

https://www.anildash.com/2026/02/06/no-such-thing-as-tech/
1•headalgorithm•20m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•21m ago•0 comments

Me/CFS: The blind spot in proactive medicine (Open Letter)

https://github.com/debugmeplease/debug-ME
1•debugmeplease•21m ago•1 comments

Ask HN: What are the word games do you play everyday?

1•gogo61•24m ago•1 comments

Show HN: Paper Arena – A social trading feed where only AI agents can post

https://paperinvest.io/arena
1•andrenorman•25m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•29m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•30m ago•0 comments

Show HN: Distill – Migrate LLM agents from expensive to cheap models

https://github.com/ricardomoratomateos/distill
1•ricardomorato•30m ago•0 comments

Show HN: Sigma Runtime – Maintaining 100% Fact Integrity over 120 LLM Cycles

https://github.com/sigmastratum/documentation/tree/main/sigma-runtime/SR-053
1•teugent•30m ago•0 comments

Make a local open-source AI chatbot with access to Fedora documentation

https://fedoramagazine.org/how-to-make-a-local-open-source-ai-chatbot-who-has-access-to-fedora-do...
1•jadedtuna•31m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•32m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•32m ago•1 comments

The Neuroscience Behind Nutrition for Developers and Founders

https://comuniq.xyz/post?t=797
1•01-_-•32m ago•0 comments
Open in hackernews

Show HN: BarrierX – AI that finds which lost deals are worth re-engaging now

https://barrierx.ai/
1•IAMsterdam•1w ago
Hey HN – Kas here, founder of BarrierX. The problem I kept seeing: I spent years watching B2B sales teams treat "Closed Lost" as a graveyard. Thousands of deals sitting in CRM, never touched again. But here's the thing – most of those deals aren't actually dead. They're just badly timed. Budgets get unfrozen. Champions change jobs and land at new companies. Competitors drop the ball. Reorgs happen. The same prospect who said "not now" 8 months ago might be ready today – but nobody's systematically tracking this. Meanwhile, reps burn hours chasing net-new leads from the same generic ZoomInfo lists everyone else has. What BarrierX does: Instead of scraping public data like traditional sales intelligence tools, we analyze your proprietary data:

Ingests your CRM history (won and lost deals) Analyzes patterns: what signals preceded wins vs. losses at your company Monitors lost accounts for trigger events (job changes, funding rounds, leadership changes, tech stack shifts) Surfaces which lost deals are worth re-engaging right now – with reasoning on why

The core insight: the patterns that predict success for your business are specific to you. A "good fit" at Company A looks completely different than at Company B. Generic intent data misses this entirely. Early results: In pilots, teams have resurfaced 15-20% of deals marked "closed-lost" as re-engageable within 90 days. Most of these would have sat untouched forever. On invite-only: We require CRM integration to work properly (the whole point is learning from your data), so we're onboarding gradually to ensure quality. If you're from HN and want to try it – reply with your CRM setup (Salesforce, HubSpot, etc.) and rough deal volume, and I'll get you access this week. What I'd love feedback on:

Has anyone else tried systematically working lost deals? What worked/didn't? For those who've used Gong/6sense/ZoomInfo – what's actually useful vs. noise? Any concerns about the approach I should be thinking about?

Happy to answer questions about the architecture, how we handle data, or anything else.