# AI that unlocks major productivity, instead of just shifting bottlenecks

## Automate context delivery
Eliminates hours of hand-feeding context, tuning prompts for every PR, and manually maintaining rules files.

## Accelerate agentic PRs
Agents produce code that embodies your tribal knowledge and meets your internal standards—sailing through review.

## Maintain human oversight
Human-in-the-loop guardrails ensure engineers refine specs, review and approve changes to ensure quality.

# AI ENGINEERING REPORT 2026
## acceleration whiplash
The definitive data on AI's engineering impact. What's working, what's breaking, and what leaders need to do next.

- Engineering throughput is up
- Bugs, incidents, and rework are rising faster
- Two years of data from 22,000 developers across 4,000 teams

# CONTEXT CHANGES EVERYTHING
## Train your agents the same way your best engineers learn: through experience

## historical replay
### Give your agents tenure, overnight
Clara feeds your AI coding agents context derived from past PRs and tickets, until success rates soar.

- Historical task and code replay to extract the context agents need.
- Spot-on context generation per repo, including patterns, dependencies, and failure modes.
- Battle-tested rules that include only what’s proven to improve output in replay simulations.

## agentic pr delivery
### Assign Clara, Get a PR
Your context is documented and planted directly into agentic workflows so agents can produce ready-to-merge code.

- Automatic Jira ticket enhancement—from one-line descriptions to detailed specs and acceptance criteria.
- Disambiguated implementation plans that flag open issues to engineers for resolution before coding begins.
- Code generation with the agents you already use like Claude, Codex, Copilot, Cursor, and more.

## human oversight
### Humans-in-the-loop, by design
Clara generates a pull request, but your developers review and merge it, maintaining quality gates while accelerating delivery.

- Humans review, comment, and approve agentic code, exchanging with Clara just like they do with peers.
- Developer feedback becomes part of your reusable context, so agents don’t ask twice.
- Context can be leveraged to train new hires and upskill the workforce.

## continuous learning
### Self-optimizing as your codebase evolves
Clara captures feedback from every merged PR and code review to refine agent behavior, ensuring your AI gets smarter about your codebase with each iteration.

- Learns from every agent trace and human exchange.
- Updates context graph from recently completed tasks and PRs.
- Generates digests to keep engineers informed of codebase changes.

# Get started
## Discover what context can do for complex engineering work.

See the platform in action.