How Prado 5×'d Deploys and Cut Review Time by 30% Using Optibot + Insights

Prado embedded AI into every PR and got real-time visibility into how fast code was moving — turning code review from a bottleneck into a competitive advantage.

Daily Staging Deploys

• 5–6×
  Up from 1–2 per day — the team ships features multiple times daily with confidence.

Faster PR Cycle Time

• 30%
  Measured across all contributors, including the CTO's own cycle time.

AI Review Coverage

• 1 Agent
  = 1 senior engineer equivalent. Every PR reviewed instantly, zero idle time.

The Problem

Manual Review Bottlenecks and Limited Visibility Slowed Delivery

As Prado's customer base expanded, so did its codebase. The number of pull requests climbed, but the review process couldn't keep up. "We were releasing to production once a day — sometimes only two or three times a week," recalls Grainger Blackett, CTO.

• Large PRs piled up — nobody wanted to touch them, leading to long pickup times and unpredictable release windows.
• Deployments lagged, creating tension between speed and safety.
• Team metrics were murky, making it difficult to see which processes actually drove performance.

"Our feedback loops weren't scaling with the company. We needed a system that could keep up with how fast we were moving."

The Solution

AI-Powered Reviews and Real-Time Engineering Insights

Prado adopted both Optibot — the AI code review agent — and Insights, the engineering analytics platform. Together they eliminated idle review time and replaced guesswork with measurable performance data.

• Instant first-pass reviews
  Optibot reviews every PR automatically within seconds — flagging risky logic, suggesting improvements, and linking changes back to Jira/GitLab issues for full context.

• A new quality standard
  The team's rule became: Optibot reviews every PR first. Engineers resolve its feedback before any human reviewer touches it — keeping merges clean and reducing noise.

• Real-time pipeline visibility
  Insights tracks cycle time, review duration, deployment frequency by environment, and PR activity trends — turning gut feel into measurable data.

The Results

5–6× Daily Deploys, 30% Faster PR Cycles, and Safer Releases

The impact was immediate. With Optibot handling first-pass reviews and Insights providing real-time visibility, Prado's team saw measurable gains across speed, quality, and confidence:

• Staging deployments increased from 1–2 per day to 5–6 per day — a 5× improvement.
• Average PR cycle time dropped ~30% across all contributors, including the CTO.
• Every PR received an immediate review, eliminating idle time and ensuring code safety.
• Cleaner merges and fewer regressions — engineers resolve Optibot's feedback before human review.
• Optibot's recommendations became part of the team's daily rhythm — fully adopted.

"I still contribute code myself, and even my cycle time dropped by about 30%. It's like we added a full-time senior engineer dedicated to reviews."

The Impact in Numbers

Before and after metrics for Prado's team using Optimal AI

Cut cycle time by 50% and get visibility into engineering productivity

Start reviewing PRs faster, catching issues earlier, and shipping with confidence.