The Orchestrated Mind: A Vision for Multi-Agent AI

The future of AI isn't single agents but orchestrated swarms sharing temporal memory graphs. Picture agents that don't pass messages but share thoughts, with orchestrators that predict bottlenecks before they surface and memory systems that evolve themselves.

Resilient Future, Agrama v2

Why AI Code Still Needs Human Nudges

AI coding assistants are incredible at rapid code generation, but without human guidance they miss maintainability, architecture, and sustainable engineering practices. The key isn't perfect prompts, it's knowing when and how to nudge the AI toward better decisions.

Stargazer Observatory, Reading Progress, Agentic Patterns, Advisory Work

“Play long-term games with long-term people.” — Naval Ravikant

This hits different when someone extracts value from you, then actively works to devalue you.

Long-term games compound. Trust compounds. Reputation compounds.

The short-term player takes what they need, then burns the bridge to prevent you from collecting on the relationship later. It’s extraction with sabotage, ensuring the value only flows one way.

Long-term people understand that they protect your reputation because it’s connected to theirs.

When you find your long-term people, you’ve found something rare: partners who understand that mutual success compounds.

What Sourcegraph learned building AI coding agents

AI coding agents work best with inversion of control, curated context over comprehensive, usage-based pricing for real work, emergent behaviors over engineered features, rich feedback loops, and agent-native workflows. The revolution is here--adapt or be displaced.

Why I Built a Tool to Test AI's Command Line AX

Built AgentProbe to test how AI agents interact with CLI tools. Even simple commands like 'vercel deploy' show massive variance: 16-33 turns across runs, 40% success rate. The tool reveals specific friction points and grades CLI 'agent-friendliness' from A-F. Now available for Claude Code MAX subscribers.

The Agent-Friendly Stack: 50+ AI Projects Taught Me This

From shipping 50+ AI projects in months, I learned that successful tools must master the duality between human needs (power/flexibility) and agent needs (clarity/determinism). Type safety, machine-readable docs, and friction-free workflows separate winners from losers in the AI-native era.

The Anti-Playbook: Why AI Dev Tools Need Different Growth

The traditional SaaS playbook is dead for AI dev tools. Developers smell BS, the market has three overlapping layers, and you're fighting inertia—not competition. Success means activation through value, retention through community, and expansion through metrics.

Code with Claude AI from Your Phone: VM Setup Guide

Complete guide to setting up Claude Code in your homelab VM and accessing it securely from your phone via Cloudflare Tunnel - no open ports required.