Faster LLMs, Bigger Demands: Why Coding Agents Won’t Stabilize Soon
137
Faster LLMs will reshape coding workflows and productivity, but escalating demand, hardware limits, and pricing pressures mean a bumpy, fast-changing road ahead.
Reading List
AI Amplifies Seniors, Not Juniors
461
Today, AI amplifies senior engineers’ impact instead of democratizing coding for juniors.
AI Agents Can Already Do Lean Proofs—But They Still Need a Project Manager
219
A general-purpose AI coding agent can already do real Lean proof engineering with guidance, hinting that theorem proving may soon be cheap and automated despite today’s rough edges.
Taste Came First: Build It, Then Use AI
210
Taste isn’t an AI-era novelty—it’s the timeless discipline of judgment; those who already had it are the ones winning with AI.
Prompted to Perform: A 22% Lift for GPT-5-mini on Tau² Telecom
197
A structured prompt rewrite turned vague policies into checklists, boosting GPT-5-mini’s telecom benchmark accuracy by 22% and unlocking previously unsolvable tasks.
Deep Orchestrator: A Simple MCP Loop That Makes Deep Research Work
Keep the agent simple: plan–execute–deterministically verify in a loop, with MCP tools, targeted memory, and a small policy engine.
ApeRAG: Production-Ready Multimodal GraphRAG with Agents and MCP
ApeRAG is a production-grade, multimodal GraphRAG platform with AI agents and MCP, built for hybrid retrieval and scalable K8s deployment.
GPT-5 Thinking Makes ChatGPT a Surprisingly Competent Research Assistant
361
GPT-5 Thinking turns ChatGPT into a competent, mobile-friendly research agent that interleaves reasoning with web search and tools to deliver verifiable, deep results—provided you guide and sanity-check it.
Trust-First Architecture Beats Smarts for AI Agents
208
Users adopt AI agents that are architected for trust—start simple, integrate thoughtfully, expose limits, and escalate gracefully.
Stop Building Multi-Agents: Context Engineering for Reliable LLM Agents
123
Skip multi-agents for now: unify decisions in a single-threaded agent that shares full context, and use summarization to scale.
Standardizing the AI Orchestrator as a Model Virtual Machine
234
Treat the AI orchestrator as a secure, standardized virtual machine so models can safely and portably use tools and data under strict governance.