Practices coaching

Coaching your engineers in TDD and continuous delivery until they run it.

AI makes every developer faster at producing code. It does not make the code better. This is for a team that does not have the practices underneath yet. We pair with your engineers on your codebase, set up the delivery platform on your repositories, and leave when the health score and DORA metrics are yours to hold.

See it in our work

At a glance

Format
Pairing on real work, not training
Our side
One to three engineers
Length
Typically two to three quarters
Step back
When the metrics hold without us

What it covers

Your team, shipping with the discipline.

  • Pairing on real work

    Not workshops. Our engineers sit with yours on the tickets already in the sprint, and the practices are learned by shipping.

  • The delivery platform on your repos

    Quality gates, specification driven development and the code health score, set up on your repositories and left with your team.

  • Practices that hold

    Test driven development, clean architecture, small batches, trunk based development and continuous delivery, held as daily discipline.

  • A measured handover

    The same health score and DORA metrics you saw during the engagement, reported by your team after we step back.

How we do it

Diagnose, coach, enable, step back.

  1. 01

    Diagnosis of where the team is

    The repository diagnosis plus a week alongside the team. Where delivery stalls, and which practice would move it most.

  2. 02

    Platform coaching, one to two engineers

    We set up the platform and train your team. You run it, with us on call for the first releases.

  3. 03

    Enablement, two to three engineers

    We coach the practices alongside your team until they are self sufficient, pairing on the work already in flight.

  4. 04

    Step back on evidence

    When the metrics hold for a quarter without us, we step back. That is the outcome, and it is written into the engagement.

What you get

Practices your team owns and reports.

  • The delivery platform set up on your repositories
  • Your engineers shipping with TDD, small batches and continuous delivery
  • A code health score and DORA metrics your team reports, not us
  • Written practices and runbooks in your own terms
  • A step back date, agreed on evidence

Where we have done it

Real engagements, named.

Questions

Questions we get asked.

Our developers already use AI tools. Why do we need this?
Because AI amplifies whatever is already there. With discipline it makes a team faster; without it the codebase degrades faster than review can keep up. Enablement is the discipline part.
How long until you step back?
Typically two to three quarters. The step back is tied to the metrics holding without us, not to a date.
Is this training?
It is pairing on real work. Training sessions happen where a concept needs one, but the practices are learned by shipping.

What clients say

In their words.

01 / 04

Life Insurance Direct
Before Metricsense, checking calls was a manual process: we selected files for review. Now the platform analyses every call, and we review by risk. It has identified customer experiences we would not have picked up before, and it lets us scale our quality assurance program without increasing headcount, with our team still the human in the loop. It helps us protect our customers, our business and our agents.

Russell Cain

Founder and CEO, Life Insurance Direct

Also under product development

Where it leads next.

All of product development

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