Knowledge & Technology
Most engineering delay is reconstruction and review, not a shortage of clever code.
26%
measured productivity gain in software development studies. Employment for developers aged 22–25 has fallen nearly 20% since 2024.
Stanford HAI, AI Index 20261Teams buy coding assistants, then keep the same ticket ambiguity, the same flaky tests, and the same review bottleneck. An agent that writes a patch you do not trust is a new queue.
How I see it
Engineering agents recover time from tickets, not from taste
A software engineering agent is useful when it owns a defined result: a reproduced bug with a failing test, a routine change in a well-covered area, a draft fix with citations to the code it touched, or a pull request that already answers the review checklist.
Product and internal-tools teams in Miami technology companies, and the smaller engineering groups inside operators, lose time to context: finding the path, the owner, the last incident, the test that should have existed. That reconstruction is the first surface.
Judgment stays on architecture, security, and anything that can take production down. The control point is review with a standard, not a rubber stamp and not a rewrite of every line.
Start with one ticket type that already has volume and tests. Measure cycle time, review time, and escaped defects. Do not start with autonomous development across the estate.
Where the cost sits
Engineering capacityengineers × hours on a named ticket type × loaded cost, minus review and defect cost the agent adds
Net the review time. If seniors spend the recovered hour rewriting the patch, you moved work up the ladder.
Is this your problem?
Five signals the cost is already real.
Which ticket type is high volume and well covered by tests?
That is the first agent object. Novel architecture work is not.Where do hours go: finding context, writing the change, or waiting on review?
Each bottleneck is a different design.What may merge without a person, and what may not?
If the answer is nothing, you are buying an assistant, not an agent.Can you evaluate on last month's real tickets?
A greenfield kata is not your codebase.Who owns the agent when it opens a bad pull request?
Unowned coding agents become noise in the review queue.
What done looks like
The result, not the category.
A solution is finished when a named result no longer waits on reconstruction.
Produce the brief
A packet an expert can use — sources, exceptions, and a recommended next step — not another search box.
Someone can decide from the artifact this week.
The system retrieves documents the expert still has to reread.
Someone uses it on live work
The brief enters a real case, a ticket, or a decision. Unused research is inventory.
The artifact shows up in the operating path.
A knowledge base grows and the unofficial path stays Slack.
Stop re-researching the same question
Recurring questions reuse a maintained brief. Experts add judgment, not reconstruction.
Repeat questions do not restart from zero.
Every ask is treated as novel.
What usually fails
How solution shopping wastes a quarter.
Measuring accepted suggestions instead of cycle time
A high accept rate can still leave the same review queue and the same escaped defects.
Unsupervised commits on the money path
Payments, identity, and core booking paths need a named human control point.
Skipping tests because the agent looks fluent
If the repo cannot fail a bad change automatically, you added speed to an untested path.
This is not the problem if
Do not start with a category purchase.
- The repo has no tests and leadership will not add them.
- The request is unsupervised commits to production.
- The work is novel architecture with no repeating ticket type.
- The real constraint is product decision latency, not engineering throughput.
A useful next step
Bring one expensive problem. Get guided into production.
We guide the implementation, go deep on the technical path, and stay hands-on through operations — or tell you when a simpler answer is better.
Discuss an AI opportunity