When One Agent Isn't Enough
What happens when agents negotiate with agents? The math becomes visible, the romance disappears, and the questions left over don't have answers.
What happens when agents negotiate with agents? The math becomes visible, the romance disappears, and the questions left over don't have answers.
MCP, A2A, A2UI, commerce protocols: they're not layers, they're orthogonal. Here's who's using what in production and when you need which.
Pure chat fails for complex work. The future isn't replacing UI with chat — it's coherent shells with disposable pixels inside. Here's what that looks like in practice.
My attempt at a framework for deciding where agentic experiences belong in your product. Not everything needs an agent — here's how I think about finding the candidates that do.
Software is decoupling into three persistent layers: System of Record, Agentic Layer, and Pixels. This isn't prediction — it's already happening.
Your enrichment data lives in Clay. Your interaction history lives in HubSpot. Your dialer has a 250-character limit. The middle layer is where you reconcile all of it.
TDD works for humans because humans carry domain knowledge. Agents don't. The research flow makes requirements explicit before implementation begins.
Investigation fills your working context with stuff you don't need afterward. Sub-agents keep it separate — send inputs, receive outputs, don't carry intermediate state.
Plan mode gives you a document. Beads gives you a graph of work with dependencies that the agent understands. Tasks small enough to survive context loss, blocking relationships that prevent premature work.
If a task is verifiable, it's optimizable. Quality gates that reject bad code, visual testing so the agent can see what it built, and the feedback loop tying everything together.
A prompt is a one-time instruction. A plugin packages expertise into something that persists — commands you invoke, skills that load on demand, hooks that run automatically.
Adding an MCP server to Claude Code takes one command. Changing how your agent approaches problems takes intention. Here's how to enforce doc-first behavior.
Most developers use maybe 10% of what Claude Code can do. Five pillars unlock the rest: context, skills, verification, persistence, and scaling.
Technical sales requires preparation, not automation. We spend 10x more preparing for a call than making it. AI handles research. The call itself? That's human.
Rows don't know about each other. That single constraint means Clay can't track prospects over time, merge records, or maintain history. Here's why — and what to do about it.
AI coding agents are the most capable tools we have. Your sales knowledge should be queryable by them. Here's how to set it up in 30 minutes.
A practitioner's guide to defending against prompt injection. Structured outputs, trust boundaries, and patterns that actually work.
Prompt injection is the SQL injection of 2026. Here's why vibe-coding won't save you.
Why 95% of Claude Code skills fail — and what actually works. Most AI skills are system prompts in a trench coat. Here's the diagnosis.
Workflows, Not Personas. How to build skills that encode developer behavior, not library descriptions.
Managing Entropy. How to organize skills so they don't collapse under their own weight.
How to build Claude Code custom commands that work. The 5-phase process: archaeology, stress test, codification, compilation, and QA audit.