How it works for
engineering teams
Workstream-driven
Breaks big goals into sequenced, observable actions.
Autonomous & results-driven
Handles complex tasks without prompt engineering.
Output: merge-ready pull requests
Finished, checked, merge-ready code — not suggestions.
Lineai acts like a team of developers
Lineai autonomously plans and executes library and framework upgrades end-to-end. It is results-driven, observable, and built for complex, multi-step work.
Workstream-driven
Breaks big goals into sequenced, observable actions.
Autonomous & results-driven
Handles complex tasks without prompt engineering.
Writes its own tickets & prompts
Generates work items, then directs a coding AI.
Output: pull requests
Finished, checked, merge-ready code — not suggestions.
A detailed map of the codebase
Profiles & diagnoses
Core app structure, impact information and cyclomatic complexity.
Built from multiple sources
Bytecode / IL / source decomposition, runtime inspection and DB / data-model scanning.
Extensible
Lineai annotations, pipeline integration and continuous capture.
Informs the AI
Gives the director the dependency and relationship data it needs to act safely.
An AI Director that plans and executes
AI Director
Performs in-depth analysis, then plans and executes workstreams.
Coding AI & MCP
The foundation of automated coding; also supports interactive IDE scenarios.
Event-driven loop
Ties into the build system and tooling to drive work as an automated workload.
No prompt engineering
The Director writes the tickets and prompts — checking output against graph + build feedback.
Stop tech debt from ever accruing
Lineai wires the Directed-AI loop into a pipeline-integrated automation pattern — driven by dependency-change notifications, so updates happen continuously and automatically.
Notification
Dependent component change detected.
Update graph
Re-profile impact across the codebase.
Directed AI
Director identifies the changes and plans the workstream.
Coding AI
Coding AI writes and checks the change.
Updated code
Merge-ready pull request, lights-out.
Let AI continuously do most — or all — of this mundane work. Lights-out with no prompt engineering.
It recovers when things go wrong
Lineai doesn't just attempt the change — it reads build failures, diagnoses the cause and iterates until the work passes and a clean pull / merge request is ready.
- Reads build & migration failures.
- Plans and applies the fix autonomously.
- Re-checks against graph + build feedback.
- Iterates to a merge-ready PR — reviewed & approved.
⚠ Build failed after AI implementation. Claude created a diagnostic log.
Build Failure Log
Command attempted: mvn clean compile -DskipTests
Exit code: 127 (command not found)
Failure cause:
- Java 17 is not available in the build environment
- Maven is not available in the build environment
- Cannot proceed with compilation without proper Java/Maven toolchain
Migration Work Completed:
- Updated Spring Boot parent version from 2.7.11 to 3.5.6 in pom.xml
- Updated Java compiler version from 11 to 17 in pom.xml (required for Spring Boot 3.x)
- Migrated Jakarta EE namespace imports:
javax.annotation.Nullable→jakarta.annotation.Nullablejavax.annotation.concurrent.Immutable→jakarta.annotation.concurrent.Immutablejavax.annotation.PostConstruct→jakarta.annotation.PostConstructjavax.annotation.Nonnull→jakarta.annotation.Nonnull
this tests out fine, Lineai FTW!
Supported technologies
Works with the languages, tools, and databases your team already uses.