Blogs

Witty, slightly sarcastic takes on all things AI — from buzzwords to buyer’s guides, hallucinating chatbots to agentic assistants. If you’re a marketer wondering what LLMs have to do with ROI (and chai), you’re in the right place.

Side-by-side comparison showing a curated demo environment with smiling team members and green status indicators versus grainy CCTV-style footage of a 3:47 AM incident with error dashboards, cold pizza, and engineers rolling back deployment

Your AI Coding Demo Looked Perfect. Your Production Deployment Is a Mess. Here’s Why.

AI coding demos look magical: agents fixing builds, shipping features, and letting developers “stay in flow”. Reality is messier. Teams see more debugging, governance headaches, and underwhelming ROI. This piece breaks down the demo-to-production gap—and what engineering leaders should actually do about AI coding tools.

Your AI Coding Demo Looked Perfect. Your Production Deployment Is a Mess. Here’s Why. Read More »

"Split-screen infographic contrasting agent sprawl chaos on the left showing 2.5 million interconnected agents with cost spiral warnings versus organized governance structure on the right with Slackbot orchestrator centre, illustrating why governance gaps cause implementation failures

Why Slackbot’s AI Hype Is Already Failing—and What That Means for Your Workplace

Salesforce’s new Slackbot promises to be your “AI agent for work”—but the marketing hides a troubling reality. Enterprise AI adoption has surged 13% while worker confidence collapsed 18% simultaneously. Research reveals that 87-95% of enterprise AI projects fail to scale beyond pilot phase, and only 14% of workers achieve net-positive outcomes from AI use. Slackbot’s core claims rest on assumptions that workplace research systematically disproves: hallucination rates remain dangerously high, rework consumes 40% of productivity gains, and the tool creates new forms of context switching rather than eliminating them. Most damning, Salesforce itself admitted it “massively overestimated AI’s capabilities.” Before your organisation adopts Slackbot, understand what research reveals about enterprise AI implementation failures, trust gaps, and the governance infrastructure actually required for success.

Why Slackbot’s AI Hype Is Already Failing—and What That Means for Your Workplace Read More »

Microsoft operational focus vs Google conceptual focus comparison

How tech giants teach: what a week watching Microsoft and Google’s developer channels revealed about authenticity

Yesterday, I published my analysis of Google’s timeline problem—how Aniket’s story compressed “2-3 weeks from zero coding to Android app winner,” creating a 92% gap between marketing promise and educational reality.

But that raised a question: Is this how these companies actually teach developers? Or just how they market to them?

So I spent the past 24 hours watching both Microsoft Developer and Google for Developers channels obsessively. Not hunting for gotchas—just observing what they publish, how they frame it, who presents it, and what they promise.

What I found: Both companies teach from fundamentally different philosophies about what developers need and how they learn best. Microsoft optimises for operational realism. Google optimises for conceptual foundations. Neither is dishonest. Neither is wrong. But they serve completely different types of learners.

How tech giants teach: what a week watching Microsoft and Google’s developer channels revealed about authenticity Read More »

AI agent funnel collapse from traditional 12-touchpoint customer journey to single API call in 2.3 seconds, showing paradigm shift in e-commerce.

Your Customers Are Becoming Agents—And You’re Still Selling Like It’s 2019

A meaningful share of customer interactions will happen agent-to-agent in 2026. Not human-to-agent. Agent-to-agent. This isn’t futurism—it’s reality emerging in e-commerce, financial services, and enterprise software sales right now.

The implications for marketing are staggering. Your carefully constructed funnel—landing pages, email sequences, retargeting ads—collapses into a single API call. An AI assistant saying “find me a standing desk under £800” queries multiple retailers simultaneously, compares specifications, checks inventory, and completes the purchase. Your attention-grabbing photos never load. Your persuasive copy goes unread. There’s no browser session to track.

Welcome to “Share of Model”—the new metric for how often AI systems recommend your brand. Search engine optimisation becomes irrelevant when there’s no search results page. Ad targeting loses purpose when autonomous agents comparison-shop based on structured data feeds, not browsing behaviour. The competitive moat is speed: agents route transactions to whoever responds first with complete, accurate data. Second place might capture 10% of the winner’s volume, not 90%.

Your Customers Are Becoming Agents—And You’re Still Selling Like It’s 2019 Read More »

AI agents leaking marketing data while appearing to securely organise campaign files.

Anthropic Just Launched an AI That Can Delete Your Files—And Marketers Are Rushing to Use It

On 12 January 2026, Anthropic launched Cowork—an autonomous AI agent that manipulates files and executes tasks across your desktop. Marketing teams immediately saw the appeal: automatic expense reports, organised campaign assets, drafted reports from scattered notes. But within 72 hours, security researchers demonstrated something terrifying: hidden instructions in a PDF could make Cowork silently upload files to an attacker’s account.

This collision defines 2026’s marketing technology crisis. Adoption is accelerating—72% of marketers identify generative AI as their top trend, 33% have already implemented AI agents. Yet security infrastructure lags dangerously behind. Sixty-seven per cent of AI usage happens through unmanaged personal accounts. Copy-paste has become the primary data exfiltration channel, bypassing traditional DLP tools entirely.

The fundamental problem: marketing AI agents don’t just analyse—they execute. They send emails, modify CRM records, trigger campaigns, and adjust segmentation logic. When compromised through prompt injection, they act on adversarial instructions that appear to be normal operations. And marketing teams lack the threat modelling expertise to identify when their AI has been weaponised against them.

Anthropic Just Launched an AI That Can Delete Your Files—And Marketers Are Rushing to Use It Read More »

Apple iPhone 17 Ceramic Shield 2 advertisement split-screen analysis showing two lawyers in mahogany conference room with iPhone positioned as bridge between institutional power and personal agency

Apple’s 35-Second Divorce: What Ceramic Shield 2 Is Really Selling

Apple’s new iPhone 17 advertisement lasts 35 seconds. Two lawyers. One phone. A mahogany-paneled room. The premise: a divorce negotiation where the phone slides across the table twice—once with the offer, once with the rejection. The company chose to show Ceramic Shield 2 surviving not a drop or a scratch, but the legal dissolution of a marriage. This is either brilliant or cynical. Possibly both. The ad understands what most brands miss: people don’t buy products for specs. They buy for the fantasy that invulnerability is possible—that at least one thing you own will survive the end of everything else. While marriages dissolve and fairness expires, the phone emerges pristine. It’s not selling durability. It’s selling the promise that something can remain intact when everything else breaks. For $999 and up.

Apple’s 35-Second Divorce: What Ceramic Shield 2 Is Really Selling Read More »

I Misread Apple’s Creator Studio. The Correction Is Worse Than the Original Take.

Apple’s Creator Studio looked like a straightforward blunder yesterday. Today’s piece reveals something more unsettling: Apple may have read India’s metro creators perfectly—and is betting on a financial moment that cannot last.

The original critique was that emerging markets value ownership, Apple sells subscriptions, so the strategy fails. But the data tells a different story. Gen Z in Tier 1 cities has already normalised EMIs, BNPL and subscription stacks. For them, ₹399 monthly fits seamlessly into an existing borrowing culture.

Here’s the uncomfortable part: that culture is temporary. China’s Gen Z shifted overnight from “revenge spending” to “revenge saving” when economic uncertainty hit. India’s metros show the same vulnerability. Apple can absorb that shift. Most subscription businesses cannot. This follow-up piece explores what marketers should learn from Apple’s timing bet—and why copying its surface strategy could be dangerous.

I Misread Apple’s Creator Studio. The Correction Is Worse Than the Original Take. Read More »

Timeline visualization showing Apple Creator Studio subscription costs accumulating from ₹4,788 in Year 1 to ₹38,304 by Year 8, exceeding Final Cut Pro perpetual license (₹29,900) at Year 6 and both Final Cut Pro and Logic Pro combined (₹47,500) by Year 8, with callout showing subscribers own nothing after payin

Apple’s Creator Studio is a subscription Trojan horse—and marketers should be worried

Apple just turned a quiet business model pivot into 35 seconds of beautiful misdirection. Creator Studio looks like a bargain bundle, but for marketers in India and other emerging markets, it’s a warning: subscriptions are colliding with hardware lock-in, purchasing power reality and a creator economy that’s already moved on from Mac-dependent tools.

Apple’s Creator Studio is a subscription Trojan horse—and marketers should be worried Read More »

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