

Z AI released GLM-4.7-Flash, a new 30B open source model with a 59.2% achievement on SWE Bench Verified. .ai

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Z AI released GLM-4.7-Flash, a new 30B open source model with a 59.2% achievement on SWE Bench Verified. .ai
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1/ Run the full prompt. 2/ Fill in your available time, current frustration, and responsibilities. 3/ Answer the questions honestly. The AI will build your personal Life Architecture Document. This isn't motivation. It's a system. The original article took 15 minutes to

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What DIED in 2023-2026: Prompt Engineering: −60% salary ($95K→$38K). 100K+ certified, jobs disappeared. Basic Python: −61% ($82K→$32K). AI writes better code. Entry Data Analysis: −64% ($78K→$28K). Automated dashboards replaced analysts. Commoditization happened
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One small thing we’ve been using ChatLLM by Abacus AI for lately: text → speech.
— Abacus.AI (@abacusai) 19 janvier 2026
Drop in any text and get clean, natural audio back in seconds.
Great for quick demos, voiceovers, or just hearing content out loud.
Simple, useful, and surprisingly handy. pic.twitter.com/zNHdwrBUhr
One small thing we’ve been using ChatLLM by Abacus AI for lately: text → speech. Drop in any text and get clean, natural audio back in seconds. Great for quick demos, voiceovers, or just hearing content out loud.
Simple, useful, and surprisingly handy.

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Responses by ChatGPT 5.2 Auto. Currently popular prompts found by me at https://
x.com/uubzu/status/2
012782068829171955
… and https://
x.com/gmltony/status
/2012936406461456411
…. Similar result pair at https://
x.com/hovormijurko/s
tatus/2012993464464511270
… with real picture. Longer explanation at https://
lesswrong.com/posts/rP66bz34
crvDudzcJ/decision-theory-does-not-imply-that-we-get-to-have-nice
….
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here's the part that stuck with me. claude outperformed every human candidate who's ever taken anthropic's internal engineering hiring test. not most. every single one in the company's history. a 2-hour rigorous assessment designed to filter for elite engineers. so what

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the benchmark data made me pause. claude opus 4.5 hit 80.9% on SWE-bench verified. first model to ever break 80%. this isn't leetcode. it's real github issues from production repos. the actual work developers do. 4 out of 5 real-world bugs. solved.

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i looked up the internal numbers. their engineers are using claude for 60% of their work. not "sometimes helps with debugging." sixty percent of everything. 50% productivity gains. 2-3x better than a year ago.
at what point do we stop calling this "assistance"?

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daniela amodei on CNBC: "by some definitions of that, we've already surpassed" human-level AI. her example was coding. she said claude writes code "about as well as many developers at anthropic now." anthropic. the company that probably employs some of the best engineers on
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Abacus AI Is The Infrastructure You Need To Orchestrate Across 40 AI Models Reasoning – GPT 5.5 thinking and pro
Coding – Opus 4.5 Spatial Intelligence – Gemini 3.0 Pro – Kling 2.6 Motion Control
Images – Nano Banana Pro Routel LLM will max and match the BEST AI Models