Agentic Engineering
Also written: Agentic ML Exploration, A-MLE, Agentic development
Building AI systems that can act and decide on their own to perform tasks and solve problems.
Agentic engineering is about creating artificial intelligence that can act independently. Instead of just following direct commands, these AI systems can figure out what needs to be done, make plans, and execute steps to reach a goal.
Think of it like building a smart assistant that doesn't just wait for you to tell it every single action. You might ask it to plan a trip, and it would figure out flights, hotels, and activities on its own. This involves designing AI that can reason, adapt, and take action in the real world or digital environments.
Agentic engineering focuses on the design, implementation, and orchestration of autonomous AI agents capable of performing complex tasks and making decisions. This paradigm shifts from traditional command-response AI to systems that exhibit initiative, planning, and self-correction. It often involves integrating multiple AI models, tools, and custom code to create robust workflows that can operate with minimal human oversight.
Agentic engineering is a growing focus as labs like OpenAI and Google Gemini explore how to make AI systems more autonomous. Recent discussions highlight building AI agents that can work together, integrate with code, and perform complex tasks without constant human input, moving beyond simple prompt engineering.
- 🎙️Voices from the Skies: Build Your Own Personal Assistant with GitHub Copilot AppMicrosoft · Microsoft Developer on YouTube ·
- Vibe coding in the pit lane 🏁Google · Google Cloud Tech on YouTube ·
- Agentic Engineering Benchmarks: How I RANK Astra, Fable 5.1, and Open-WeightsAnthropic · IndyDevDan ·
- Agentic ML Exploration (A-MLE) for Ads RankingAnthropic · arXiv cs.AI ·
- Are Agent Swarms USEFUL? OpenAI’s GPT-6 Astra SWARM TakeawaysOpenAI · IndyDevDan ·
- Research acceleration: The view inside OpenAIOpenAI · Simon Willison ·
- FIXING Opus 5: PROOF that Prompt Engineering IS NOT DEADAnthropic · IndyDevDan ·
- My Super Simple Software Factory (For Agentic Engineers)Anthropic · IndyDevDan ·
- Engineers... STOP Picking GPT-5.6 Sol OR Claude Fable 5… FUSE THEMAnthropic · IndyDevDan ·
- FORGET Loop Engineering. Agentic Engineering is about THISAnthropic · IndyDevDan ·
- SEE CMUX SOLVE Multi-Agent Orchestration (Claude Code and Pi Agent)Anthropic · IndyDevDan ·
- PLANS For Fable 5: Rebuilding My /Plan Skill for Mythos Class ModelsAnthropic · IndyDevDan ·
- Top #1 Opportunity for Senior Engineers: Agentic EngineeringAnthropic · IndyDevDan ·
- Start building with Gemini 3Google · Google DeepMind Blog ·
- Anthropic Claude
- Anthropic's research and benchmarks evaluate AI models like Claude Fable 5.1 on their agentic capabilities, suggesting a focus on autonomous task performance.
- Google Gemini
- Google Gemini's 'Antigravity' project and discussions around 'Software Factories' indicate an interest in using AI agents to directly process information and build systems.
- OpenAI ChatGPT
- OpenAI is actively researching and implementing agent swarms, using systems like GPT-6 Astra to accelerate development and engineer workflows for real outcomes.
- Prompt Engineering
- Prompt engineering focuses on crafting inputs to guide an AI
- AI Workflows
- AI workflows are sequences of tasks, while agentic engineering is
- Reinforcement Learning
- Reinforcement learning is a training method for AI, wher
The term 'agentic engineering' emerged from the AI community as a way to describe the practice of building AI systems that exhibit agency, meaning they can act independently to achieve goals. It builds upon concepts from AI agents and autonomous systems research.
Try using a tool like ChatGPT's custom GPTs or a similar platform that allows for custom instructions and tool integration. Ask it to perform a multi-step task, such as planning a weekend trip, and observe how it breaks down the task and uses its capabilities to achieve the goal.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- ChecklistFramework for agentic engineering developmentA 5-pillar framework for focusing time, money, and compute in agentic engineering. · 30 min
- HeuristicCombine agents with code for better performanceAgents plus code outperform agents alone for cost, speed, and reliability. · 15 min
- HeuristicSoftware factories give more leverage on your promptCombine agents with code in a software factory for greater control and better outcomes. · 15 min
- Anti-patternPicking a single AI model instead of combining themDon't pick one AI model; combine multiple models for better agentic engineering outcomes. · 10 min
- Anti-patternRelying solely on agents without custom codeUsing only agents without custom code leads to higher costs, slower speeds, and more errors. · 10 min
Questions people ask
- What is the difference between an AI agent and agentic engineering?
- An AI agent is the system that can act autonomously, while agentic engineering is the discipline of designing, building, and orchestrating these agents.
- Is agentic engineering the same as prompt engineering?
- No, prompt engineering is about crafting inputs for AI, while agentic engineering is about building AI systems that can act independently and make decisions.
First seen on Subvolts Nov 18, 2025. Updated Oct 12, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.