Case Studies / Prado
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.
Daily Staging Deploys
5–6×
Up from 1–2 per day.
Faster PR Cycle Time
30%
Measured across all contributors.
AI Review Coverage
1 Agent
Every PR reviewed instantly.
See why engineering leaders at high growth companies use Optimal AI
"Now we can actually say our team is shipping faster. With Optibot reviewing every PR and Insights showing the full picture, we're releasing to staging five, six times a day — and it feels safer than ever."
Grainger Blackett
CTO, Prado
Prado had built a reputation for helping food and meal-prep brands deliver high-quality subscription experiences at scale. But behind the scenes, their engineering team was struggling with a familiar problem: velocity.
Manual code reviews, unpredictable deploys, and a lack of visibility into team performance slowed development to a crawl. By adopting both Optibot and Insights, Prado transformed code review from a bottleneck into a superpower — shipping five, six times a day, safely.
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."
Grainger Blackett
CTO, Prado
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.
Senior engineer equivalent coverage
The first time Optibot caught a pagination edge case with a clean, detailed fix, it clicked: "It felt like having another senior engineer on the team."
"Our new standard is simple: Optibot reviews every PR. You resolve its feedback before anyone else touches it. That change alone sped us up dramatically."
Grainger Blackett
CTO, Prado
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."
Grainger Blackett
CTO, Prado
"I feel safer knowing every PR has that extra layer of review. If you're trying to speed up to keep up, you need Optibot."
Grainger Blackett
CTO, Prado
The Impact in Numbers
Before and after metrics for Prado's team using Optimal AI
Real numbers verified by the leaders using the tech.
Metric
Before
After
Improvement
Staging Deploys
1–2 per day
5–6 per day
PR Cycle Time
Slow; long pickup times on large PRs
30% faster across all contributors
Code Review Coverage
Partial; dependent on human availability
100% — every PR reviewed instantly via Optibot
Engineering Visibility
No real-time metrics; murky team performance data
Automated via Insights — cycle time, deploy freq, PR trends
Release Confidence
Tension between speed and safety
Every PR has AI review layer; team ships faster and safer
Cut cycle time by 50% and get visibility into engineering productivity
Start reviewing PRs faster, catching issues earlier, and shipping with confidence.
