Inside LLMs: Psychology & Limits, Prompts, GUI, and Agent Evals | Ep. 13
Description
In this episode of the Agent Workforce Podcast, Kristiina and Niko reunite to discuss the latest in LLM trends, model chaos, and real-world AI adoption. From Karpathy’s Y Combinator summer school talk to what’s actually inside a system prompt, we cover a lot of ground — including energy use, pricing shifts, and the surprising rise of OpenEvidence as the go-to tool for U.S. physicians.
Plus: insights into Sam Altman’s comments on AI resource use, GPT-4 pricing shifts, and why evals are actually the unsung heroes of scalable AI solutions.
🔍 Topics include:
Karpathy’s Y Combinator summer school talk: “software is changing again”
The evolving GUI of LLMs & user autonomy
How much energy ChatGPT really uses
OpenEvidence is becoming the “search bar” for U.S. doctors
03 model price drops and selection confusion
Prompting at different levels (system, user, custom GPTs)
How Agent Workforce agents are built under the hood
The role of evals in building trustworthy agents
A quick summer sign-off and a shoutout to agentacademy.ai
United States
