Build with AI. Ship with senior judgment.
For CTOs and product leaders, AI-assisted engineering creates room to test uncertain features and revisit work you previously deferred. We help you turn those possibilities into working software, with senior judgment guiding what to build and ship.
Make the work reviewable at every step
Agents help with implementation and first-pass review. Your team and ours decide whether the product solves the right problem and whether a change is ready for your users. A senior engineer reviews and owns every merge.
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1
Agree on the next useful change
Define the user workflow, acceptance criteria, constraints, and decisions that need your input. Keep the scope small enough to demonstrate and review. If the direction is unclear, resolve that before expanding the build.
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2
Build inside an explicit structure
Give agents the code conventions, design system, and boundaries they need. Divide work into changes that can be checked independently, with a person responsible for how they fit together.
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3
Challenge the implementation
Use automated checks and independent review to look for missed requirements and failure cases. Reviews from different models can surface different concerns. Engineers resolve disagreements against the requirements and evidence.
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4
Verify the workflow and decide
Test the behavior that matters to users, including permissions, error states, and the steps around the changed screen. Record remaining limits and decide what is ready to merge, release, or revise.
Progress you can evaluate
Work runs on a weekly delivery review and a monthly priorities review. You own the business priorities; we shape product and technical decisions with you. The cadence gives both sides a place to change course when the evidence changes.
Working increments
Try the proposed workflow before expanding it. Compare working alternatives when the product decision is uncertain, and use feedback to decide which deserves more investment.
Review evidence
See which acceptance criteria the change meets, what review uncovered, and what still needs work. Track time to an accepted change and the rework needed to get there.
Visible tradeoffs
Revisit a deferred feature with a small, bounded experiment. Use what you learn about usefulness, effort, and maintenance to continue, change direction, or stop.
DORA's 2025 research describes AI as amplifying existing organizational strengths and weaknesses. That supports investing in the delivery process alongside the tools. Read the DORA research. Your project's results still need their own evidence.
See the methods and evidence
Design rules agents can follow
The Onion Design Framework puts design decisions into the environment agents build inside, with a documented experiment and its limits.
Engineering judgment in practice
Our Rails World notes cover the shift toward clear constraints, verification, and human judgment as more implementation runs through agents.
Quality controls for AI products
Building AI into a product adds another kind of verification. See the prompt versions, evaluations, model comparisons, and publication checks behind SimpleDocs.
Still deciding what should come first? Start with the sequencing questions. If your goal is an AI feature inside your product, see how we approach AI enablement.
What does your next release need to prove?
Tell us about the product, the people using it, and the decision you need to make next.