The Rise of Agent-to-Agent Communication

Simon Willison shared a fascinating development in how developers are working with multiple AI coding agents simultaneously. The approach involves having agents read a shared AGENTS.md file, register with an "agent mail" system, and introduce themselves to other agents before coordinating on tasks.

"Before doing anything else, read ALL of AGENTS dot md and register with agent mail and introduce yourself to the other agents. Then coordinate on the remaining tasks"

This represents a significant shift from treating AI agents as isolated tools to viewing them as collaborative team members that need coordination protocols—much like human developers working on the same codebase. Kevin Kern's related observation that Codex "usually handles it by itself" when dealing with MCP tools suggests we're entering an era where agents are becoming sophisticated enough to self-organize around available resources.

Microsoft's Agent Lightning: Systematic Optimization

Akshay highlighted Microsoft's latest open-source contribution to the agent ecosystem. The problem it solves is painfully familiar to anyone who's built with AI agents:

"Building with AI agents almost never works on the first try. You spend days tweaking prompts, adding examples, hoping it gets better. Nothing systematic, just guesswork."

Agent Lightning aims to replace the trial-and-error approach with something more methodical. This addresses one of the core friction points in agent development—the gap between a working prototype and production-ready reliability.

The Business Side: Financial Qualification First

Liam Ottley offered a counterpoint to the technical discussions with hard-won sales wisdom:

"Never pitch full-blown 'AI automation' to businesses. Before you get into the weeds and throw a proposal together, you have to take the most important step: Financial qualification."

This is a crucial reminder that the most sophisticated AI system means nothing if you can't identify prospects who can actually pay for it. The excitement around agent capabilities needs to be balanced with pragmatic go-to-market strategies.

Practical Entrepreneurship

Rounding out the day, The Backlink Guy shared a grounded approach to building local service businesses with simple SEO strategies, while TJ Bongiorno delivered motivational fuel for anyone sitting on the fence about starting something new:

"Start building the thing this weekend. Take the first step. Buy a domain name and make a logo. Do ANYthing."

Key Takeaways

1. Multi-agent coordination is moving from concept to practice, with developers creating explicit communication protocols between AI agents

2. Systematic optimization tools like Agent Lightning may finally solve the "prompt tweaking purgatory" that plagues agent development

3. Selling AI requires the same fundamentals as selling anything else—qualify your prospects financially before investing in proposals

4. The gap between AI enthusiasm and business reality remains wide; bridging it requires both technical sophistication and sales discipline