Applied AI Cohort 6 adds Jev and Clairic to its curriculum
Arpit Bhayani's applied AI cohort adds sessions on Jev and Clairic, long-running agents, multi-agent decomposition, memory paths and cost efficiency, starting November 14.
Given how quickly AI is advancing, I am adding a bunch of super interesting topics to my upcoming Applied AI Cohort 6. Here's a glimpse... 1. How Claude Code Works 2. Jev and Clairic 3. Parallel, Sub, and Long-Running Agents 4. Multi-agent Task Decomposition 5. Production Issues in Multi-Agent Systems 6. Memory Write and Read Paths 7. Agent Reliability 8. Cost Efficiency Over the last five cohorts, I have continuously refined the content based on feedback, production learnings, and countless technical discussions with participants. With every cohort, the goal has been to make the content more practical (testimonials reflect the same), relevant, and closer to the problems engineers are solving in the real world. The goal is simple: "I know how to call an LLM API" -> "I can design and build production-grade AI systems." The cohort is extremely practical. We spend very little time on slides and almost all our time reasoning about production problems, writing code, dissecting real systems, discussing trade-offs, and understanding why certain approaches fail in practice. The focus is on building the right mental models and developing an intuition that stays useful even as models and frameworks evolve. Cohort 6 starts on 14th November. Curriculum, schedule, testimonials, and enrollment details are available here: http://arpitbhayani.me/ai