Real Results from Real Users

See how developers and teams use ReasonKit to prevent costly mistakes, make better decisions, and save thousands with structured AI reasoning.

How TechCorp Avoided a $300K Microservices Disaster

💰 $300,000 saved in wasted engineering effort

TechCorp's engineering team was planning a major microservices migration for their monolithic application. The initial architecture design looked solid on paper, approved by senior engineers.

"ReasonKit's LaserLogic module exposed a critical flaw in our service boundaries that would have caused cascading failures at scale. We caught it in 5 minutes of analysis before spending $300K on the wrong architecture." — Sarah Chen, Staff Engineer @ TechCorp
🎯 Problem: Flawed service boundary design that looked good initially
🛠️ Solution: Used GigaThink to explore 10+ architecture patterns, LaserLogic to validate scalability assumptions
Outcome: Redesigned architecture with proper event sourcing, avoided 6 months of technical debt
$300K Cost Avoided
5 min Analysis Time

Senior Developer Negotiates $45K Higher Salary

💼 $45,000/year salary increase + better equity terms

Michael was considering a job offer from a fast-growing startup. The base salary seemed competitive, but he wasn't sure if the equity package was fair.

"I used ReasonKit's ProofGuard to verify the startup's claims about valuation and market positioning. Turned out their 0.5% equity was significantly below market for my role. Armed with ReasonKit's analysis, I negotiated to $165K base + 0.8% equity." — Michael Torres, Senior Developer
🎯 Challenge: Initial offer: $120K salary + 0.5% equity for Senior Developer role
🛠️ Analysis: GigaThink explored market comparables, ProofGuard verified company claims against Crunchbase/LinkedIn data
Result: Final offer: $165K + 0.8% equity + signing bonus ($225K total comp)
$45K Annual Increase
$135K 3-Year Value

Engineering Team Catches 3 AWS Cost Optimization Traps

📉 $87,000/year in prevented waste + 40% cost reduction

CloudCo's engineering team hired an AWS consultant to optimize their cloud spend. The recommendations looked promising: Reserved Instances, Lambda migrations, S3 lifecycle policies.

"We ran the consultant's plan through ReasonKit before implementing. ProofGuard caught 3 major issues: RIs that would lock us into outdated instance types, Lambda migrations that would increase costs due to our usage pattern, and S3 policies that would delete critical data. ROI in the first week." — Alex Martinez, Engineering Manager @ CloudCo
🎯 Situation: $40K consultant proposal for AWS optimization
🛠️ ReasonKit Analysis: BedRock first-principles cost modeling, BrutalHonesty adversarial review of consultant assumptions
Impact: Avoided $87K/year in wasted spend, implemented correct optimization strategy
$87K Annual Savings
3 Critical Flaws Found

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