The Great Unbundling of AI & GPT-5
Your single co-pilot is becoming a specialist toolkit.
While the "almighty" GPT-5 has been announced, the very idea of a single, all-powerful AI assistant might be becoming obsolete as we move towards specialist models.
The GPT-5 Induced AI Coding Showdown Reveals a Deeper Truth
Developers are realising we need a toolkit of AI specialists, not one generalist co-pilot.
A debate comparing GPT-5 with Claude Code revealed the future of development. The consensus is that different AI models are needed for different tasks. A faster model might be better for quick bug fixes, while a model with deeper context is essential for architecting entire applications from scratch.
This isn't about which AI is 'better', it's about a fundamental shift in how we work. The real story is the move from a single AI co-pilot to an entire garage of specialised tools. We are quickly entering an era where the most valuable skill isn't just prompting, but knowing which AI to deploy for which specific job, just like knowing when to use a wrench versus a screwdriver.
The dream of one AI to rule them all is dying. In reality, developers are becoming conductors of an AI orchestra, choosing the right instrument for each part of the code. This changes how we should evaluate these tools – not on abstract benchmarks, but on their fitness for a specific purpose in our workflow.
The AI Content Factory
Meanwhile, AI is systematically industrialising every aspect of content creation.
Hera: Your new AI motion designer.
This isn't just another video generator; it creates code-based animations. It gives you AI speed without sacrificing the granular control needed for professional work, challenging tools like After Effects.
Vireel: A cheat code for viral videos.
Vireel aims to automate the creation of TikToks and Reels by baking in viral formulas. It democratises high-engagement video, lowering the barrier for brands but also raising the noise floor for everyone.
Wepost: An AI publicist for your personal brand.
This tool automates content creation and scheduling across multiple personal profiles. It signals a future where an AI manages your entire personal brand lifecycle, making strategic posting accessible to everyone.
Building the New AI Plumbing
With the novelty wearing off, developers are now building the critical infrastructure to make AI actually usable.
Dereference: A command centre for your AI coder.
This is a 'prompt-first IDE' built specifically for Claude Code. It’s a sign of maturation in the market, moving beyond generic integrations to specialised workflows that treat the AI as a first-class citizen.
SelfHostLLM: A GPU calculator for your self-hosted models.
A simple tool that tells you exactly how much GPU memory you need to run open-source models. It removes the expensive guesswork from self-hosting, making decentralised AI more practical and less of a headache.
Wordin: The AI writer that actually remembers your story.
AI writers struggle with long-form narrative consistency. Wordin tackles this by embedding the live document for context, solving a huge pain point for anyone trying to write a book or screenplay with an AI collaborator.
Quick hits
The 7-Year Overnight Success: Stop building in an echo chamber.
A founder’s story about finally finding success after seven years proves that solving a real user problem always beats chasing a cool idea.
Bublr: A digital garden to escape the algorithm.
This minimalist, open-source writing app is part of a growing "anti-social" trend, prioritising quiet, evolving thought over performance metrics.
Click to Woof: The perfect anti-productivity app.
Created as a protest against the endless stream of AI tools, this website does nothing but make a dog noise, and is a perfect palate cleanser.
My takeaway
The era of the single, all-powerful AI assistant is a fantasy.
We're rapidly moving towards a world of specialised AI agents, each designed for a specific task. The hype around one model being 'the best' is a distraction from the real story. The smart move is to stop looking for a silver bullet and start building a bespoke toolkit.
This requires a new skill: not just prompting, but strategically deploying the right AI for the right job. It's less about being a magician and more about being a master mechanic. That means getting good at diagnosing a problem and knowing exactly which tool will fix it.
What's the most glaring gap in your own AI toolkit right now?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().