Your Brand's Newest Problem Is an AI's Opinion

The next wave of marketing isn't about getting found on Google; it's about controlling your narrative inside the black box of AI.

Search engine optimisation is getting a rewrite. As AI models become the new front page for information, your ranking on Google matters less than the summary an LLM spits out. This is the problem tools like ReachLLM are built to solve, letting you audit and analyse how models like ChatGPT or Gemini represent your brand.

This isn't just a new channel to manage; it's a fundamental shift from discoverability to algorithmic reputation. We've moved from optimising for keywords to trying to influence an AI's perception, which is a much fuzzier and more dangerous game. When an AI can confidently lie or misrepresent you, passively waiting for users to find your website is no longer a viable strategy.

The real story here is the emergence of a new tooling layer for the AI economy. Marketers, brand managers, and PR teams are the first to need it, but they won't be the last. Most companies are completely unprepared for a world where their brand is defined by a machine's summary.

Read more →

Your New AI Creative Department

AI is moving from a novelty to a practical co-pilot for creative work, turning simple prompts into complex assets.

Madespace: The AI interior designer in your pocket.

This is about democratising a high-cost service, making interior design accessible. The real test will be bridging the gap between a stunning AI render and a practical, liveable space that doesn't suggest moving a load-bearing wall.

DreamFlow: A Hollywood makeover for your static maps.

This shows the power of specific, applied AI. It turns boring data into a compelling narrative tool, giving industries like real estate and tourism a way to create cinematic flyovers without a drone pilot.

ToMoviee: The all-in-one AI creative suite.

An 8x speed boost is seductive, but the real question is whether it produces generic content or genuinely useful creative assets. The goal isn't just faster output, but a fundamentally better workflow.

Putting a Leash on Tech

As tech gets more invasive, a counter-movement for focused, private, and user-controlled tools is quietly growing.

Daily Grind: The time-tracker that minds its own business.

This is a direct response to the subscription-heavy, cloud-first default. It's proof that a market exists for simple, private tools that do one job well without harvesting your data.

Kaizen Protect: A screen time manager that works offline.

The offline functionality is the killer feature here. It's a powerful statement about user control and privacy in a world where even parental control apps want a constant connection.

Quick hits

Marxx AI: Your new ad spend analyst.
This uses AI to explain precisely why your ads are failing, finally moving marketers from just guessing to actually knowing.

FishPic: A Shazam for fish.
Instantly identify a fish, its edibility, and local regulations, because nobody wants to accidentally eat something they shouldn't.

Global AI News: A dedicated firehose for AI news.
A free aggregator for when you need to keep up with the frantic pace of AI without the noise of multiple feeds.

My takeaway

The most interesting work is happening in the messy middle, turning raw AI power into focused, reliable tools.

We spent the last couple of years amazed that AI could generate an image or write an essay. Now, the novelty has worn off, and the hard work of building useful things has begun. This new wave of tools isn't about magic; it's about control, application, and building guardrails.

This means the real opportunities are shifting from foundational models to valuable applications built on top of them. The next breakthroughs might feel less like sorcery and more like really good plumbing. And honestly, good plumbing is much more useful.

Are we focusing too much on the power of the core AI, and not enough on the user-facing tools that actually solve a problem?

Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().