AI agents need better work flow, not just better code skills
AI agents can write code, but real company work is larger than writing code. Useful work includes understanding the , knowing who owns each area, deciding when not to change something, waiting for approval, judging risk, explaining why a change is safe, and coordinating across teams. Many current agents still feel like powerful tools inside a terminal.
They run commands and edit files, but they may guess, repeat actions that should not be retried, or fail to know the right next step when blocked. The more likely future is not one giant agent replacing everyone. A more practical setup is several agents working with people, such as a , review agent, security agent, docs agent, agent, and team-specific agents.
For that to work, agents need more than tools; they need identity, , and an understanding of which , file, or area belongs to whom.
Key points
- AI agents can write code, but they also need to understand , approval, and risk.
- Current agents can guess, retry the wrong action, or get stuck without knowing whom to ask.
- A set of role-based agents may work better than one all-purpose agent.
- Agents need identity, , and clear responsibility boundaries.
- Better workflow design can reduce wasted tokens and failed agent work.