aiagentsanthropicguide
Claude Fable 5 vs Opus 5: which model should your AI agents use?
Fable 5 or Opus 5? Choose by mission difficulty and cost per successful task — not by putting Anthropic’s strongest model everywhere.
10 min read
Product research desk
Stellary Product Desk
The Stellary Product Desk writes about delivery systems, board structure, cockpit-style piloting, documentation practices, and software evaluation criteria for product and engineering teams. It specializes in trade-offs, workflow design, and adoption patterns.
About this desk
Documents real delivery workflows, planning systems, workspace design, and how product teams operate with AI in the loop.
Expertise
Delivery workflowsBoard designProject pilotingTeam adoption
Articles
13
published or maintained articles
Articles
These articles are currently owned or maintained by this editorial desk.
aiagentsopenaiguide
GPT-5.6 Sol, Terra, and Luna: which OpenAI model should your AI agents use?
Sol, Terra, or Luna? Pick GPT-5.6 by mission difficulty, volume, and cost per successful task — not by putting the strongest model everywhere.
9 min read
aiagentsmcpapiguide
MCP vs REST API: which architecture should you choose for AI agents?
MCP or REST API for an AI agent? Choose based on who picks the operation: the code, the model, or both in a hybrid architecture.
10 min read
aiagentsautomationsguide
AI agent, AI workflow, or automation: which should you choose in 2026?
Choose between automation, an AI workflow, an agentic workflow, and a bounded autonomous agent based on who picks the next step, cost, latency, and risk.
13 min read
aiagentsguide
AI Model Fusion: Why the Future Is Not One Model, but a Multi-Agent Architecture
AI model fusion: multi-agent pipelines combine several models, then compare and judge their answers to deliver a more robust result than a single model alone.
14 min read
guidedocumentationagentsai
Documentation and AI Memory: Why Your Agents Should Not Start From Zero
Why documentation and memory are the two foundations of reliable AI agents: context, RAG, governance, trust, and practical habits for modern teams.
18 min read
aiguideproject-management
What Is AI Project Management? A Practical Guide for 2026
Understand AI project management in 2026: assistants, automations, operational agents, governance, MCP, benefits, risks, and a practical adoption plan.
7 min read
productaipiloting
AI-Assisted Project Piloting: From Signals to Controlled Action
Learn how AI-assisted project piloting connects goals, delivery signals, decisions, agents, and controlled actions without replacing human accountability.
6 min read
guideknowledgeproduct
Knowledge Management for Dev Teams: Stop Losing Context
Why dev teams lose critical knowledge and how to build a system that keeps documentation alive, searchable, and connected to your workflow.
5 min read
aiguideproduct
How AI Improves Remote Team Collaboration in 2026
Practical strategies for using AI to bridge the gap in distributed teams — from async decision-making to automated standups and intelligent notifications.
5 min read
aiguideproject-management
How to Run Better Sprint Planning with AI in 2026
Use AI to prepare Sprint Planning evidence, surface dependencies, and compare capacity scenarios while the Scrum Team keeps ownership of the Sprint Goal and forecast.
7 min read
project-managementguide
Kanban vs. Scrum in the AI Era: How to Choose
Compare Scrum, Kanban, and hybrid delivery in 2026, then see where AI can prepare evidence without replacing goals, flow policies, or team judgment.
6 min read
aiguideproduct
How to Reduce Unnecessary Meetings with AI
Use AI standups, decision briefs, and project signals to replace status-only meetings while keeping the conversations that need real-time human judgment.
6 min read