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Both 'AI agent' and 'automation' can look identical on a slide. They aren't. Here's the framework I use with clients to pick the right one per workflow — and why most teams end up running both.

If you've heard the term 'AI agent' thrown around in 2026 and aren't sure what's actually new vs repackaged ChatGPT hype, this is the orientation piece. Written for business leaders, not engineers.

Most businesses who ask 'should we be using AI agents?' get pitched by a vendor with an obvious incentive. This piece is a no-incentive readiness check — 10 yes/no questions with honest interpretation.

Most companies waste their first agent on something too ambitious. Here are five scoped first agents that tend to work, in the order they tend to work, with what to expect from each.

The free preview ended and the credit clock started ticking. Here's the practical math on what agents actually cost in production, with real usage patterns and how to avoid surprise bills.

Most companies that try AI agents in 2026 produce something that works in a demo and dies in production. The failure patterns are predictable — and avoidable if you know them.

One of the cleanest ways to understand Workspace Agents is to watch a Custom GPT get migrated. Here's what that actually looks like, with the gotchas that surprised us.

'Let's watch the space for a quarter' sounds prudent. At real SMB volume, six months of wait costs more than a year of agent licenses. Here's the math.

'The agent ran 847 times this month' is not ROI. Here's how to tell if your agent is actually delivering value, with metrics that survive a skeptical CFO.

Teams agonize over 'which 10 tools should we connect first.' The honest answer: four tools unlock most of the value, and the rest is diminishing returns.

Public-facing AI agents are the most tempting, highest-risk first build. Internal agents are the unglamorous, highest-ROI first build. Why the boring choice wins.