Building the World's Next AI Backbone

"Write a one-line update explaining your product without using the words AI, automation, smart, or platform." A great way to pressure-test whether your value prop actually stands on its own.

Hallucination Budget:
The acceptable margin of error an AI system is allowed to have in a real- world workflow. In high-stakes use cases, that budget should be close to zero. THE ALIGNMENT PROBLEM How Can Artificial Intelligence learn Human Values?

Read: "The Alignment Problem" by Brian Christian:
An accessible look at how AI systems learn values, make decisions, and sometimes get it very wrong. Great for anyone deploying AI responsibly. RRIANCHRISTAN

Google has been pushing on-device AI for voice and vision, meaning more inference happens directly on the user's device instead of the cloud. The big shift? Faster responses, lower latency, and fewer privacy trade-offs especially important for real-time voice agents!

What it is:

A next-generation, AI-native CRM that feels more like Notion than Salesforce. It is fully customisable, allowing you to build your own data models and workflows without needing a team of consultants. Attio

How you can use it:

Instead of manually entering data, you can sync your email and calendar to automatically populate relationships. You can then use its built-in AI agents to "enrich" your leads, for example, ask it to "Find the estimated revenue and key stakeholders for every company in this list."

Good for you if:

You are a startup founder or GTM builder who hates the rigidity of traditional CRMs and wants a flexible, data-rich workspace that automates the boring parts of sales.

Salesforce bet the farm on AI agents, but now they're pumping the brakes. After cutting 4,000 roles to focus on "Agentforce," executives admitted this week that current models are getting confused, drifting off task when things get complicated. They aren't ditching AI, but they are pivoting back to hard rules and strict guardrails rather than relying on open-ended chat for critical business tasks.

What Ringg thinks:

This isn't a failure of the technology; it's a correction of the strategy. We spent 2024 thinking AI was a magic wand that could replace workers entirely. Salesforce just proved that LLMs are powerful engines, not autonomous drivers. The "fire everyone and let the bot run it" approach is over. The winning play now is "Augmentation" or using AI to make your best people faster, rather than trying to replace them with a slightly confused chatbot. Reliability is the new hype.