Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
Managing the Hidden Overhead of AI Software Engineering
Jessica Doering on verification debt: AI coding tools move the bottleneck from typing to review, why opening another agent terminal feels productive, and habits that spend reclaimed time on specs, docs, and understanding.
3 min · 725 words
Building Software That Can Prove Agents WrongWhat changes when implementation becomes cheaper than verification
Rafael Câmara argues that once coding agents implement faster than they can verify, the limiting factor is application design: software must expose cheap, independent evidence that can prove an agent's change wrong—not just look right on the happy path.
2 min · 486 words
Sending SMS with an Agentic AI using Twilio and Hermes Agent
Twilio posts cloud communications trends, customer stories, and tips for building scalable voice and SMS applications with Twilio's APIs.
9 min · 1,981 words
It was never about coding 📝 post "With the AI doing the coding, do we just spend all day reviewing its output?" The rapid onset of impressively capable coding agents continues to raise this question in conversations with peers, to [press interviews](https://blog.dyanacek.com/2026/03/12/coding after coders/), to [podcasts](https://blog.dyanacek.com/2026/07/01/code with jason with david/).
9 min · 1,971 words
Everything Is a Stream: runtime composability over compile-time plugins
Antigma Labs stabilizes Ante v0.2.0’s Unix-inspired wire protocol—operations in, events out over stdio, sockets, or WebSockets—so agent engines stay separate from UIs while SemVer locks the streaming contract.
7 min · 1,520 words
Max Woolf shows how iterative agentic coding—prompting agents to repeatedly speed up Rust code—produced solutions faster than established libraries, with concrete methodology and caveats.
22 min · 5,140 words
Kit Langton explains OpenCode 2’s hot-reload architecture: plugins register catalog transformations up front so models, tools, and configs update live across sessions without restarts or cache busts.
5 min · 1,112 words
Arcturus Labs compares OpenAI’s emerging decision-model direction with TypeSafe’s Jev—and asks whether a frontier lab can absorb the System One / structured-decision niche startups are building.
12 min · 2,748 words
How Google Agent Substrate Works: 250 Agents on 8 Pods
A technical breakdown of Google’s Agent Substrate: how it multiplexes hundreds of stateful agent sessions onto a handful of Kubernetes pods with fast suspend/resume.
11 min · 2,511 words
Introducing Strands harness: frontier performance with 28% lower token cost
Arron Bailiss introduces Strands harness: a fully assembled, customizable local/cloud agent that aims for Claude Code/Codex-like “it just works” behavior with about 28% lower token cost.
5 min · 1,198 words
AI coding has made CI a bottleneck, so we reworked ours to keep up
Linear's Mufeez Amjad explains how agent-accelerated shipping made CI the bottleneck, and how they cut PR wait time and runner cost while test suites nearly quadrupled.
8 min · 1,907 words
dlab Open Source Week: Frontier AI on Your Own Hardware
Tim Dettmers argues that small academic labs can compete by building coherent open-source ecosystems rather than isolated papers. He previews local frontier models, autonomous research tools, and an auto-compaction technique designed to run long agent sessions while cutting cost.
1 min · 276 words
M5 Ultra Mac Studio Review: The Dream Mac for Local AI Agents
Federico Viticci reviews the M5 Ultra Mac Studio with 256 GB RAM—why it is a dream machine for local AI agents, what workloads it unlocks, and where it still falls short.
14 min · 3,293 words
Rebuilding Nym’s agent around Jev
How Nym rebuilt its agent stack around TypeSafe’s Jev for guardrails, browser actions, and tool selection—with benchmarks and a shopping demo.
10 min · 2,186 words
Language-model groups overstate consensus when replaying human deliberation on a reasoning task
LLM groups replaying human Wason discussions reach full consensus far more often than humans—partly because agents almost always speak up—cautioning against treating multi-agent agreement as truth.
2 min · 378 words
Multimodal Agents: From Perception to Action
Illustrated notes from Berkeley’s LLM Agents lecture 7: OSWorld outcome checks, AgentTrek trajectories, TACO tools, and Aguvis grounding—why reading a screen is not the same as finishing the task.
8 min · 1,915 words
Building AI Agents with Spring AI — Tool Calling, Memory, and Autonomous Workflows
A practical Java guide to Spring AI agents: tool calling, memory, and autonomous workflows that move beyond one-shot LLM calls into real multi-step agent loops.
12 min · 2,810 words
Why AI Coding Agents Crash at 3 AM: The Happy-Path Mirage & The Forced Continuity Defect
Part 2 of Synthetic Scars: why agents that look flawless on staging fail in production—happy-path training, forced continuity, and transferring pager-duty instincts to autonomous coders.
10 min · 2,387 words
Your AI Coding Agent Can Be Attacked by the Repository It Opens
Why opening an untrusted repo with an AI coding agent is a security boundary problem—prompt injection via files, tool abuse, and practical defenses for agent workflows.
4 min · 1,028 words
Done, Keys, and a Second Check
An operating-model essay arguing enterprises need ownership of done, keys, escalate/monitor rights, and a second check—not just consumer-style AI agents that complete tasks.
5 min · 1,180 words