AI Gets a Job
The hype is over. The real work begins.
Now we have to build the plumbing to make the tricks work every time.
An AI with 27 Million Parameters Is Outperforming the Giants
A new brain-inspired model challenges the industry's 'bigger is better' obsession by being smaller, faster, and smarter on specific tasks.
A new model with just 27 million parameters is running circles around giants like ChatGPT on complex reasoning tasks. The Hierarchical Reasoning Model (HRM) solves extreme Sudoku and navigates massive mazes with near-perfect accuracy, all while being around 100 times faster. It does this with a brain-inspired design that requires shockingly little training data.
This isn't just another clever model; it’s a direct challenge to the brute-force scaling that defines the current AI race. The industry assumes progress means exponentially larger models, but HRM suggests an alternative path. We could see a future of small, hyper-efficient, specialised AIs that are cheap to run and accessible to everyone, rather than just a few tech giants.
What's actually happening is a quiet decoupling of general intelligence from specialised problem-solving. While massive LLMs are great generalists, HRM proves that purpose-built models can dominate specific domains. This is for developers who need powerful reasoning on devices with limited resources, not another chatbot.
The New AI Control Panel
With all these new AI models, the real challenge is making them actually work together reliably.
Sailhouse: The control plane for unruly AI agents.
Managing one AI agent is hard; managing a fleet is chaos. Sailhouse provides the essential infrastructure to coordinate agents, handle errors, and make multi-agent systems work in production without building it all yourself.
ClueoAPI: Finally, an AI with a consistent personality.
A consistent brand voice is impossible when every AI response sounds generic. ClueoAPI gives developers a control panel to inject a specific, stable personality, moving beyond simple prompts to create truly memorable AI interactions.
Augmenting Your Brain
Beyond the infrastructure, a new class of tools is using AI to help us think and create more effectively.
SciSpace Agent: The AI research assistant you actually want.
Drowning in academic papers is a universal problem for researchers. This agent promises to cut research time by 90 percent by automating literature reviews and data analysis across countless sources.
Spill: A brain dump app with a voice.
This minimalist writing app encourages getting thoughts down without friction. Its unique feature is letting you listen back to your own freewriting, providing a new way to reflect and find clarity.
Quick hits
Accidental Market Validation: Fake pricing page lands real customers.
A founder's placeholder pricing page accidentally validated strong market demand, proving raw feedback is more valuable than a polished, un-launched product.
Verbite: AI that turns transcripts into SEO gold.
This tool transforms raw audio and video transcripts into publish-ready, high-ranking content, solving a huge content repurposing problem for marketers and educators.
PromptPlex: Your messy prompts finally organised.
As prompt engineering becomes a core skill, this tool acts as a command centre to save, search, and manage your best prompts across different AI models.
My takeaway
The AI industry is shifting from demonstrating raw capability to delivering real-world value.
The initial spectacle of watching an AI write a poem is over, and we are now in the much less glamorous, but far more important, construction phase. The real work involves building the control planes, management layers, and specialised models needed to make AI reliable and useful. This is about turning a captivating magic trick into dependable global infrastructure.
This shift means the biggest opportunities are no longer just in building the largest model, but in creating the smartest plumbing and the most focused applications. Are we paying too much attention to an AI's theoretical IQ and not enough to its actual job description? It's time to stop being impressed by the technology and start building things with it.
What's one tedious part of your job you wish a small, specialised AI would just take over completely?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().