AI Agent Teams: Up to 5.1x the Cost, Rarely Better Quality
AI agent teams cost 1.8x to 5.1x more than single agents in Vals AI's coding test, and only 1 of 4 gained quality. Why higher effort often beats a team.
Cohere North 2: The Enterprise AI Control Room That Works With Any Model
Cohere North 2 orchestrates autonomous AI agents on-prem or air-gapped, across any model vendor — the agentic platform built for regulated enterprises.
Building Production Agentic AI: What IBM Learned the Hard Way
IBM deployed a multi-agent platform with LangGraph and MCP in months. Three hard lessons: instrument early, baseline before build, and solve data access first.
AI Agents Struggle When Their Skill Libraries Grow: Princeton Research Explains Why
A new study ran 8,135 controlled tests to understand why agent skills help performance — and found retrieval accuracy collapses from 29.6% to 3.3% as skill libraries grow from 5 to 100 entries.
AAFlow: The Agentic AI Workflow Paper That Solves the Data Serialization Bottleneck
AAFlow proposes a zero-copy data plane for agentic AI pipelines using Apache Arrow and Cylon, delivering up to 4.64x pipeline speedup. Here's what it means for production AI workflow design.
Cursor Cut AI Coding Costs 22x by Splitting Planning From Execution
Cursor's agent swarm rebuilt SQLite in Rust for $1,339 instead of $10,565 by using an expensive model to plan and a cheap one to execute.
Agentic AI in Marketing: The Shift from Generating Content to Running Execution
Marketing AI moved from generating copy on demand to autonomously running campaigns, optimizing media spend, and managing CRM workflows — without waiting for the next prompt.
Codex Now Encrypts What Agents Tell Each Other — and OpenAI Won't Say Why
Since June 2026, OpenAI's Codex encrypts agent-to-subagent instructions in GPT-5.6 workflows, leaving developers unable to audit how tasks are delegated internally.
ChatGPT Work: OpenAI's Agent That Delivers the Finished Output
GPT-5.6 launches alongside ChatGPT Work — an autonomous agent integrating 12 enterprise tools. It doesn't suggest what to do with your data. It does the work and hands you the result.
Four Engineering Pillars for Reliable Agentic AI in Production
Bayer's PRINCE platform proves agentic AI reliability comes from engineering context and harness, not better prompts. Four replicable pillars — context engineering, harness engineering, layered reflection, structured retrieval — from a system live since 2024.
Agentic AI Reliability: Two Engineering Disciplines Most Teams Skip
A Thoughtworks case study on PRINCE, a drug discovery agentic AI platform, reveals why context and harness engineering — not model choice — determine production reliability.
OpenAI Symphony: 6x More Merged PRs When Agents Self-Orchestrate
OpenAI's Symphony turns Linear into a coding agent control plane — each ticket gets its own agent, Symphony restarts crashes, and early teams saw merged PRs increase sixfold in weeks.
Agentic AI Borrowed Three Patterns from Microservices — and Made Each Worse
Cornelia Davis at Temporal traces how agentic AI is recapitulating the cloud-native transition — decomposition, event-driven architecture, and state management — but compressing years of lessons into months.
Cursor 3 Killed the IDE Layout: What an Agent-First Interface Actually Looks Like
Cursor 3 replaces the traditional IDE with a parallel agent fleet interface — and it signals where every serious coding environment is headed in 2026.
Kensho's LangGraph Architecture: Multi-Agent Financial Data Retrieval at S&P Global
S&P Global's AI engine built Grounding — a router, domain agents, and aggregation layer on LangGraph — to unify fragmented financial data retrieval with trusted outputs.
Claude Code Gets a Cron: What Background Scheduling Means for Agentic Workflows
Claude Code's new /loop command enables cron-style scheduled tasks — error log monitoring, PR auto-fixes, morning summaries — running unattended in the background.
The Agentic Deep Dive #1: The 'Trust but Verify' Protocol
How to implement high-reliability research agents using LangGraph Critic nodes and cross-model verification.
Agentic CI: The Future of Repository Automation in 2026
Exploring GitHub's new Agentic Workflows and how Continuous AI is transforming DevOps into a series of autonomous, reasoning-driven tasks.
The Rise of Agentic AI: Building Autonomous Operations in 2026
Why the shift from assistive copilots to autonomous multi-agent ecosystems is the defining technical architecture of the decade.
Agentic Workflows: Beyond the Prompt to Orchestrated Logic
How the industry is shifting from single-shot prompts to complex multi-agent graphs in 2026.
Why Multi-Agent Systems are the Future of Productivity
Discover how specialized AI agents working in concert outperform monolithic models.
The Rise of Agentic AI in 2026: From Chatbots to Autonomous Coworkers
Exploring the shift from reactive AI to proactive agents that redefine how we work.