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B2B improvement loops 🔁, working with agents 🤖, Convoy’s culture postmortem 🏗️
Decision traces can create a compounding loop in B2B, like how
consumer platforms leveraged behavioral data. Traditional software
records
outcomes ...
Quick Access
Install command
$ mrt install automation

**TL;DR** - B2B product teams building improvement loops with AI agents; what working with agents actually looks like day-to-day.
The 10-Second Pitch
- AI agents in B2B workflows excel at high-volume, low-variance tasks - data entry, CRM updates, report generation
- Key to successful agent integration is designing good feedback loops for human-in-the-loop
- Convoy postmortem on failed AI culture initiative required reading for anyone doing this
Setup in 3 Steps
1. Identify highest-volume, lowest-variance B2B tasks first - that is where agents pay off fastest
2. Design explicit human review triggers based on confidence scores, not just task type
3. Read Convoy postmortem - failure modes they describe are universal
**Example Prompt:**
Design an AI agent workflow for a B2B sales team that triages inbound leads and schedules follow-up calls.
Verdict
| Pros | Cons |
|---|
| Improvement loops compound quickly | Agents amplify bad processes as fast as good ones |
| B2B has lot of high-volume, low-variance work | Change management is the hard part, not technology |
|---|
| Convoy postmortem honest and useful | Most companies will not publish their failures |
Companies winning with agents in B2B picked right workflows and invested in human training, not just AI.