You already know you should review agent code — I've written three posts on why. This is the how: what to read first, the failure signatures that look correct, and the tests you can actually trust.
A rule in a markdown file is a request. The agent honors it right up until 'temporarily' hardcoding the token becomes the path of least resistance. Requests need enforcement behind them.
Sub-agents are the most oversold feature in agentic coding. They're also, used precisely, the best answer to the two hardest problems in agent work: context pollution and self-grading.
Most prompt advice is decoration. The words you choose matter far less than what the model can see when it reads them — and the fastest way to improve output is usually to delete something.
You typed one line. The agent wrote four hundred. Forty minutes later you're untangling code you never asked for. The failure didn't happen while it was generating — it happened before you pressed enter.
We keep asking whether the robots will ever govern us. They already do — we just call it copy-paste. A field note on how humans became the man in the middle of their own conversations.
Developers stopped Googling errors, then stopped reading the code, then stopped reviewing the PRs. Follow that line to its end—and the honest case for whether it's even a problem.
Part one argued you should fix the harness, not the model. This is the harness—the actual rules file, skills, and memory you can drop into your agent today.
Your coding agent caves the moment you push back. That's not a dumb model—it's a people-pleasing harness. And the harness is the one part you fully control.
DevOps took a decade to mature. MLOps took five years. LLMOps took two. Now AgentOps is emerging—and most teams aren't ready for what it demands.
Your data scientists each have their own GPU VM on Azure ML. They're expensive, underutilized, and nobody shares. Here's the path from VM sprawl to orchestrated workloads.
Last week I interviewed a data scientist who showed me his Claude Code history. He built an app in record time. The logic was wrong, and he couldn't explain a single line.
Vince Gilligan's new sci-fi hit isn't just entertainment—it's a blueprint for understanding multi-agent systems and the AGI debate.
Birthday reminders, daily digests, and cron jobs for the AI age. Set it once, run forever.
Stop repeating yourself. Let Claude remember your standards. Company rules, compliance checks - all automatic.
Your meeting just ended. In 2 minutes, you have action items ready. SuperWhisper, Ollama, and the voice-to-action pipeline.
Build /start_my_day and never miss a task again. Connect Jira, Confluence, OneDrive - all in one command.
Claude Code isn't just for programmers - it's for anyone who wants to 10x their productivity.
We've moved from unlimited SaaS to metered AI. Tokens aren't just billing units—they're becoming the universal currency of intelligence.
Stop being the "Standardization Police." Bake your enterprise rules into AI's Constitution.
The smartest engineers don't build what they can configure. Decouple Compute from Communication.
The modern mandate is not just model deployment, but product delivery—database to browser.
Vibe Coding is powerful, but only if you know what you're doing. Experience still matters.
How to discern genuine expertise from well-prompted answers in the age of ChatGPT.
Empower stakeholders to solve 80% of problems, freeing data science for the complex 20%.
Transform data scientists from implementers into strategic problem-solvers.
LLMs and low-code platforms are rapidly making traditional DevOps practices obsolete.
Moving from prototype to production uncovers a web of challenges in GenAI development.