WORKSHOP · ENGINEERING PRODUCTIVITY
Engineering Productivity Workshop
An engineering productivity workshop is a hands-on day where a team leaves shipping its own work measurably faster, not just inspired about it. Engineers work in their own repositories with Claude Code and Cursor on multi-file changes, tests and review habits, and a baseline is taken during the session so the before and after is a number rather than a feeling. The same day runs an AI productivity workshop track for the functions around engineering, because in most companies the bottleneck is not only in the codebase. I run it as a working AI engineer, on-site across India or remote.
Updated 8 September 2026
What you’ll learn
Engineering track
Claude Code, Cursor and agentic workflows on your own repositories: multi-file changes, tests, review habits and team standards.
Business track
Role-specific AI workflows for finance, HR, marketing, legal and operations, built on the tasks each function does every week.
Reusable prompt frameworks
Teams keep the prompts and patterns they build in the session, so the speed-up survives past Friday.
Measurement
Simple before-and-after measures like cycle time and hours saved, so you can see whether the workshop paid for itself. An internal programme I ran this way measured a 40% speed improvement against its baseline; that is the standard I hold sessions to.
The two tracks
After a shared foundation, the room splits so each group works on its own tasks rather than watching someone else’s.
01
Shared foundation
How the models behave, where they fail, and the prompting habits that transfer across every tool.
02
Engineering track
Claude Code and Cursor on your own repositories: multi-file changes, tests, review habits and shared standards.
03
Business track
Finance, HR, marketing and operations on their own reports, drafts and analysis. No code, no jargon.
04
Rebuild the week
Each participant leaves with two or three of their real recurring tasks redesigned around the tools.
05
Measurement setup
A simple baseline taken during the session, so the before-and-after is a number rather than a feeling.
How it runs
Half day
SINGLE SQUAD
One engineering team, one track, working entirely in its own repositories.
Full day
MOST COMMON
Mixed groups: shared foundation, then engineering and business tracks in parallel.
Multi-session
FOR ROLLOUTS
Larger organisations moving team by team with application in between.
What you keep
- A prompt library built on your material during the session
- Two or three real tasks per team, redesigned around the tools
- A measurement baseline for the before-and-after
- A follow-up plan so the speed-up survives past Friday
Who it’s for
For engineering teams that want speed they can measure.
- Engineering teams adopting AI coding tools properly
- Squads with tool licences and no shared standard for using them
- Companies running a pilot before an org-wide rollout
FREQUENTLY ASKED
Engineering Productivity Workshop: common questions
What does an engineering productivity workshop actually change?
How the next sprint runs, not how the team feels on the day. Engineers spend the session in their own repositories rather than a sandbox, so what they leave with is two or three of their real recurring tasks already redesigned around the tools, plus standards the squad wrote down and committed. The measurement setup is the part most workshops skip and the part that decides whether anyone extends it.
What makes this different from a generic AI awareness session?
Everyone works on their own real tasks during the workshop. Engineers work in their own codebase, finance works on its own reports. Awareness sessions inspire; this one changes how the week actually runs.
Can you run it for a mixed group of engineers and business teams?
Yes. The workshop splits into an engineering track and a business track after a shared foundation, so each group goes deep on its own tools and tasks.
How long is the workshop?
A full day is the most common format. A half day works for a single team, and multi-session programs suit larger rollouts. On-site across India or remote.
WHERE THIS LEADS
What teams usually look at next
Where adoption and engineering meet
THE ENGINEERING TRACK
What this looks like for an engineering team
Adoption across a company and adoption inside an engineering team are different problems. If your developers are the ones who need to change how they work, the hands-on track covers Claude Code, Cursor, agents and spec-driven development on your own repositories.
See the engineering trackPROOF
From ten IT sessions to a group-wide AI rollout
I ran ten AI training sessions for Shivalik Group’s IT team. The work then extended to their Sales team, and a second entity in the group is now onboarding. This is what that looked like, and why it grew.
Shivalik Group · Real estate · Ahmedabad
Read the case study“Instead, it focused on how to use them effectively in day-to-day work to save time, improve productivity, and get better results.”
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