The Kryotta blog
Guides and comparisons on working with every AI model — Claude, Gemini, Llama, Mistral, DeepSeek and more — plus what we're building.
I used o1 vs Claude vs Gemini to debug 32 UPI webhook failures: which model per error
I tested o1, Claude, and Gemini on 32 real UPI webhook failures during a Diwali sale. Here's which model solved each error type fastest and cheapest.
I used 3 reasoning models to debug 25 EcoCash webhook failures: which one per error
I debugged 25 EcoCash webhook failures using three AI reasoning models. Each error type needed a different model—here's which one caught signature mismatches, timeouts, and rounding bugs fastest.
I used 3 reasoning models to debug 30 Razorpay webhook signature failures: which one per error
I tracked 30 Razorpay webhook signature failures across Claude Sonnet, Gemini Pro, and DeepSeek R1 to see which model caught each error type fastest and cheapest during peak season traffic spikes.
5 myths about tokens and context windows that waste your USD budget on AI
Tokens aren't stored bundles, and context windows aren't free memory. Two myths that drain your AI budget fast—and how to fix them.
I used Claude vs o1 to debug 28 Stripe webhook race conditions: which model per bug
I debugged 28 Stripe webhook failures using both Claude and o1. Here's which model caught each bug, and why one excelled at spotting race conditions while the other was faster at obvious errors.
I used 3 reasoning models to debug 35 SEPA direct debit failures: which one per error type
I tested o1, Gemini 2.0 Flash Thinking, and DeepSeek R1 on 35 real SEPA direct debit failures. Here's which model solved each error type fastest and cheapest.
5 myths about model per task for debugging that waste your freelance rupee budget
Stop burning rupees on expensive models for every bug. Here's what actually works: route simple syntax errors to Haiku, save Opus for race conditions, and use reasoning models when production fails only under load.
5 myths about model per task for code review that waste your freelance budget
Reasoning models aren't always worth ₹50 per review. Learn which AI models actually save money on code review and when to use them.
I used Claude vs o1 to debug 30 Stripe webhook timeouts: which model found the race condition
I debugged 30 Stripe webhook timeouts with Claude and o1. Claude found an N+1 query; o1 spotted the race condition causing the real problem. Here's what each model caught and the two-line fix.
I used Claude vs o1 to review 30 React PRs: which model for bugs vs style vs tests
I routed 30 React PRs through Claude and o1, splitting reviews into logic bugs, style, and tests. Reasoning models caught more bugs. Claude excelled at style. The right routing saved four hours and cut API costs by 60%.
5 myths about code review with AI that waste your freelance developer budget
Most freelancers overspend on one premium AI model for every code review task. The real savings come from matching the right tool to each job—DeepSeek for logic errors, Claude for refactoring, Gemini for style checks.
I used 3 reasoning models to debug 25 UPI webhook failures: which one per error type
I hit 25 UPI webhook errors during Diwali week. I tested Claude Sonnet 4.5, Gemini Pro, and DeepSeek R1 on each one. Here's which model caught which bug fastest.