Bugbot reviews pull requests and flags bugs. Tests pass or fail. CI is green or red. The loop is closed: the system can verify its own suggestions by running the test suite. And there are always more PRs. Cursor reports 80% resolution rate across 110,000+ repos. That is a real economic engine.
Q2 (Efficiency Play): Invoice matching.
An agent matches purchase orders to invoices. The numbers either reconcile or they do not. Verifiable. But the volume is fixed by the number of invoices your company processes. Good ROI for the accounts payable team. Not a growth vector.
Q3 (Creative Amplifier): AI-generated social media posts.
Infinite demand (always more content to post). But "is this post on-brand and actually good?" requires a human. I know this one personally. We run 12 AI agents that draft content. Every draft goes through a human review step. The agents get better over time (see our feedback flywheel post), but the loop is not fully closed. We are Q3 and we know it.
Q4 (Utility Tool): Contract clause extraction.
An agent highlights risky clauses in NDAs. A lawyer still reviews every flagged clause. The scope is bounded by deal flow. Harvey (reportedly at ~200ドルM ARR in 3 years according to a16z data) is building Q4 into something bigger, but most contract tools are capped utility.
Where We Bet
Coding-agent runtime safety (AgentGuard) is a Q1 picks-and-shovels play.
Here is why. The loop is closed: a budget guard either fires or it does not. A loop detector either catches the repeat or it does not. Tests verify the guards. And the demand is infinite: every coding agent that ships needs cost controls and safety rails. More agents, more demand.
We are not building the agents. We are building the thing that keeps them from burning your budget at 3am.
from agentguard import Tracer, BudgetGuard
tracer = Tracer(guards=[
BudgetGuard(max_cost_usd=5.00, warn_at_pct=0.8),
])
Q1. Closed loop. Infinite demand. Verifiable output.
The Uncomfortable Question
If you are building an agent feature right now, ask yourself:
- Can the system verify its own output without a human? (closed vs. open loop)
- Is the volume of work theoretically unlimited? (infinite vs. finite demand)
- Which quadrant does that put you in?
- Is your budget, team, and timeline sized for THAT quadrant, or for the quadrant you wish you were in?
Q1 and Q2 projects can justify automation budgets. Q3 projects need augmentation budgets (smaller, different ROI model). Q4 projects need to be honest about their ceiling.
Most of the pain in AI product development comes from misclassifying Q3 as Q1. The technology works. The business model does not.
Know your quadrant. Build for it.
AgentGuard: runtime safety for coding agents. Zero dependencies. MIT license. Budget guards, loop detection, and cost tracking that verify themselves.
Originally published on bmdpat.com. I run a one-person AI agent company and write about what actually works.
Want these in your inbox? Subscribe to the newsletter - no spam, unsubscribe anytime.