AI-Native Development
Most code in 2026 is written with AI help. Whether that makes a project fast or a mess comes down to who checks the output, and how.
These notes are from my own work building with AI agents: what the tools cost, how they compare when I measure them, and what it takes to let an agent run code safely.
Hire an engineer who works this way →3 notes
Cursor vs Claude Code: A Founder's Pricing Teardown
Cursor pays Anthropic $650M/year while earning $500M. I break down pricing, trust, business model risk, and why I chose the $100/month option with no middleman.
GitNexus Benchmark: Graph-Indexed Retrieval vs Claude Code's Native Exploration
Does graph-indexed retrieval actually beat Claude Code's native codebase exploration? I ran the same architectural question both ways. $0.52 vs $0.39, 38 tool calls vs 12, and the KuzuDB internals that explain the difference.
I Built an AI Agent That Runs Untrusted Code to Find Security Threats
877,000 malicious packages and counting. I used Upstash Box to build a sandboxed AI security scanner that does both static and dynamic analysis.
Not sure what to build or how to build it?
That's exactly what the advisory session is for.
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