AI Methodologies: Build your Team

A Practical Method: Invest in the Agentic Layer

In many cases, the fastest way to ship reliably with AI is to improve the layer around your systems that agents use: prompts, tool interfaces, guardrails, and verification. Instead of treating each AI interaction as a one-off, aim to make common work repeatable and measurable. When appropriate, spend a meaningful share of engineering time strengthening this layer so the next feature takes less effort and carries less risk.

Habits:

• Identify recurring “problem classes” (provisioning, config changes, incident response, routine updates) and capture them as templates with clear inputs/outputs.
• Treat prompts and tool calls like code: version them, review them, and define constraints (allowed actions, data boundaries, expected artifacts).
• Build verification into the default flow: automated checks, policy checks, and structured acceptance criteria before anything lands.
• Prefer composable primitives (small tools, clear contracts) over single large prompts that try to do everything.
• Track outcomes with lightweight telemetry: time saved, defect rates, rework frequency, and where agent output needed human correction.
• Regularly ask: “Am I solving this once, or building the reusable path that solves it the next 20 times?”