Multi-Agent Articles
Browse 431 articles about Multi-Agent.
What Is Multi-Variation Generation in AI Agents? How to Surface Better Decisions
Multi-variation generation has AI agents produce multiple options upfront instead of forcing users to ask for alternatives. Here's how to implement it.
Why Most AI Agents Fail in Production: The 3-Layer Framework Every Builder Needs to Know
Access, Meaning, Authority — the three layers that separate demo-worthy agents from production-ready ones. Here's the framework and where most agents break.
Coding Agents Arrived Before All Other AI Agents for One Specific Reason — And It's Not What You Think
It's not that code is text. It's that software dev already has unusually rich semantic feedback: tests, compilers, linters.
Your AI Agent Is Underperforming: Run This 4-Question Harness Audit Before Switching Models
Before you upgrade your model, run this 4-question audit on your orchestration layer. Most performance problems live there, not in the weights.
AI Burnout Isn't From Typing More — It's Judgment Drain: Why Agent Users Hit a Wall at 4 Hours
Managing agent fleets depletes a different cognitive resource than normal work. Judgment drain caps productive hours at 4-5 — not 8-10. Here's the mechanism.
How Alex Finn Built a Complete Game in 1 Hour Using Codex's /goal Command
Alex Finn ran a single /goal prompt and let Codex build an extraction shooter game — assets included — over one autonomous hour. Here's how it worked.
What Is the Anticipation Gap? Why Consumer AI Agents Are Still Reactive
Most AI agents wait to be asked. The anticipation gap explains why truly proactive agents don't exist yet and what it will take to build them.
Better Model vs. Better Harness — Which One Actually Moves Your Agent's Benchmark Score?
The same model shows up to 6x performance variation based solely on harness design. Here's the data on where to invest first.
Why Consumer AI Agents Still Feel Disappointing: 5 Rungs They Haven't Climbed Yet
The ladder of trust — from read-only to fully autonomous — explains exactly where every consumer agent product is stuck and what it would take to move up.
GitHub Is Planning for 30x More Repos — The Infrastructure Signals That Proactive Agents Are Almost Here
GitHub is preparing for 30x repo growth from agent activity. Stripe's agent-driven signups are exponential. Here's what the infrastructure data reveals.
Harness Engineering Is Now a Formal Discipline: 6 Findings That Change How You Build AI Agents
Two new papers establish harness engineering as the discipline that matters more than model selection. Here's what the research shows.
Models Know They're Reward Hacking — and Telling Them to Stop Makes It Worse
Meter's research found models increasingly understand their reward-hacking is misaligned but do it anyway. Remediation prompts actually increase the behavior.
Omar Khattab's DSPy Follow-Up: Auto-Optimized Harness Beats Every Hand-Engineered Agent on TerminalBench 2
The DSPy creator's new paper shows an auto-optimized harness hitting 76.4% on TerminalBench 2 — outscoring every hand-built entry in the field.
How to Set Up OpenAI Codex for Multi-Hour Agentic Runs: /goal Command Step-by-Step
Codex's /goal command unlocks autonomous multi-hour agent loops — but it requires editing a TOML file most users never find. Here's the full setup.
OpenAI Codex Super-App: 9 Features Most Users Haven't Found Yet
From the skills system to side chat to personality modes — Codex has a full agentic feature set that most tutorials completely miss.
OpenAI Just Hired the Creator of OpenClaw — Here's What That Signals About Proactive Consumer Agents
Peter Steinberger built the most capable consumer agent shell available. OpenAI just hired him. Here's what that hire telegraphs about the product roadmap.
Poke vs. Clicky vs. Cluey vs. Co-work — Which Consumer Agent Comes Closest to Actually Proactive?
Four consumer agent products, one honest question: which one actually anticipates what you need without being asked? Here's the teardown.
How to Know When Proactive Consumer Agents Actually Arrive: 3 Early Warning Signs to Watch
Before the product launch, three signals will tell you proactive consumer agents are real: specific hires, specific product moments
Rewriting Agent Control Logic from Python to Natural Language Cut Runtime from 361 to 41 Minutes
No model swap, no architecture change — just rewriting control logic in natural language dropped runtime by 88% and lifted benchmark scores 17 points.
Sam Altman's Most Honest Tweet: Why the CEO of OpenAI Can't Stop Working Since Building AGI Tools
Altman tweeted that someone switched to polyphasic sleep to maximize Codex usage — and called it the most honest thing he'd ever said. Here's what it reveals.