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What AI Has Never Seen: The Context Gap in Code Generation

Your AI coding assistant has read the entire internet. It knows every programming language, every framework, every best practice documented in Stack Overflow answers and GitHub repositories. It can generate a REST API handler in seconds that looks perfect with clean code, proper error handling, following all the patterns. But here's what it's never seen: your production traffic. Data from a real API request. Someone filling out a form with messed up or incomplete data. AI is changing how we write and test code, but there's a fundamental gap between training data and production reality.

My AI Agent Stole My Crypto #speedscale #openclaw #aicoding #codingagent #security

I thought I found the ultimate coding shortcut: an autonomous AI agent. Turns out, I just bought a one-way ticket to a digital nightmare. A friendly reminder to my fellow devs: Validation isn't optional—it's survival. Your laptop shouldn't have a higher calling than your production environment. Validate now: speedscale.com.

The Dangerous Power of Local AI Agents. #speedscale #proxymock #aiagents #openclaw #localai

I’ve been testing OpenClaw, a fully autonomous agent that lets you remote control your entire system via Signal. It’s incredibly powerful to text your computer from a coffee shop and have it execute tasks, but you’re essentially handing the keys to your digital kingdom to an LLM. The Golden Rule: Trust, but verify. I’m using Proxymock to sniff every single API call going in and out of the agent. If there’s a data leak or a "hallucination" that tries to wipe my drive, I see it first.

Refactor Safely with AI: Using MCP and Traffic Replay to Validate Code Changes

So as software engineers using AI coding assistants, we’re quickly learning of a new anti-pattern: Hallucinated Success. You give your agent (e.g. Claude via terminal or various IDE code assistants) the command “refactor the billing controller.” The agent happily complies, churning out nice clean code. The agent even goes so far as to write a new unit test suite that passes at 100%. You integrate it. Your test suites pass. Your production code breaks. Why?

The Hidden Cost of 30% AI-Generated Code #speedscale #aicoding #devops #technews #ai

AI now writes 30% of Big Tech’s code, but the resulting surge in defects is crashing platforms like AWS and GitHub. Manual testing can no longer keep up with this velocity; it's time to deploy AI Quality Agents to save our systems. Is AI speed worth the decline in code quality, or are we headed for a breaking point? Let me know if you’ve noticed more bugs in your workflow lately. Video collab with @ScottMooreConsultingLLC.

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.

Stop wasting time on Postgres migrations. #speedscale #postgresql #postgres #database #programming

If you're spinning up a whole container just for one test, you’re doing it wrong. Old way: Full DB container + pg_restore New way: speedscale + proxymock It records actual DB traffic and mocks it "on the wire." Test smarter, not harder.