Best of OpenAI — September 2025

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   Article

   Josh M.·37w

   GPT-5 is Trash.

   ChatGPT-5 has received significant criticism from users who report that responses are shorter, blander, and less engaging than previous versions. Despite being marketed as PhD-level intelligence, the model still makes basic errors in math and reasoning while suffering from hallucinations. OpenAI's removal of model selection options and implementation of an autoswitcher has frustrated users, leading many to believe this was a cost-saving measure rather than genuine improvement. The backlash was severe enough that OpenAI restored access to older models like GPT-4o.

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   Video

   NetworkChuck·35w

   N8n AI Agents are INSANE!!

   Demonstrates how to create AI agents in n8n that combine language models with command-line tools and memory. Shows a practical example of building an agent that can check website connectivity by executing ping commands through ChatGPT integration, highlighting the potential for automating network monitoring and system administration tasks.

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   Article

   Where's Your Ed At·37w

   Why Everybody Is Losing Money On AI

   Generative AI companies are fundamentally unprofitable, with every major player from OpenAI to Anthropic losing billions of dollars annually. The economics are broken: companies like Cursor send 100% of their revenue to model providers, Perplexity spends 164% of revenue on compute costs, and OpenAI lost $5 billion in 2024 despite being the market leader. Inference costs are increasing rather than decreasing, making it impossible for AI startups to achieve profitability even with usage-based pricing models.

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   Article

   Where's Your Ed At·34w

   The Case Against Generative AI

   A comprehensive analysis arguing that the generative AI industry is in an unsustainable bubble. Despite over $500 billion in investments, the industry lacks profitable companies and relies heavily on NVIDIA's GPU monopoly. Major players like OpenAI and Anthropic burn billions while generating minimal revenue compared to their costs. The piece examines how AI hype has been manufactured through vague promises and media coverage, while actual AI applications remain limited and unreliable. The author predicts an inevitable collapse as the fundamental economics don't support the massive capital expenditures.

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   Article

   Telerik·35w

   Build an LLM Chat App Using LangGraph, OpenAI, Python—Part 1

   A beginner-friendly guide to building an AI chat application using LangChain, OpenAI's GPT-3.5-Turbo, and Python. Covers setting up dependencies, environment variables, creating basic chat functionality with streaming responses, handling user input in a loop, and constraining model responses to specific JSON datasets using system prompts.

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   Video

   ByteGrad·37w

   This React AI-Text Editor Is Amazing!

   A demonstration of integrating AI features into a React text editor using Froala. Shows how to implement AI-powered text completion, shortening, and rewriting by hooking into editor events and connecting to OpenAI's API. Covers the setup process, event handling, and user interface implementation for AI text manipulation features.

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   Article

   Justin Searls·35w

   So much for OpenAI running out of money…

   OpenAI and NVIDIA announced a strategic partnership to deploy 10 gigawatts of NVIDIA systems, contradicting earlier predictions that OpenAI would run out of funding by the end of the year. This major infrastructure investment suggests OpenAI has secured significant financial backing to continue scaling their AI operations.

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   Article

   TechCentral·37w

   OpenAI’s staggering burn rate: $115-billion by 2029

   OpenAI has dramatically increased its projected spending to $115 billion through 2029, up $80 billion from previous estimates, as it scales infrastructure for ChatGPT and AI services. The company plans to develop custom chips with Broadcom and build its own data centers to control soaring cloud computing costs, with annual burn rates expected to reach $45 billion by 2028.

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