Offerings
Governance · Vibe-coding

Guardrails for Your AI Team

Your developers are already shipping with AI. We help you make it governed — architecture checkpoints, specification workflows, and human decision gates.

What it is

Fast output without accelerating technical debt.

Your developers are shipping with AI. Copilot, Cursor, Claude Code — the tools are in use and the output is coming fast. But fast output without governance is how you accumulate technical debt and unintended dependencies at an accelerated rate.

Guardrails for Your AI Team is a structured engagement that puts the right governance around your existing AI-assisted development — without slowing it down.
What we do

Three layers of governance, none of them bureaucracy.

Architecture checkpoints
Before agents touch a new area of the codebase, there is an architecture review. Not a committee meeting — a lightweight, documented decision about the approach. The agent works from that decision, not around it.
Specification workflows
A lightweight specification discipline: a structured brief that captures what is to be built, what constraints apply, and what the done criteria are. The specification is what agents work from and what humans review against.
Human decision gates
We identify the decisions in your delivery process that should not be delegated to an agent — and make those gates explicit. Not everything needs a gate; most things do not. But the ones that do need to be clear.
How we start

Observation before prescription.

We start by observing how your team currently works. Not to judge the process, but to understand it. Where do agents get direction? Where are the implicit quality gates? What is working and what is not?

From that observation, we introduce the three layers. The goal is trained habits and documented practices your team can maintain — not a dependency on Consid.

What you get

A governance model that fits how your team already works.

  1. Governance assessment

    An honest read on your current AI-assisted delivery process — what is working and what is quietly creating risk.

  2. Lightweight governance model

    Implemented with your team, not handed over as a document. The three layers, fitted to your context.

  3. Trained habits and documented practices

    Your team can maintain this after we leave. That is the goal.

  4. 30-day review session

    We come back a month after implementation to assess what is working and what needs adjustment.

Who it is for

Teams shipping fast and starting to see the cost.

Engineering leads and CTOs whose teams are already using AI coding tools effectively but are starting to see the downstream costs: inconsistent architecture, difficult-to-review PRs, and technical decisions made by agents that should have been made by engineers.

Questions

Frequently asked

What are guardrails in this context?
Concrete controls — architectural constraints, specification gates, review checkpoints, and tooling policies — that let an AI-augmented team move fast without losing quality, security, or auditability.
Do guardrails slow the team down?
Well-designed guardrails increase sustained velocity. They remove ambiguity at decision points, so engineers and agents both spend less time re-litigating questions that should already be settled.
How are guardrails enforced?
A mix of specification, automation, and review gates. The goal is for the guardrails to be visible in the workflow, not bolted on as a separate compliance exercise.
Next step

Tell us how your team is working. We'll show you where the gaps are.

A short conversation about your current delivery process is enough to scope the engagement.

Talk to Consid