Are you using AI to think more; or think less?
At our kick-off event on May 17, @baibhavbista , Member of Technical Staff at Roam Research, will be talking about cognitive delegation vs surrender.
⌛Deadline: May 10
Register: https://t.co/TqzbK5piKa
The long term value of Recreational Programming (apart from enabling you to enjoy what you are doing again) comes from allowing you to explore unusual things outside of the local optimum that the market pressure forces you into.
Really solid insights on AI agent context engineering here.
Faced some weird hallucinations on a recent project - we were accidentally "few shotting" ourselves with poor context management.
Cool to see this pattern getting a proper name.
After four overhauls and millions of real-world sessions, here are the lessons we learned about context engineering for AI agents: https://t.co/Ql014rEzBQ
#LSPPDay08
light day today
read part of 12-factor-agents: https://t.co/3hhW6glzOg
It talks about owning the prompt, context and control flow rather than handing to to a library, as it gives us more room for experiments.
#60DaysOfLearning2025#LearningWithLeapfrog@lftechnology
#LSPPDay07
Read a paper from Apple demonstrating complete accuracy collapse of LLM/LRM's reasoning capability once problems become complex enough.
For this, they used the famous Tower of Hanoi problem. That reminds me
#60DaysOfLearning2025#LearningWithLeapfrog@lftechnology
#LSPPDay06
Talks on LLM Evals
One intriguing analogy compares LLM outputs to basketball shots on a court.
Showcasing
- inherently unreliable - even pros miss shots
- Making sure we cover the important parts of the Court
#60DaysOfLearning2025#LearningWithLeapfrog@lftechnology