What does enterprise dependence on AI mean when the selected model is unavailable? The gap between 99.50% and 99.95% uptime, the lasting consequences of model fallbacks, and the energy cost of adding capacity point to the same challenge: dependable intelligence delivered efficiently.
My AI agent handled a billing dispute with a support agent while other agents worked on code, security, and documents. The customer finally has an agent too. Companies need AI with the tools and system access to resolve problems for human and AI customers alike.
As agentic AI turns tokens into a visible, finite resource, users face new decisions about models, effort, speed, resets, and workplace spending. Token anxiety is becoming the range anxiety of intelligent work.
The interstellar “wait calculation” explains how a later spacecraft can overtake an earlier one. In an age of rapidly improving AI tools, the same paradox is changing software projects: starting later can sometimes help us reach the outcome sooner.
GPT-5.6 is faster, Codex and ChatGPT now share one app, and AI can coordinate multiple agents at once. Yet complex work still takes time. Learning to use that interval may be the next productivity skill.
A look at why most AI investments fail to deliver real ROI—and how a new metric, “return per megatoken,” could redefine how companies measure value in the age of agents.
This article argues that AI is shifting software development from writing syntax to expressing intent. As natural language becomes the highest abstraction layer above code, the real value of developers moves toward defining problems clearly, setting constraints, and designing systems rather than memorizing frameworks or APIs.
Most conversations about AI focus on productivity, innovation, or replacing jobs. That misses the real shift already underway. AI is quietly changing the economics of intellectual work, and with it, what clients are willing to pay. The companies that understand this early will adapt. The rest will be forced to..
Most AI rollouts fail not because of the tech, but because of a "capability gap." Once the initial hype fades, teams hit a wall of generic outputs and frustration, leading to silent abandonment. To survive the "Three-Week Trough," organizations must move past basic prompts and invest in the human judgment required to make AI actually work.
AI can now analyze hundreds of complex documents in minutes, yet humans are still forced to click checkboxes, solve CAPTCHAs, and download PDFs by hand. In this article, I reflect on a real-world medical AI project that exposed a growing mismatch between AI capabilities and web-based software, and why asking “are you human?” may be the wrong question in an AI-driven world.
Artificial intelligence is flattening traditional signals of competence. When everyone can write compelling proposals and polished applications, evaluation breaks down. This article explores how AI acts as an equalizer—and why accountability, judgment, and responsibility are becoming the new differentiators.
They live online but can’t use a computer. Big Tech hid complexity, schools stopped teaching fundamentals, and now AI punishes digital laziness. The biggest risk in the AI era isn’t job loss—it’s computer illiteracy.
AI transformation doesn’t start with technology — it starts with people. After running multiple AI Bootcamps across different organizations, I’ve seen what truly separates a quick experiment from a lasting cultural shift. These are the key lessons that help companies turn AI from a buzzword into real business impact.
AI in mid-2025 is shifting from assistants to true agents, driving measurable gains for early adopters while exposing cracks in scalability and trust. The next six months will test whether businesses can balance bold automation with strong governance and human oversight.
Can GPT-5 solve a riddle that stumped AI models and took humans days to crack? I put it to the test—and what happened in 49 seconds blew my mind!
In this post, I share key insights from my keynote at CINNED on how artificial intelligence is transforming entrepreneurship. I explore practical tools, automation strategies, and how solo founders can now build scalable startups faster than ever.
No-code and low-code are fading fast. Discover how vibe coding—AI-powered, prompt-based software creation—is redefining the way we build
A glitch in ChatGPT’s connection to Bing and Google revealed how AI reasons, adapts, and thinks out loud. I share what I discovered — and what it means for the future of AI collaboration.
An analysis of the unintended consequences of tariff implementations on AI progress, highlighting the strain on startups and global tech dynamics.
Chatbots were just glorified menus—limited to pre-programmed workflows. AI agents, on the other hand, reason, adapt, and take real action. In this article, we’ll explore how they work and the five key principles for building AI agents that deliver real-world value. Long live AI agents!
AI just cracked my hardest riddle. For months, every model failed—until today. Grok-3 solved it in just three minutes, with an answer more elegant than my own. If AI can now reason at this level, what’s next?
AI is at the center of a global regulatory showdown. The U.S. pushes for fewer restrictions while imposing GPU bans, the EU struggles with overregulation, and innovators like DeepSeek find ways to thrive despite limitations. Are we repeating past mistakes like the Clipper Chip fiasco? Discover the good, the bad, and the ugly of global AI regulation.
DeepSeek’s clever adoption of OpenAI’s API design is sparking a shift in the AI industry. Could this move establish OpenAI’s API as the universal standard for AI development? Find out how it’s reshaping competition and innovation.
Can AI outthink us? riddle AI can’t solve—but a human did. Find out why human intelligence still shines
Discover how AI's breakthroughs, limitations, and the slowing pace of advancements mirror the metaphorical wall in Pink Floyd's The Wall
Discover whether OpenAI's o1 model is worth the investment. Explore its advanced reasoning capabilities, enterprise integration potential, and key limitations in this concise guide.
As AI-driven search engines take over, the old SEO playbook is quickly becoming outdated. Learn about AI-Search-Optimization, the new strategy for being discoverable online, and why it requires a fresh, honest approach.
Discover the thrill of balancing control and collaboration in the world of modern engineering. From the precision of coding to the wild ride of prompt engineering, this article draws parallels between driving and taming a stubborn Texas horse. Ready to master both? Click to dive into the dual lives of today’s engineers!
Shadow AI is becoming an increasing concern for organizations, paralleling the long-standing issue of Shadow IT. While Shadow IT refers to the use of systems and solutions without formal approval from the IT department, Shadow AI encompasses the unsanctioned or ad-hoc use of generative AI tools by employees.
AI, once revolutionary, is now causing frustration among investors and tech enthusiasts. Are we beginning to feel AI fatigue, and could this signal the next big shift in the tech industry? Consider the signs and what this might mean for the future of innovation.
Discover how Generative AI is revolutionizing the way business users interact with complex programming languages. From mastering Python and SQL to leveraging Google Colab and ChatGPT, find out how AI is bridging the gap between business expertise and software engineering.
Ever wondered how well AI can tackle real-world puzzles compared to humans? Dive into our latest blog where we put GPT-4o to the test with a challenging spatial intelligence puzzle from World of Engineering.
Curious about AI's abilities? In this blog, I share a chat with GPT-4o. It's great at answering questions but struggles with spelling and meta-language. Through a conversation about Spanish prime ministers, I show its strengths and quirks. If you want to see what AI can and can't do, read on!
Through a captivating riddle, we push the limits of problem-solving. Testing both ChatGPT (GPT-3.5) and advanced GPT-4o, we uncover surprising insights. Join us on this thrilling journey of mind-bending challenges and AI showdowns.
The democratization of coding through Generative AI has transformed it from a unique superpower into a widespread skill. However, as the field evolves, it still requires innovative thinkers capable of creating fresh algorithms. Despite opportunities becoming more competitive, a new elite will emerge, driving innovation and steering the future of technology.
Even with Generative AI, sectors like healthcare and government depend on finely tuned Large Language Models (LLMs), which hinge on relevant data. Ignoring a solid data strategy risks stalling AI projects and losing valuable talent. Thus, maintaining a comprehensive data strategy remains crucial
Artificial Intelligence (AI) is revolutionizing sales processes by offering innovative solutions across various stages, from data enrichment and lead generation to price optimization and competitive intelligence
I explore the changing landscape of AI education, shifting from traditional coding methods to the adoption of user-friendly tools like no-code platforms and Generative AI.
From starting Inbenta in Barcelona to witnessing the transformative impact of Generative AI in education, join me on a journey of entrepreneurship, excitement, and endless possibilities
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