Agent readiness before you scale AI
Agentic workflows fail fast when data access, ownership, and logging are unclear. A short readiness sprint surfaces the gaps before production.
Agentic AI is moving from demos to day-to-day workflows. The hard part is not prompt quality but what the agent can touch, who owns decisions, and how you trace its actions.
Run a two-week readiness sprint
Week 1: map data sources and permissions. If an agent can read a system, it can also leak it. Decide what is allowed and what needs approval.
Week 1: define action boundaries. Which actions can run automatically, which need human confirmation, which are blocked.
Week 2: log what matters. Store prompts, tool calls, and outputs in a place your security team can audit.
Week 2: agree on cost and latency budgets. Agents that hit the best answer but miss response time will still fail in production.
What you get out of it
With these basics in place, you can ship a thin production slice and learn fast. Without them, you get noisy demos and little trust.
If you want a fast, structured checkpoint, we run an Agent Readiness Sprint that ends with a concrete backlog.
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