Coding agents
Use coding agents without the review queue becoming the bottleneck.
Coding agents can draft most first-pass code and tests. Without ownership boundaries, promotion gates, and recovery, they collide, skip checks, and the review queue becomes the bottleneck.
I help a team use coding agents so seniors are not stuck clearing that queue. Agents draft. Humans and gates decide what ships. This is not a chatbot product. It is how the team works.
Fit
Is this right for you?
Good fit
- ?Series A-C or growth team that wants to use coding agents without the review queue taking over
- ?Already experimenting with coding agents and hitting collisions, skipped tests, or a senior review bottleneck
- ?Engineering leaders who need an operating model, not a demo
- ?Humans will stay in the loop. Agents draft. Gates and people promote
- ?You will keep writing production software after the engagement
Not a fit
- ?You want a personal AI assistant or chatbot set up
- ?You want someone to "add AI" without changing how the team ships
- ?No engineering team yet. This is an operating model, not a product build
- ?You need a vendor install or a consumer agent SKU
Process
How I install the model
Diagnose how you ship today
I look at the repo, the pipeline, and how work actually moves. Where are agents already creating collisions, skipped gates, or a review pile? Where would they, if you turned them loose? Week one ends with a clear map, not a slide deck of AI possibilities.
Design ownership, gates, and the agent contract
We define who owns which files, what agents may draft, and what only humans promote. Promotion is gated: typecheck, lint, and tests decide what lands. Agent work goes through queue-driven services with retries, idempotency, and recovery, not a pile of one-off prompts.
Install it in the repos and the process
Ownership rules. Promotion gates. Queues. Recovery. Observability fed into the test suites so agent failures show up the same way the team already tests. I work in the codebase and in the rituals. This is a hands-on install, not a recommendation memo.
Run it with the team, then hand it off
We use the model on real work. Adjust the boundaries. Make sure parallel agents do not collide. Train the people who will keep the gates honest. The goal is a delivery OS the team owns after I leave, so the review queue does not swell back.
Scope
What I do
Human+agent operating model
- · Coding agents draft most first-pass code and tests
- · Humans stay in the loop for direction and promotion
- · Working agreements the team can actually keep
- · Clear split between draft work and what is allowed to land
Ownership that prevents collisions
- · Enforced file ownership boundaries
- · Parallel agents that do not overwrite each other
- · Review stays on the paths that matter, so the queue does not become the job
- · Less "who touched this?" after every agent run
Gated promotion
- · Typecheck, lint, and tests as the promotion bar
- · No merge on vibes or a green-looking chat transcript
- · Gates wired into the same path humans already use
- · Broken work stays out of main
Recoverable agent services
- · Queue-driven agent services, not one-off prompts
- · Retries, idempotency, and recovery when a run dies
- · Observability fed into test suites
- · Failures surface the way the team already tests
Outcomes
Results you can expect
Agents draft code and tests inside ownership
Typecheck, lint, and tests decide what lands
Queues, retries, and observability in the test suite
Why this is different
This is not "we set up a chatbot." I designed and ran this class of operating model as CTO at Interstice Digital and in related AI delivery work. You get an engineering OS for human+agent teams (ownership, gates, queues, recovery), not a consumer agent product.
If the call is really team rescue, leadership, or cost, I will say so. This is for teams that want to use coding agents and are willing to change how work is owned and promoted, so the review queue does not become the new bottleneck.
Questions
Frequently asked questions
Is this a chatbot or personal AI agent setup?
No. This is an engineering operating model, not a consumer AI agent product. I do not install a personal assistant or a chatbot. I install how your team and coding agents work together: ownership, promotion gates, queues, and recovery.
What does file ownership mean for agents?
File ownership is an enforced boundary. Agents and humans may only write first-pass work in the paths they own. That is how you run parallel agents without colliding PRs, overwritten files, or a review pile nobody can merge.
Do we already need to be using coding agents?
Helpful, not required. The typical call is a Series A-C team already experimenting with coding agents and hitting collisions, skipped tests, or a senior-engineer review bottleneck. If you have not started yet, we install the operating model first so you do not learn those lessons the expensive way.
How is this different from Fractional CTO?
Fractional CTO is ongoing leadership across process, hiring, architecture, and delivery. This is a time-boxed install of one operating model: how humans and coding agents ship together. They stack well. Many teams start here and keep a lighter fractional retainer to hold the line.
What do you actually install?
Ownership rules so parallel agents do not collide. Gated promotion: typecheck, lint, and tests decide what lands. Queue-driven agent services with retries, idempotency, and recovery. Observability fed into the test suites so failures show up the same way the team already tests. Working agreements so humans stay in the loop and the review queue stays on the work that matters.
How long does it take?
Typically 8 to 12 weeks. Week one is diagnosis. The middle is install and first real use. The last stretch is handoff: the team can run the model without me.
Will you pick our agent vendor or model?
I work with the tools you already use, or help you choose, but the offer is not a product SKU. The operating model is the work. Vendors change. Ownership, gates, and recovery have to survive that.
Investment
What it costs
per engagement, typically 8 to 12 weeks
- ?Hands-on install of the human+agent operating model
- ?Ownership rules, promotion gates, and agent service infrastructure
- ?Observability wired into the test suites
- ?Team handoff so the model survives without me
Range tracks team size, repo sprawl, and how much agent usage already exists. One primary product org sits toward the middle. Multi-org or greenfield platform work sits higher.
Want coding agents without the review queue becoming the bottleneck?
Book a free 30-minute call. I will tell you whether you need this operating model, a team turnaround, or something else, and whether I am the person to install it.
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