Mythos Begets Fable, Cursor's Composer 2.5, Agents Building Agents
The Batch / 6/12/2026
💬 OpinionDeveloper Stack & InfrastructureIdeas & Deep AnalysisTools & Practical UsageModels & Research
Key Points
- The article argues that desktop AI agents can go beyond chat by reading and editing local files, sending/receiving messages, and producing scheduled outputs like daily news summaries.
- It explains a common design pattern for desktop agents: define callable tools (e.g., file access, web fetch, messaging), grant permissions with guardrails, and let a frontier LLM choose which tool to use at each step.
- The key software component is described as an “agent harness,” which wraps the LLM and runs the loop that decides the next action in an agentic system.
- It contrasts current practice: many reliable agentic workflows rely on developer-specified control flow rather than the LLM deciding the next step, but recent LLM progress makes an LLM-driven harness a more viable alternative.
- The piece highlights that while CLI coding agents have dominated agent systems, there is growing value in non-CLI desktop agents with user-friendly interfaces spanning chat, CLI, and desktop contexts.
Continue reading this article on the original site.
Read original →Related Articles
Black Hat USA
AI Business
Meta’s months-old AI unit is a soul-crushing gulag, say the engineers stuck inside it
TechCrunch
Rails Won Because It Had Opinions. AI-Native Apps Need the Same Thing.
Dev.to
AI Evals, Part 2: Error Analysis The Unglamorous Superpower Behind Good Evals
Dev.to
Kimi K2.7-Code Cuts AI Costs, but Benchmarks Crack
Dev.to
