How to build AI agents from scratch (9 steps): 1. Purpose & scope 2. I/O schemas 3. System instructions 4. Reasoning + tools 5. Multi-agent orchestration 6. Memory & context 7. Multimodal 8. Structured outputs 9. UI / API Ship agents that do work, not just talk.
PROMPT ENGINEERING
-
Grok Training and Agent Setup Guide Now Available
By
–
The fun thing is they offer training too. And Grok can teach you how to set it up and get your first agent running anyway.
-
Save and run one today with Claude
By
–
Most people will read this and go back to prompting Claude like a search engine. Save it. Run one today.
-
Track Project Decisions and Requirements Across Weeks
By
–
6/ Keep Track Across Weeks "This project runs for a month: [describe it]. Keep track of every decision made, how requirements have shifted, and what we have already tried. Use context compaction so nothing important gets lost as we keep going."
-
Think Before You Answer: Complex Problem-Solving Framework
By
–
4/ Think Before You Answer "Here is a complex problem: [describe it]. Do not respond yet. First tell me how deep this actually needs to go, what information is still missing, and which assumptions should be questioned. Then solve it at the right level."
-
Multi-Agent Task Coordination and Parallel Execution
By
–
3/ Run Everything At Once "I need all of these done at the same time: [list tasks]. Assign each one to a separate agent, keep them coordinated, report back on all of them as they progress, and bring the results together when finished."
-
Front-Load Context Once for Better AI Responses
By
–
2/ Front-Load Your Context Once "I am working on [project name]. Everything you need to know is here: [paste context]. Pull from this in every response going forward without me having to repeat it. Tell me what you have stored."
-
7 Daily Claude Prompts to Stay Ahead at Work
By
–
Breaking: You are already behind if you are not using Claude at your job. The people outworking you are not smarter. They are using these 7 prompts every single day. Copy them here:
-
Building AI Agents: Vision and Iterative Improvement Strategy
By
–
Two ways: 1. Start with a clear, defined, vision of what you are building.
2. Iterate. I talk with my agents many times to get them to improve what I'm building. It's deeper than that, of course, but this is X and only have a small amount of time. 🙂 -
Genie Agent Mode: AI-Powered Data Analysis and Hypothesis Testing
By
–
Genie Agent Mode changes the class of questions you can bring to your data.
— Databricks (@databricks) 17 avril 2026
Instead of returning a single query result, it investigates like a data analyst, planning an approach, testing hypotheses, and iterating toward an explanation. Ask questions like:
– Why did our churn… pic.twitter.com/gIgxt1SumqGenie Agent Mode changes the class of questions you can bring to your data. Instead of returning a single query result, it investigates like a data analyst, planning an approach, testing hypotheses, and iterating toward an explanation. Ask questions like: – Why did our churn