OpenAI Codex CLI Debuts 🤖, Are We Overestimating the Power of AI? 📉

Are We Overestimating the Power of AI? 🤖📉

As AI continues to dominate headlines, it’s easy to get caught up in the extremes—either panicking about job loss or dreaming of AI utopia. But just like cloud computing before it, the real story isn’t about instant disruption—it’s about long-term transformation that depends on far more than just algorithms.

Here’s what we can learn from the cloud revolution to truly understand where AI is headed.

The Short-Term Hype vs. Long-Term Impact

According to Amara’s Law, we tend to overestimate the effect of a technology in the short term and underestimate it in the long term. We saw this with cloud computing: it took nearly a decade before AWS faced serious competition, and even longer before cloud services matured into critical business infrastructure. The same is happening with AI. What feels like immediate disruption might, in fact, be early-stage exploration.

AI Needs More Than Code

AI, like cloud, won’t deliver real value unless paired with good leadership, safe environments, and business-aligned engineering. Success doesn’t come from the tech alone—it comes from how well you integrate it into real-world problems.

Think: not “How do we use AI?” but “What problem can AI solve better today?”

Cloud Is the Hidden Backbone of AI

Without strong cloud infrastructure, AI can’t scale or personalize effectively. Companies with mature cloud systems are pulling ahead—training models on their own data, scaling experiments easily, and embedding AI directly into their workflows.

For others, relying on AI-as-a-Service could mean higher costs and less control.

We’re Underestimating the Long Game

AI’s short-term hype may fade, but its long-term effects will change everything—from how teams collaborate to how companies create value. It’s already reshaping job roles, business models, and problem-solving methods.

AI won’t just support your business—it might become its foundation.

Final Takeaway

We might be overestimating AI’s present, but we’re absolutely underestimating its future. The winners won’t be the ones with the flashiest tools—they’ll be the ones who combine AI with thoughtful strategy, strong cloud foundations, and people-centered innovation.

💬 OpenAI Developments

OpenAI debuts Codex CLI, an open source coding tool for terminals

OpenAI has introduced Codex CLI, an open-source coding agent that runs locally in terminal environments, enabling its AI models—including the new o3 and o4-mini—to write, edit, and interact with local code and files. Though not fully autonomous, Codex CLI reflects OpenAI’s vision of “agentic” software engineering and includes support for multimodal inputs, with $1 million in API credits offered to encourage developer adoption.

OpenAI o3 and o4-mini System Card

OpenAI's newly launched o3 and o4-mini models integrate advanced reasoning with full tool access—including web browsing, coding, image analysis, and automations—enabling them to tackle complex tasks with enhanced safety through reinforcement learning and deliberative alignment. According to OpenAI’s Safety Advisory Group, these models do not meet the High threshold in critical risk areas like bio-chemical capability, cybersecurity, or AI self-improvement, aligning with the standards of Version 2 of OpenAI’s Preparedness Framework.

🚀 Tech Industry Moves

Google: Researchers argue that while generative AI models like ChatGPT surpassed earlier reinforcement learning (RL) systems like AlphaZero in handling open-ended human input, they lost the ability to self-discover knowledge, relying too heavily on human prompts and judgment. To overcome this limitation, they propose a new approach called "streams," which builds on RL principles to enable AI agents to develop strategies and insights beyond what human raters can anticipate.

Google's Gemini 2.5 Flash introduces a "thinking budget" feature that lets developers control the level of reasoning the AI performs, enabling significant cost savings—up to 600%—for simpler tasks, while preserving power for complex ones. Designed for enterprise flexibility, the model balances performance and affordability, outperforming some rivals in reasoning benchmarks and forming part of Google’s broader strategy to compete with OpenAI through customizable, cost-efficient AI solutions.

Microsoft has introduced "Computer Use" in Copilot Studio, a new AI feature that enables agents to autonomously interact with websites and desktop applications by mimicking human actions like clicking, typing, and navigating menus—without needing APIs. Designed for real-world business automation, it includes adaptive reasoning, secure cloud operation, and transparency tools, with early access now available and wider rollout expected soon.

Meta: During Meta’s antitrust trial, CEO Mark Zuckerberg acknowledged that TikTok significantly slowed Meta’s growth and posed a major competitive threat since its rise in 2018. He also noted that social media platforms have shifted from relying on personal connections to functioning as content discovery engines, even as Facebook attempts to revive its original focus on friend-based interactions with new features.

Nvidia CEO Jensen Huang visited China to reinforce business ties amid growing US export controls, emphasizing the country's importance as a key market despite declining sales compared to the US. These controls reflect a broader push by the US to shift advanced tech supply chains domestically, intensifying the global tech divide between US- and China-led systems.

💡 AI Tools

Hint AI helps users craft better prompts and generate high-quality content across various platforms using AI guidance.

Bearly AI is an all-in-one productivity tool that brings together reading, writing, and research features powered by AI for faster workflows.

PromptPal AI offers a searchable library of curated prompts to help users get more out of their AI tools like ChatGPT.

Suggesty AI recommends personalized content and ideas, enhancing creativity and productivity based on user input and context.

Supernormal AI automatically generates meeting notes and summaries from video calls, saving time and improving documentation for teams.

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