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Try it yourself

Most AI coding assistants are good at writing code.

What's harder is getting them to understand a system they have never seen, follow decisions they were never told about, and produce something consistent with what your team has already built.

Giving the AI enough context to generate something that fits your system takes a carefully written prompt, a detailed README, and hours spent assembling context from across your tools. And even then, the AI fills the gaps with assumptions that look reasonable but quickly accumulate technical debt.

What your Coding Assistant doesn't know

No matter how good your prompt is, you can't give the AI what it can't see.

Architectural decisions made last month live in Confluence or someone's head, invisible to any AI tool. Two developers prompting the same task produce different code. Every new service starts from scratch.

And no matter how good your prompt is, you can't reliably describe service boundaries, relationships, and constraints in plain text. Some problems can't be prompted away.

This is what Workbench changes

IBM DevOps Solution Workbench gives your coding assistant something better than a prompt: a structured, machine-readable design model that captures your architecture, your domain, and your team's decisions — and makes all of it available to the AI at generation time.

What that looks like in practice:

  • A developer implements a feature correctly without knowing the architectural decision that governed it
  • A new service is bootstrapped with the right entities, interfaces, and patterns — because your experts encoded that knowledge once, and it travels to the code automatically
  • What an Architect and a Business Analyst decide together becomes the context every developer and every AI works from

These trials are short, hands-on and work with your own IDE and coding assistant. Each one proves a specific point. Pick the one that matches what you want to see.

Pick a Trial to get Started