Agentic tools can perform much of a data scientist's research and analysis cheaply. The leverage comes from framing the question and checking the result.
Summary: Agentic tools can perform much of a data scientist’s research and analysis cheaply. The leverage comes from framing the question and checking the result.
AI performance depends less on clever prompts than on context. Give models the right goals, examples, constraints, history, and tools so they can act effectively.
Agents turn LLMs from answer generators into workers that use tools, execute multi-step tasks, and recover from failures. The challenge is control and verification.
I learned that harness design now matters more than prompt design, how Codex's new controls improve agent work, why mental closure helps intense conversations, and a faster way to search files.
I learned to ask what others and I must take away from conversations; linked data and AI make taxonomies useful; Bitwarden’s CLI avoids plaintext passwords; flipbook.page offers visual exploration.
