AI Coding
Promised 2x.
Are You
Getting It?

ContextBridge optimizes AI coding performance for your codebase by automatically measuring, learning, and improving.

  • Benchmark agents/models on YOUR code, not SWE-Bench
  • Learns from every coding session
  • Learns from every code review
  • Paved road agent orchestrator ensuring best practices
  • Tests improvements automatically against your evals
  • Works with Claude, Cursor, Copilot, Codex, Gemini

Reality Check

AI coding tools promised 10x. Where is it?

Studies show minimal lift

Stanford research shows AI coding tools deliver only 0-10% improvement for brownfield codebases. The 10x promise isn't materializing.

Vibes-based context engineering

AGENTS.md, rules, skills—everyone's trying different approaches but there's no way to measure if they actually work.

Agents don't automatically learn

Every new agent session starts from zero. All your steering, corrections, and feedback from previous sessions has been forgotten.

The Code Slop Crisis

AI makes it easier than ever to create tons of verbose, unidiomatic code slop—flooding PRs, exploding review times, and burying your most experienced engineers in code debt.

Inconsistent prompts, inconsistent results

Human prompting varies by person, by day. Every session is a winding road of back-and-forth, with no guarantee you'll end up with a good solution or slop.

SWE-Bench isn't your codebase

Industry benchmarks measure performance on generic open source code. You have no way to evaluate which agents, models, or context engineering actually work for YOUR code.

The Answer

Go from vibes to evals

Measure

  • Benchmark agents/models on YOUR code (not SWE-Bench)
  • Track task velocity and PR quality to prove the 10x

Optimize

  • Continuous improvement for your context engineering
  • Learns from sessions, code reviews, and tests changes against your evals

Ship

  • Structured workflows from task to merged PR with automated guardrails
  • Precision feedback on plans and code at every step

How It Works

Get started in minutes, see results in days

01

Connect

Link your GitHub repos and project management tools. ContextBridge automatically tracks tasks and PRs.

02

Baseline

We analyze your existing task completion velocity and PR quality to establish your baseline metrics.

03

Benchmark

Test different agents and models on YOUR codebase. Compare Claude Code vs Cursor vs Copilot with real data.

04

Improve

Every task, every PR, every merge feeds back into the system. Your context engineering gets smarter.

Ready to find out if you're getting 10x?

Request a demo and see how ContextBridge can optimize your AI coding workflow

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