Products
MCPAI Code ReviewDeveloper Q&A
Outcomes
Improve QualitySave tokensReduce rework
SecurityBlogDocsPricing
Book a DemoGet Started



Products

MCP
Improve AI coding agent output by connecting knowledge from your codebase, docs, and messaging platforms.
AI Code Review
High-signal PR feedback informed by how your system actually works. No noise or nits.
Developer Q&A
Fast, high quality answers without digging or disrupting coworkers.
Outcomes

Improve Quality
With plans and code that reflect how the system actually works you're one step closer to production.
Save tokens
Give agents the right context up front to reduce costly retrieval loops and tool calls.
Reduce rework
Get more accurate output on the first pass and spend less time reprompting and reviewing.
SecurityBlogDocsPricing
Log InBook a DemoGet Started

<
All posts
Shop talk
Calculating ROI on Unblocked
Dennis Pilarinos
·
October 28, 2025

After partnering with hundreds of engineering teams, we’ve seen Unblocked consistently drive measurable gains across three use cases: 

  • Faster onboarding: New hires ramp up on unfamiliar codebases and tools more quickly, contributing value sooner.
  • Reduced support overhead: Fewer repetitive questions for senior engineers and subject matter experts, freeing them to focus on strategic work.
  • Greater team autonomy: Engineers spend more time coding and solving problems, and less time waiting for answers or digging through documentation.

Here’s what the latest industry data shows:

  • StackOverflow shows that 61% of developers spend 30+ minutes per day searching for answers, and another 30+ minutes per day answering questions from teammates.
  • Developers often consult outside their immediate team 10+ times/week.
  • Cortex reports developers lose 5+ hours/week to unproductive work - often context gathering.
  • Google found 65% of developer time is wasted without effective knowledge platforms.
  • Independent research estimates full onboarding takes (6 months) depending on system complexity.

Below, we model cost savings conservatively using these industry benchmarks for inefficiencies and standard assumptions about team composition.

Assumptions from industry data
  • Developers lose 30-60 minutes per day searching for information
  • Senior engineers spend about 4 hours per week answering repetitive questions
  • Average onboarding time = ~ 6 months
Fixed assumptions
  • New hires = ~ 10% of the total engineers
  • Senior engineers = ~ 20% of the total engineers
  • Average senior engineer salary = ~ 20% above average salary
Example: A 200-person org with an average salary of $160K
  • Search Time Savings
    • 200 engineers × 30-60 min/day = 100-200 hrs per day previously spent searching for context
    • At ~$76/hour = $7,600–$15,200 per day
    • Annualized = up to $4,000,000/year
  • Onboarding Acceleration
    • Average onboarding time = ~ 6 months (~$80,000 in salary before full productivity)
    • Reducing onboarding by just 1 month saves ~$13,333 per hire
    • For 20 new hires/year = $266,000/year
  • Reduced Support Overhead
    • For 40 senior engineers × 4 hrs/week = 160 hrs/week
    • At ~$96/hour = $15,360/week, or $768,000/year
Total annual ROI potential for 200 engineers:
  • Search savings: up to $4M/year
  • Faster onboarding: $266K/year
  • Reduced support load: $768K/year
  • Total: ~ $5M/year in recovered productivity

These figures are based on conservative industry benchmarks and reflect only measurable efficiency gains - excluding softer benefits like higher team morale, reduced burnout, and stronger retention.

When developers can instantly find why something was built, how it works, or who to ask, they move faster and make better decisions. That’s what Unblocked delivers: the right context, at the right time, in the right place.

Read More

February 10, 2026

•

Shop talk

Unblocked vs Greptile: Best code review tool comparison for your team (February 2026)
Unblocked vs Greptile code review tool comparison for February 2026. See which tool fits your team's needs with organizational context vs repository analysis.

October 1, 2025

•

Shop talk

Context Engineering: Why LLM’s need more than prompts and MCP servers
Context engineering ensures large language models see the right information at the right time, grounding their reasoning in real code, docs, and conversations instead of guesswork.
Get answers wherever you work
Book a Demo
vscode logo
VS Code
IntelliJ logo
JetBrains IDEs
Unblocked logo icon
macOS App
Slack logo
Slack
web icon
Web
Product
Get StartedBook a DemoDownload UnblockedPricingSecurity
Outcomes
Improve QualitySave TokensReduce Rework
Resources
BlogDocumentationPrivacy policyTerms of service
Company
About usCareersContact us