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AI is everywhere in this week’s dispatch – tripping up media, creeping into consulting and even rewriting how we pitch ourselves to machines that scan CVs. But the bigger story isn’t the tech itself, it’s how quickly it’s reshaping the rules for founders, workers and brands. From content crunches to leadership shifts, the pace of change is relentless – and the smartest players are already adapting.

Enjoy!

Momentum, not features, is today's consumer AI advantage

In consumer AI, the strongest defence isn’t code or capital – it’s momentum. Bryan Kim at a16z argues that features can be copied and models commoditised, but capturing distribution and user attention early creates a compounding edge. For example, Perplexity has shown how quickly a product can become the default for a new use case, while Midjourney demonstrates the pull of a distinctive community around an experience. In this market, the moat is not technology but trajectory – the ability to launch quickly, expand relentlessly and stay top of mind as new waves of users pour in. Find out more here.

AI’s uneasy place in media and consulting

AI may be reshaping industries, but its limits are being tested in real time. Wired and Business Insider recently withdrew a tranche of AI-written freelance articles after readers spotted errors and questioned quality, raising awkward questions about whether cost savings outweigh reputational risk. The episode shows that while AI can accelerate production, editorial trust is harder to automate. At the other end of the spectrum, Futurism reports that McKinsey has been running internal analyses on how far AI could replicate its own consulting work. Early findings suggest parts of its high-margin advisory business – from research to strategic modelling – may one day be automated. Taken together, these cases underline a paradox: companies are racing to deploy AI, yet they are simultaneously discovering how exposed their own models are to disruption by the very tools they are adopting.

Cutting through the clutter of productivity apps

Tech writer Casey Newton’s annual reflection on productivity arrives amid a crowded field of “tools that save time,” but his account is unlike any roundup. He opens with what he’s stopped using – the time-sink apps that disguised busyness as momentum – and builds to what remains essential. For example, Raycast, his keystroke launcher and AI assistant, still dominates his workflow, saving seconds that add up, even as he double-checks every fact it surfaces. Throughout the article, Newton balances personal insight with practical advice, offering clarity on when these apps enhance your work and when they distract. Start building your own productivity engine by reading the piece here.

Apple calls out AI’s “illusion of thinking”

Apple researchers have published a paper arguing that today’s most advanced reasoning models often project an “illusion of thinking”. While they excel at short, structured tasks, the study finds they collapse once the number of steps grows or the context becomes messy. The risk is that performance in demos or benchmarks creates false confidence when systems are deployed in the wild. For businesses, it’s a timely reminder that while reasoning models can certainly boost productivity, they still shouldn’t be left in charge of complex or high-stakes decisions. Over-automation without safeguards could magnify errors rather than reduce them.Read the white paper here.

Work-life balance is for underachievers, says entrepreneur

Emil Barr, a 22-year-old founder who has already built two companies worth more than $20mn, claims that “work-life balance” is a trap. His approach was to front-load his 20s with extreme intensity – sleeping 3½ hours a night, outsourcing every non-essential task and even using helicopters to save time. The results were striking, but so were the costs: weight gain, anxiety and social isolation. Barr insists the trade-off bought him compounding advantage and a shot at financial freedom by 30. For most entrepreneurs, though, his story underlines a tension rather than a template – between the allure of rapid wealth and the risks of burning out before you get there. The WSJ has the story (use archive if you don’t have a subscription).

The content crunch

A new survey from Statista shows the pressure for brands to produce content is intensifying. More than half of marketers say they can’t keep up with the demand for high-quality material, while others are held back by outdated tools and weak ROI tracking. The demand isn’t abstract: algorithms reward frequency, audiences expect a steady stream of relevance and competitors are quick to fill any silence. For growth-focused firms, this raises the bar – the challenge isn’t just creating more, but creating better, with smarter processes, sharper ideas and clearer measures of success. The survey itself is gated but there’s a good overview of it here.

When your content exists but AI can’t see it

Search Engine Land points out a growing blind spot in content strategy: AI search engines scan plain HTML, not JavaScript widgets or hidden slide decks. One site’s beautifully designed explanation of a framework was visible in browsers – but invisible to AI – forcing the brand to buy ads on its own search. The authors offer a 30-minute fix: put essential ideas into visible headings and bullet lists, add FAQ markup and schema and test by inspecting page source. Making your content AI-readable isn’t about fancier design; it’s about staying discoverable in the future of search. Get the guide here.

How to write a CV for hiring algorithms

Recruiters aren’t always the first to read your CV anymore – software is. Applicant-tracking systems and AI filters now decide which candidates make it to the short list, often based on whether your wording matches the keywords in a job description. The Register notes that too many applicants still write in ways machines don’t understand, which means their skills go unseen. The fix is simple: use clear job-relevant phrases, spell out tools or achievements in plain English, and think of your CV as being read by an algorithm scanning for fit as much as by a hiring manager looking for personality. Read the article here.

AI prompt of the week: the decision diary

One of GPT-5’s biggest upgrades is its ability to reason in steps and surface hidden assumptions. That makes it the perfect tool for those of us facing tough trade-offs. Instead of asking for pros and cons, try using it as a “decision auditor” – a way to test your thinking and catch what you might have missed.

Act as a decision auditor. Here’s the decision I’m facing: [describe].
Step 1 – Map out all the realistic options I have.
Step 2 – For each option, analyse first-order outcomes (immediate impacts).
Step 3 – Highlight second-order consequences (knock-on effects 6–18 months out).
Step 4 – Surface hidden assumptions or blind spots I may be overlooking.
Step 5 – Recommend questions I should ask my team or investors before deciding.

Leadership that fits the stage

Founders don’t lead the same way at 10 employees as they do at 1,000. The challenge is knowing when to shift modes. This handy guide helps you flex across management styles without losing focus.

Drop me a line

That’s a wrap for this week. I’ll be back in your inbox next Sunday with more interest-piquing insights. Until then, keep me posted on what you’re noticing.

Cheers!
Adam

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