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🪐 What’s happening in tech today, April 8, 2025?

The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Bahrain's WTC construction is completed in 2008, Windows XP End of Life in 2014, and we present you with these top quality stories. From Escape Prompt Hell With These 8 Must-have Open-source Tools to Can GPT Outsmart Social Media Regulations? Inside an AI Language Evolution Experiment, let’s dive right in.

Returns are Rising Fast — and Not Enough Tools are Focused on Stopping Them at the Source

TL;DR In 2024, nearly one in five online purchases ended up being returned.

By @jelmer [ 5 Min read ]

Research shows that consumers are up to 10 times more likely to make a confident decision when presented with fewer options. This highlights the undeniable impact of the overload of choices when making decisions...

Escape Prompt Hell With These 8 Must-have Open-source Tools

TL;DR Discover 8 powerful tools transforming prompt engineering from trial-and-error into scalable systems—featuring visual workflows, auto-tuned prompts, and memory-

By @albertlieyeongdok [ 6 Min read ]

Remember when prompt engineering meant clever ChatGPT hacks and intuition-driven guesswork? Those days are long gone. As large language models (LLMs) become embedded in enterprise workflows, the tools we use to build with them need to grow up too.

Key Concepts:

What It Does:

Core Features:

Core Abstraction:..

Muddy Waters Didn’t Short AppLovin. They Shorted You.

TL;DR Muddy’s short only works if no one understands the stack. This is the line-by-line dismantling that makes their whole bet fall apart.

By @bigmao [ 9 Min read ]

Muddy Waters’ recent short report on AppLovin reads serious. Abuse, violations, an impending takedown.

This isn’t a thesis. It’s a dare: “We bet you don’t understand this company well enough to call our bluff.”

They’re not betting against AppLovin’s business, but against your comprehension. Classic intellectual arbitrage...

Can GPT Outsmart Social Media Regulations? Inside an AI Language Evolution Experiment

TL;DR See how Large Language Models creatively adapt language strategies under supervision, effectively evading detection and communicating covert information.

By @mediabias [ 11 Min read ]

Authors:

(1) Jinyu Cai, Waseda University (bluelink@toki.waseda.jp);

(2) Jialong Li, Waseda University (lijialong@fuji.waseda.jp);

(3) Mingyue Zhang, Southwest University (myzhangswu@swu.edu.cn);

(4) Munan Li, Dalian Maritime University (limunan@dlmu.edu.cn);

(5) Chen-Shu Wang, National Taipei University of Technology (wangcs@ntut.edu.tw);

(6) Kenji Tei, Tokyo Institute of Technology (tei@c.titech.ac.jp).

Abstract and I. Introduction..

Testing LLMs on Solving Leetcode Problems in 2025

TL;DR Large-scale LLMs test (o1, o3-mini; Gemini 2.0 Flash, 2.0 Pro, 2.5 Pro; DeepSeek V3, R1; xAI Grok 2; Claude 3.7 Sonnet) on solving Leetcode algorithmic problems

By @alexsvetkin [ 9 Min read ]

There are existing benchmarks for LLMs to assess their coding abilities.

Codeforces benchmarks better reflect LLMs' algorithmic problem-solving skills. OpenAI tested o1 and o3 models on Codeforces problems and shared detailed results (1, 2), while other competitors did not. That made a direct comparison impossible.

Well-Known..

Additional Stories of your interest:

-How to Choose the Right Programming Language For Your Next Project

-My GameBoy Taught Me the Future of Web3 Gaming

-To Hit $1T TVL, Ethereum Must Play the Ace

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