AI market intelligence
Analysis & guides
Long-form, data-driven articles. No AI slop, no recycled press releases — every piece is researched, sourced and dated.
AI companies
3The biggest AI companies in 2026: who actually builds the models
A map of the AI industry in 2026 — the model labs, the chipmakers, the hyperscalers and the application layer — and how to tell which companies are core to AI versus along for the ride.
Nvidia and the AI supply chain: the companies that power the boom
Behind every AI model is a physical supply chain — chips, memory, networking, manufacturing and power. A map of the picks-and-shovels companies, and why this layer captured so much of the boom.
OpenAI vs Anthropic vs Google DeepMind vs xAI compared
The four frontier AI labs, compared on what actually distinguishes them — backers, business model, positioning and how investors can (and can't) get exposure to each.
AI bubble
3AI bubble vs the dot-com bubble: 5 comparisons
Is 2026 a rerun of 2000? Five concrete comparisons between the AI boom and the dot-com bubble — valuations, profits, concentration, capex and breadth — and what each one tells you.
Are we in an AI bubble? What the data says — not the headlines
A calm, numbers-first look at the AI bubble question in 2026: market concentration, capex, valuations and how today compares to the dot-com peak. With the data points and their caveats.
Magnificent 7 concentration: how to measure your real AI exposure
A few mega-caps now drive the whole market. Here's how to measure how concentrated your portfolio really is in the Magnificent 7 and AI — and what to do about it.
Company verification
3AI startup due diligence: a checklist for angels and operators
Before you wire money into an 'AI startup', work through this checklist — data, model, team, moat and the AI-washing red flags. Adapted from professional due-diligence practice.
AI-washing: how to verify whether a company really does AI
A practical, source-based guide to telling genuine AI from marketing. Built on the CFA Institute's due-diligence framework, with a checklist, red flags and the filings to read.
10 red flags of AI-washing in a startup pitch
A field guide to spotting AI-washing in pitch decks and product pages — ten concrete red flags, why each one matters, and the question that cuts through it.
AI detection
3AI Act Article 50: an investor's lens on AI-washing
From 2 August 2026, the AI Act's Article 50 transparency duties become a real regulatory risk. How investors and boards can gauge a company's exposure, where AI-washing starts, and which detection tools help.
Best AI content detectors in 2026, compared
An independent comparison of the leading AI detectors — Originality.ai, Copyleaks, GPTZero, Sapling, Winston AI and more — what each is best at, how reliable they really are, and how to use them well.
How to detect AI text, images and deepfakes: a practical toolkit
A hands-on guide to spotting AI-generated content across text, images, audio and video in 2026 — which tools to use, what they can and can't do, and the manual checks that still matter.
AI abuses
2AI abuses and scandals: the patterns
From deepfake fraud and voice cloning to data scraping and overstated AI claims — the recurring categories of AI abuse in 2026, and the concrete lessons each one holds for users and investors.
Deepfake fraud and voice cloning: how it works and how to defend
AI-powered impersonation is now a mainstream fraud tactic. How deepfake and voice-cloning scams actually work in 2026, who they target, and the practical defences that stop them.
Investing in AI
5Best AI ETFs in 2026: how to compare them
AI ETFs are not interchangeable. A practical framework for comparing them — concentration, holdings overlap, fees and what 'AI exposure' really means — so you don't buy the same five stocks three times.
The hidden risks of investing in AI startups
The upside of AI startups gets all the attention. Here are the structural risks that quietly determine your real return — illiquidity, lock-ups, dilution, SPV fees and model dependency.
How to invest in AI in 2026: stocks, ETFs, startups and the risks
A complete, honest map of the ways to invest in AI — public stocks and ETFs, plus the private routes (angels, VC, equity crowdfunding, pre-IPO and secondaries) — and the risks of each, including concentration and illiquidity.
How to invest in AI startups: 5 legal routes (and who each suits)
Five real ways to invest in private AI startups — equity crowdfunding, angel investing, syndicates and SPVs, secondaries and pre-IPO funds — with the access requirements and trade-offs of each.
Pre-IPO AI stocks: how to buy private shares
OpenAI, Anthropic and SpaceX-type companies are private — but there are real ways to get exposure before an IPO. The legitimate routes, the gatekeeping, and the risks nobody advertises.
Tool reviews
2Agentic engineering vs. agentic washing: how investors tell the difference
"Agentic" is on every pitch deck now. A practical framework for investors and decision-makers to separate real agentic-engineering competence from marketing relabeling, grounded in 2026 adoption data.
Best AI tools in 2026: how to choose (and the traps to avoid)
There are thousands of 'AI tools' and most reviews are affiliate listicles. A practical framework for choosing AI software by the job it does, with the buying traps that waste money.