1. so far enterprise AI projects I worked on are generation: given X, output Y.
2. to make the predicted Y better, prompt engineering and context engineering are performed. this spans across projects with evidence extraction, tags generation, and recommendation.
3. the next step is execution: given a process P, deliver outcome O. This is basically the agent systems.
- How do we build enterprise-level agent systems?
- What are the right workflows to target?
- How do we define that workflow, executable by AI, and make sure guardrails and safety nets are in place?
4. As I mull over the next project to work on, agent systems seems like an interesting candidate.