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CASE STUDY / THEN CAME AI

Alkemy Brought the Discipline:
AI Coding Agents Brought the Speed

How Team d²l℠ discovered a winning combination

Give AI coding agents the structure they need to accelerate your team’s machine learning (ML) projects even further.

Project Overview

Recipe for a Repeat Win

Across the ML lifecycle, Alkemy made the difference by stepping in where AI coding agents struggle on their own.

​AI coding agents bring a huge amount of machine learning knowledge to the table, but every session starts from an empty chat. They don’t inherently know what success looks like, what decisions were made last week, and how to navigate scattered notebooks and scripts.

 

Alkemy was built to give data scientists a complete operating framework for the ML lifecycle:

 

 - Structured projects

 - Reproducible datasets

 - Structured experiments

 - Artifact management

 - Deployment from the same code used in experiments

 

It became immediately clear that these players could benefit from this coach.  Then the team really geeked out to prove the concept - look for videos COMING SOON!

Results

What Team d²l Learned

Across the ML lifecycle, Alkemy made the difference by providing the defense where AI coding agents struggle on their own:

Project Setup

Agents inherited a standard project layout with built-in conventions for code, config, and artifacts.

Building Datasets

Datasets were validated objects agents could reference by name across sessions.

Running Experiments

Experiments and artifacts were tracked automatically, with results and feedback recorded so agents could use prior runs to guide iteration.

Comparing to a Benchmark

Benchmarks and prior runs lived inside the project structure, so agents could compare new results against the current bar.

Deployment

Deployment used the same code path as experiments - no rewrite and no drift.

Handing off Mid-project

New session inherited structure, history, and current state from the framework itself.

Ongoing Maintenance

Lifecycle structure was part of the system, not something the team had to build and maintain.

Ready to get in the game? Get in touch to take the next step in your data journey.

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