What AI Has Never Seen: The Context Gap in Code Generation
AI coding tools generate code from docs and examples—but they've never seen your production traffic. Here's what breaks AI-generated code.
Posts about ai/ml
Browse 9 posts in this category
Refactor Safely with AI: Using MCP and Traffic Replay to Validate Code Changes
Use traffic replay via MCP to create a tight feedback loop for AI coding agents, preventing hallucinated success by validating against immutable production traffic snapshots.
The PII Testing Dilemma
Software is hard to test when production data contains PII and AI systems are causing an explosion in bugs. Explore the hidden nature of PII in modern systems and why traditional test data approaches fall short.
AI Prediction for 2026
Explore 5 bold AI predictions for 2026. From the burst of the AI bubble to the rise of 'vibe coding' and agentic workflows, discover why the future of tech belongs to those who prioritize reliability over hype.
Test Code Changes with Claude Code Using Real Traffic
Claude Code can write features and fix bugs, but proxymock traffic snapshots give me the integration tests, replays, and observation diffs required to ship confident backend changes.
Better integration tests in Cursor using proxymock
Cursor can scaffold new API calls, but proxymock traffic snapshots give me the integration tests, replays, and observation diffs required to ship confident backend changes.
Speedscale Proxymock: Freely testing cloud native apps alongside AI code assistants
Testing AI-generated code in cloud-native apps? Speedscale Proxymock provides a free tool for mock API endpoints and realistic sandboxes based on real traffic to validate your code changes instantly.
Testing AI Code in CI/CD Made Simple for Developers
Generative AI can produce code faster than humans, and developers feel more productive with it integrated into their IDEs. That productivity is only real if CI/CD tests are solid and automated.
A Developer's Guide to Improving AI Code Reliability
AI code reliability explained for developers using LLMs to write faster while keeping their code safe and maintainable