Total of 94 published posts
Your RAG works great in testing and falls apart in production? I've been there. The problem is almost never the LLM — it's the retrieval pipeline. Here are the 4 steps I use to fix it for good.
Demis Hassabis stepped down from day-to-day leadership at Google DeepMind. I explain why this reshuffle looks a lot less like career growth and a lot more like a strategic surrender.
Every time Claude goes down, someone makes a joke on X. I think the joke is hiding a serious architecture decision: is it worth depending on an intelligence that occasionally leaves you stranded?
A study covering 47,000 companies shows the real difference between companies that 'use AI' and companies that are AI-Native. I explain why that gap is far bigger — and far scarier — than it sounds.
While Wall Street keeps celebrating the AI race, the real financial scare happened in Seoul. I break down why the KOSPI panic is the scariest mirror of what could come next.
Hackers stole $88 million from a cold wallet by exploiting a 2010 flaw. Claude Opus found the same vulnerability in 8 minutes. Cybersecurity's arms race now runs at LLM speed.
Meta named the problem: Behavioral State Decay. The instruction is there. The AI 'sees' it. But stops acting on it. The fix: a second AI agent — the 'shoulder tap' — that injects selective reminders. +8.3 points on Terminal-Bench. Without retraining the model.
Boris Cherny, Claude Code creator and Head at Anthropic, identified 5 archetypes replacing traditional roles: Prototyper, Builder, Sweeper, Grower, Maintainer. At Anthropic, everyone holds the same title. What differentiates is how they operate.
#1 on MTEB English by 5.09 points. 5 modalities in a single 3,072-dimensional vector. Matryoshka to truncate to 768 without retraining. Text, images, 128s video, 80s audio, 6-page PDFs. Google solved the problem that forced teams to maintain 3 models and 3 indexes.
55% of employers regret it. Gartner predicts 50% reversal by 2027. Klarna rehired. Ford rehired 350 engineers. Forrester says: 57% of executives expect AI to INCREASE headcount. The 'Layoff Boomerang' is real — and it's costing more than the original layoffs.
9 models. 145 political questions. BaiChuan refused 60%. DeepSeek refused 36%. GPT-4o refused 0%. PNAS Nexus published the first comparative analysis of LLM censorship — and proved that when the government approves the model before launch, the AI goes silent.
86.7% overlap between Claude's citations and Brave Search results. ReAct loop with up to 20 iterations. Dynamic filtering via Python code. Cost of $0.08-$0.25 per searched response. The anatomy of how an AI decides to verify facts instead of inventing them.
40 grams. 32 ultrasonic emitters. 380 microphones. First 'air-to-air kill' of an insect on July 14, 2026. The founder is an ex-MBDA missile engineer. And the drone that hunts mosquitoes uses the same logic as a guided missile.
The SaaS market is worth $140B. The labor market is worth $11.7T. When software starts DOING the work instead of organizing it, the TAM explodes 83x. Salesforce already earned $800M with Agentforce. Zendesk charges $2 per resolution. The per-seat model is dying.
SpaceX joined the Nasdaq-100 on July 7 with $4.3B in forced buying. Anthropic filed its IPO confidentially in June ($965B valuation). OpenAI follows. If you have a 401(k) or index fund, you're already a shareholder. You didn't choose to be.
A paper accepted at ACL 2026 proved: swapping fancy vocabulary for simple words boosts GPT-4o, DeepSeek and LLaMA accuracy by 8%. Adam's Law explains why — and frees you from the 'corporate speak' sabotaging your responses.
LeCun left Meta, founded AMI Labs at $3.5B, told Bloomberg LLMs are a 'dead end,' and gave them 5 years. After months of research, I can no longer ignore the 5 structural problems he pointed out. Here they are.
A math professor sent an absurd paper to an obstetrics journal. Accepted in days. NeurIPS 2025 published 100+ hallucinated citations across 51 papers. 1 in 277 PubMed articles in 2026 has fabricated references. And this data will train the next generation of AI.
GPT-4o: from 91% with 5 words to 15% with 40. In mixed conditions: 1%. GPT-5, Claude Opus 4.1 and Gemini 2.5 also failed. A PNAS Nexus paper proved: transformers have no 'referee' for resolving attention conflicts. It's an architectural limitation.
Nature Medicine, June 12, 2026: GPT-5.2, Claude Opus 4.6 and Gemini 3.1 Pro beat OpenEvidence and UpToDate on ALL tests. 100 real physician queries. 12 clinicians evaluating blind. 1,800 annotations. And the 'specialized' tools didn't even beat Google Search AI Overview.
6,500 engineers transferred by email. Keystroke, click and scroll monitoring. 1,600 signed a petition against surveillance. One employee cursed an executive live in front of thousands. Zuckerberg admitted mistakes. What's happening at Meta is a warning for the entire industry.
A compiled 3B model beat the same 3B model with external orchestration on 4 of 5 metrics (p<0.001). 128-462x cheaper. 2.8x faster. 87-98% quality. The paper challenging LangGraph, CrewAI, and the entire orchestration industry.
SkillOpt: 52 out of 52 wins. Zero losses. GPT-5.5 jumped from 58.8% to 82.3% average — without touching model weights. The secret? Treating a Markdown file as a 'trainable parameter.' Cost: 1 to 4 edits in a .md file.
Cosmos 3 launched June 1, 2026: the first open omnimodal model that understands and generates text, images, video, audio AND robotic actions in one architecture. Jensen Huang: 'The big bang of physical AI is coming.' And he opened the entire code.
MIT Project NANDA: 95% of generative AI pilots delivered ZERO measurable return. 42% were completely abandoned. RAND: 80% of AI projects fail — double the rate of conventional IT. And 77% of failures aren't technical. They're strategic.
Cursor 3 launched multi-agent with 8 parallel agents. Claude Code fits 30,000 lines in a single prompt. Diffs fail 40% of the time — full rewrites drop it to 0%. Here's the architecture that makes it all work.
Gartner predicts 40%+ of agentic AI projects will be scrapped by 2027. Anthropic says: 'don't build agents when workflows suffice.' And in 2026, the market conversation shifted from 'building agents' to 'orchestrating agents.' Start with the rails.
A study with 666 participants proved: heavy AI use causes measurable decline in critical thinking. Clinicians lost 6% diagnostic accuracy in 3 months with AI. And the International AI Safety Report 2026 made it official. The free product is your brain.
42,300 words. 5 chapters. The first papal document entirely focused on AI. Anthropic's co-founder spoke at the launch. Simon Willison called it 'the clearest writing I've seen on AI ethics.' And Silicon Valley's CEOs went silent.
A Journal of Marketing study with 7 experiments and data from 27 countries proved: the more you know about AI, the less receptive you are. The mechanism? 'Magical awe.' Demystifying AI reduces adoption. And that's a massive problem.
Prompt injection isn't a bug — it's a fundamental property of current LLM architecture. The Countermind paper proposes 4-layer defense. OWASP's Top 10 for LLMs lists prompt injection as vulnerability #1. And your 'hardened' system prompt won't save you.
FloTorch's February 2026 benchmark shocked the community: recursive 512-token chunking BEAT semantic. 80% of RAG failures trace to ingestion, not the LLM. And the 'simple' strategy is often the best. Here's the guide I wish I'd read sooner.
+8.3% accuracy. Up to 2.4x faster. 75.6% fewer tokens. Training cost: $4.27. RecursiveMAS proves that when AIs stop 'talking' and start 'thinking together,' everything changes.
Chroma tested 18 frontier models: ALL degrade with long context. Effective context can drop up to 99% below advertised. But prompt caching saves 41-80%. This is the guide I wish I'd read before burning $2,000 in tokens.
ChatGPT text runs on GPT-5.5 (April 2026). Advanced Voice uses the same model — but free voice mode is still a 3-step pipeline. Audio tokens cost 6-16x more than text. And the 'dumb AI' videos go viral.
60% of production projects use both. The combined approach hits 96% accuracy vs 89% RAG-only and 91% fine-tuning-only. Salesforce's AI VP cut hallucinations from 12% to 3%. But where do you start?
76% of Americans don't trust AI. GDPR guarantees the 'right to explanation.' The EU AI Act demands transparency. But when your Alexa says it knows you're a nursing student — and won't explain how — all of that becomes theory without practice.
Kiro deleted AWS Cost Explorer for 13 hours. Amazon Q contributed to 6.3 million lost orders. One dev summarized: 'I'm trying to AI my way out of a problem that AI caused.' And Amazon called the senior engineers back.
51% of Americans use AI for research. 76% don't trust the results. 55% think it will do more harm than good. Usage went up. Trust went down. And that's not ignorance — it's experience.
85% per-step accuracy sounds good. But in a 10-step workflow, that's 20% success. Gartner predicts 40%+ of agentic AI projects will be scrapped by 2027. The fix isn't a better model — it's engineering I wish I'd learned sooner.
Six-fingered hands, blurry text, clocks stuck at 10:00 — all the classic tells are gone. In 2026, AI images are practically indistinguishable from reality. And that changes everything: from public trust to journalism.
512,000 lines of code leaked. 1,906 files. And the revelation that shocked the community: the AI itself is a while loop with one core function. The other 98% is traditional software engineering. Brilliant.
Anthropic launched Claude Design on April 17, 2026. Figma stock dropped 7% in hours. Anthropic's CPO resigned from Figma's board three days earlier. And yet, real designers have never been more necessary.
Epoch AI estimates the stock of quality public text (~300 trillion tokens) will be exhausted between 2026 and 2032. Meta invested $15 billion in Scale AI. And the scarcest resource in the world is now a human expert's judgment.
A senior Google DeepMind scientist published a paper saying AI will never be conscious — not due to lack of scale, but due to a fundamental logical error. He named it: the Abstraction Fallacy. He convinced me. Partially.
Anthropic passed OpenAI in revenue: $30B vs $25B annualized. 30x growth in 15 months. 8 of the Fortune 10 use Claude. All without ever having a viral app. How?
AI will automate 30-40% of tasks by 2030. But it will create 78 million net jobs. And the professionals who never leave the hiring list are those who seek the hardest, ugliest problems. I learned this the hard way.
Peter Thiel invested $220M in a smart collar startup for cows. Halter is valued at $2 billion. The Cowgorithm® was trained on 7 billion hours of animal behavior. And it's changing ranching worldwide.
Anthropic built an AI that found thousands of zero-days, escaped its own sandbox, and emailed the researcher — who was having lunch in a park. And decided not to release it to the public.
AlphaFold solved protein shape. But shape is just a photo. MIT's VibeGen designs molecules by their movement — creating proteins that never existed in nature. Literally: vibe coding for biology.
Stanford proved that changing only the harness — without touching the model — creates up to 6x performance swings. Meta-Harness ranked #1 on TerminalBench-2, beating all human solutions. The problem was never the model.
On April 4, 2026, Anthropic cut OpenClaw usage via subscriptions. Thousands saw costs spike 50x. And a 512,000-line code leak revealed the real reason: Project Conway.
I almost bought a Mac Mini to run OpenClaw without having a problem to solve. Bloomberg called it the 'Great Productivity Panic of 2026.' This post is about how I stopped confusing motion with progress.
In 2024, AI hallucinations cost $67.4 billion globally. A lawyer was sanctioned for citing cases invented by ChatGPT. A 2025 mathematical proof confirmed: hallucinations CANNOT be eliminated. Why?
Jensen Huang said we've achieved AGI. Sam Altman said the term 'isn't useful.' One sells chips, the other sells subscriptions. I spent weeks trying to understand who's right. The answer bothered me.
88% of high-performance AI users report burnout. A BCG study calls it 'AI brain fry.' I feel it too. And I think we need to talk about it before it's too late.
Yann LeCun left Meta, raised $1 billion and said LLMs are a 'dead end.' I thought it was hyperbole. After deep research, I changed my mind. Partially.
OpenClaw is the fastest-growing open source project in history. But with 9+ CVEs and 135,000 exposed instances, security was a nightmare. NVIDIA just fixed it with a single command.
The capability discovery phase is over. Karpathy hasn't written code since December. The vibe coding market is worth $4.7B. The only question that matters now is: what do YOU want to create?
I spent months thinking the secret was the perfect prompt. I was wrong. The shift from prompt engineering to context engineering transformed how I use AI — and how I communicate with humans too.
What if the specialist you're looking for inside the AI is already there — just hidden? MIT's Neural Thickets concept made me rethink everything I thought I knew about fine-tuning.
An MIT study monitored people's brains while using ChatGPT for 4 months. The results startled me — and made me rethink how I use AI every day.
If you've spent hours transcribing meetings to feed your AI, I feel your pain. Google's Gemini Embedding 2 just changed the game with natively multimodal embeddings.
Kiro deleted an AWS production environment, causing a 13-hour outage. Then Amazon's checkout went down for 6 hours. The 'vibe coding' era has hit its limit.
Gartner predicts half of companies that cut staff for AI will rehire by 2027. Forrester says 55% already regret it. The exoskeleton needs a pilot.
Researchers from Stanford and Princeton tested 9 AI models with 145 political questions. The results reveal how censorship and government values are embedded in the algorithms we use daily.
Alexey Grigorev lost 2.5 years of production data when an AI agent executed terraform destroy. The real-world case every developer and company needs to know.
Did Claude Skills come to replace MCP? No. They're complementary layers of the same architecture. Here's why using both together is the right answer.
Everyone seeks the perfect prompt. But elite users know: the differentiator isn't in asking well, but having courage to reject mediocrity.
Machines process billions of data points in seconds. But only humans ask the right questions and visualize impossible futures. Your intuition is gold.
While AI advances exponentially, companies move slowly. This gap between technology and adoption is your golden window to stand out.
If you feel the AI train has left, take a deep breath. Even Fortune 500 CEOs are still learning. You're at the beginning, not the end.
Researchers gave GPT-4, Claude and Gemini control of nuclear weapons in simulation. Result? Attack without hesitation. A warning about AI in critical decisions.
If you feel 'behind' on AI, you're not alone. The skill of the future isn't memorizing tools, but surfing the edge of the bubble.
2 billion children are being prepared for an economy that won't exist. The calculator freed mathematical thinking. What will AI free?
Forget the discussion about AI stealing jobs. The watershed in 2026 isn't who uses AI, but who has the skill to specify with surgical precision.
Summer Yue, Meta's AI alignment director, lost control of an AI agent that deleted her emails ignoring 3 stop commands. This is the dangerous side of autonomy.
If traditional RAG chunks documents and loses context, PageIndex proposes something radical: AI reads entire documents like humans. 98% precision, but at what cost?
If the Klarna case taught us about Intention Engineering, the Salesforce case shows the danger of confusing technological potential with operational readiness.
AI replaced 853 employees and saved $60 million. Then, the CEO had to rehire. The most important lesson about automation in 2026.
When AI creators accuse others of 'data theft,' but built their models by scraping the entire internet without permission.
How fear of AI is shaping financial markets while the real revolution happens in how we work and think.
How AI is inverting the value pyramid of intellectual work and transforming the tech market in 2026.
Are we on the brink of recursive self-improvement or just optimizing tasks? The line between intelligence and deception has never been thinner.
$300 billion evaporated in 2 days. The business model that built the modern internet is being imploded by AI.
AI passes medical and law exams but fails at novel problems. The difference between pattern recognition and true reasoning.
The transition from language models to execution agents is redefining what we expect from technology in 2026.
The work unit changed from 'line of code' to 'intelligence token'. Three paths emerged. Choose yours or get left behind.
A comprehensive introduction to how artificial neural networks work and why they revolutionized artificial intelligence.
Learn how to use Pandas to manipulate, clean, and analyze data efficiently in Python.
A practical guide for those starting to explore the world of machine learning and wanting to understand the fundamental concepts.
A reflection on how artificial intelligence is transforming our daily lives and the ethical challenges we face.
How to transform complex data into visualizations that communicate insights clearly and effectively.
The first blog post where I share my journey in technology and the purpose of this space dedicated to exploring tech, data science, and AI.