Multimodal agents shatter the span tree the moment voice, vision, and LLM each open their own root. The fix is a turn ID, attached artifacts, and one owner for the join.
Your token bucket measures user clicks; the bill measures model calls. When a single click fans out into thirty calls, the limiter at the HTTP boundary becomes a paper umbrella.
Your team's stated AI capability is the maximum of its members' skill, while delivery velocity is the median — and that gap is the most underpriced risk on your roadmap.
Six months ago your prompt prefix was 4k tokens and amortized to nearly free. Today it is 11k tokens, your cache hit rate is 31 percent, and nobody can point to the PR that did it.
Wiring an AI agent into CI with merge rights creates a new operational class your SRE runbook never named. Type its actions, queue what cannot run unattended, log every change with attribution, and rehearse the kill switch.
A tool nobody owns can sit in your shared agent catalog forever, taxing every inference in tokens, selection accuracy, and security surface. Build the deprecation lifecycle that lets you remove it.
Your AI feature has an undocumented contract with its users, encoded in the system prompt. A small fraction of patient users reverse-engineer it; the rest get a worse product. Surface the contract instead of hiding it.
Wiring an agent into your log stack gives it access, not understanding. The real integration work is teaching it what your data is called.
Streaming UX inherits a reversibility contract that tool calls do not honor. Here is why the stop button can't unsend the email, and the framework changes that fix it.
The autonomy default that turns 'undo' into an aspirational verb — and the tool-layer, eval, and orchestrator discipline that keeps agents from acting first and apologizing later.
New-hire onboarding gives humans a tenure gradient; agents inherit production-grade permissions on day three. Inside the seam where security review, the tool registry, and the chargeback bucket meet — and why it has no owner yet.
Two AI features can each pass their own A/B test and still make the product worse. Cross-feature attention competition is a portfolio problem no team-level dashboard will catch.