Coding Agent Cost: Why Sessions Get Expensive
Keep the project on disk, treat lunch as a bill, and score the first finished tasks rather than dollars per million tokens
AI agent skills: Why they succeed and what causes them to crash
Everyone's adding skills to their agents. Almost no one knows when they help, why they work, or where they fail.
Does Self-Improvement Still Work on an Engineered Agent Harness?
How self-improving agent harnesses can look better in validation than they perform on unseen tasks.
MCP Went Stateless: What Must Change on Your Servers
2026-07-28 drops protocol sessions. A local place_order went 1 to 2 orders unless I sent an order id.
The three layers of AI agent security: from sandboxes to network proxies
How the industry is shifting from prompt engineering to systems engineering to secure the autonomous stack.
Bot Settings: When to Trust / Review AI Agent Code
Five settings for agent PRs, the rule that picks between them, and the paths that never get Full auto
DeepSeek V4 Flash Debugging Benchmark: Can It Match Fable 5 at 1/99th the Cost?
We ran DeepSeek V4 Flash through 54 private debugging attempts, then compared its reliability, cost, latency, token use, and patch behavior with nine other frontier models.
Why 99%-Accurate Agents Fail Long Horizon Tasks
Why agents fail even when the right rule stays in context
Why your keyboard is the new bottleneck for AI agents (and how to solve it)
Wispr Flow turns messy speech into clean, context-aware text across your IDE, terminal, and AI coding tools.
Open Models as AI Incident Response Infrastructure
If your IR path is paste-into-a-frontier-API, it will break when you need it most.
Why Kimi K3's architecture is a masterclass in AI efficiency
How Moonshot fit a 2.8 trillion parameter model into real hardware without breaking it.
Claude Opus 5 Debugging Benchmark: Does More Reasoning Actually Fix More Bugs?
We ran Claude Opus 5 through 260 debugging attempts at Low, Medium, High, and XHigh effort, then compared its reliability, cost, latency, token use, and patch behavior with nine other models.
Why your enterprise needs a team agent, not a solo bot
How Viktor replaces isolated solo bots with shared memory, secure access, and team-wide coordination.
The Open-Model Race has Split Four Ways
Why “open” now means four different engineering trade-offs, not one model category
Model Routing Layers and the Prompt Cache Tax
One model switch cost 5x a warm turn at 10,000 tokens and 11x at 60,000, measured across three session sizes.
Bun’s Agent Graph Billed $165,000 over 11 days
Nobody paid the invoice, and the arithmetic underneath it still sets the point where a graph beats a single loop.
