Agentic Coding Mag — Page 3

Multi-agent systems cut refactoring complexity in half compared to single-agent approaches.

How startups can build sustainable practices around AI agents before their edge decays.

Agents now handle entire development tasks, but teams must review output to avoid bottlenecks.

Autonomous AI now executes full development tasks while humans set direction and verify results.

Debugging agents can be hijacked through untrusted logs and tool output.

Agents iterate dozens of times per commit, making pipeline speed the real bottleneck.

Humans need checkpoints, not just oversight, to make agent pipelines work safely.

Telling data drift from concept drift is how you fix the right problem in coding agents.

Static analysis must evolve to catch bugs agents write before humans ever see them.

Misreading the rules file setup means your agent acts wrong for dozens of steps before you notice.

Rising throughput can mask quality problems and wasted work that dashboards don't measure.