Andrej Karpathy observes a significant disparity in how people perceive LLM capabilities, ranging from derpy chatbots for the general public to stunning advancements for a small group of professionals. Immersion courses at events like Foocamp aim to teach developers agentic engineering, focusing on the emotional impact of changing software development identities. Large enterprises, however, are slow to adopt this technology, likened to using only a toothpick from a Swiss army knife, due to data quality and security concerns. The current AI boom is compared to the dotcom era, with high valuations and a potential bubble, yet significant long-term investment potential. Adam Tornhill suggests that programming is evolving, emphasizing problem-solving and system understanding over mere code writing, separating identity from the act of coding. Tim Bray expresses ethical discomfort with GenAI, citing its use by "terrible people" to slash payrolls and its contribution to climate change. Annie Vella frames AI-assisted software development as a shift from direct to supervisory control, where AI agents close the loop. She outlines a five-level model of AI automation, cautioning that AI agents' accounts of their actions are not always accurate, emphasizing the need for redesigned job roles and control systems. Eric Evans explores the future by examining domain language in code repositories to analyze bounded contexts. Thoughtworks is developing a token sourcing strategy to reduce future LLM costs by renting frontier models and running open-weight models on owned infrastructure based on workload classification.