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ai-agents
246 postsWhy AI Agents Should Propose Infrastructure, Not Execute It
AI agents with direct cloud API access risk emergent infrastructure mutations. A governance model splits propose, judge, and execute authority.
Inside the New Agent Swarm: Coordination at 1,000 Commits/Sec
A deep dive into how a new AI agent swarm architecture uses planner-worker hierarchies and a custom VCS to coordinate work at 1,000 commits per second.
HyperShots renders App Store screenshots with CSS, not AI pixels
HyperShots generates App Store screenshots via CSS and headless Chrome at exact pixel specs, eliminating rejections caused by AI image models.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comSynapsor Runner Lets AI Agents Propose Changes, Not Execute SQL
Synapsor Runner is an open-source MCP runtime giving AI agents reviewed semantic tools instead of raw SQL, keeping database write authority outside the model loop.
Solo Lead Playbook: Running Product, Architecture and Backend with AI Agents
How one founder runs product, architecture, and backend engineering solo using a single AI coding agent, one collaborator, and a five-phase workflow.
agent-gate: keep your AI agents from having unchecked power
agent-gate is a dependency-free MIT Python layer that gates AI agent actions behind deterministic checks and one-time tokens, blocking prompt injection and irreversible mistakes.
Why AI Agents Must Never Choose Their Own Acting Subject
AI agents shouldn't self-assign identity via tool arguments. Learn why acting subjects must come from trusted boundaries, not model output.
Does the Harness Come Before Pretraining? A Data Flywheel View
An analysis of how AI agent harness design and pretraining are interdependent, shaping data flywheels and model biases in coding agents.
Tracing Async AI Agents: Manual OpenTelemetry Propagation with SigNoz
How to fix broken OpenTelemetry traces in async AI agent pipelines using manual context propagation and SigNoz, from queue to LLM call.
The Real Divide in AI Verification: Code vs. Judgment
An AI agent's false 'I will remember' claim exposed why code-based gates, not judgment calls, are needed to verify agentic AI workflows.