the experience will get better but here’s something that’d help: 1. create a goal md and put your ramblings there
2. ask codex to use set_goal and refer to goal md and ask for approval from you before it gets set go all through compactions codex will refer to your “ramblings”
PROMPT ENGINEERING
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Using goal.md and set_goal with codex for compactions
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Success with Codex: Convert Writing Samples into a Skill
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it’ll get better sooner thank you think but later than you want! in the meantime I’ve had tremendous success by give codex samples of writings and artefacts that I like and having it convert that into a skill use that skill for whenever it writes (ask codex to add it to your
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Using time in agents: obsession fix via system prompt
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Pls do this! Makes agents so much better. They do tend to get a bit obsessed with time if they see it every message or two but a line in the system prompt usually fixes that.
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GEMINI + YOUTUBE: my prompts for automatic income
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GEMINI + YOUTUBE = $$$ The majority use Gemini to summarize texts.
I used it to create YouTube content that works for me while I sleep. And it generates automatic income for me. These are the exact prompts I used. -
Build no-code agents with everyday language using LangSmith Fleet
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With LangSmith Fleet, you can start creating agents using every day language.
— LangChain (@LangChain) 4 juin 2026
Enroll in our LangChain Academy Quickstart course to learn how to build no-code agents for real work. https://t.co/k2AhiIz7fB pic.twitter.com/LLYyyT1oIpWith LangSmith Fleet, you can start creating agents using every day language. Enroll in our LangChain Academy Quickstart course to learn how to build no-code agents for real work. https://
academy.langchain.com/courses/quicks
tart-agent-builder
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LangSmith Engine automates agent team improvement loop from traces
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Most agent team runs the same manual improvement loop:
— LangChain (@LangChain) 4 juin 2026
Trace → find failure patterns → fix prompts or code → create evals → test → ship → repeat
LangSmith Engine helps turn production traces into named issues, root-cause analysis, proposed fixes, and stronger eval… pic.twitter.com/TozrvKwfTHMost agent team runs the same manual improvement loop: Trace → find failure patterns → fix prompts or code → create evals → test → ship → repeat LangSmith Engine helps turn production traces into named issues, root-cause analysis, proposed fixes, and stronger eval
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Design Mode in Canvases: Annotate UI elements for faster AI edits.
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Design Mode is now available in canvases.
— Cursor (@cursor_ai) 4 juin 2026
Select and annotate UI elements directly in a canvas to guide Cursor's edits and iterate more quickly. pic.twitter.com/5XFOayiPhSDesign Mode is now available in canvases. Select and annotate UI elements directly in a canvas to guide Cursor's edits and iterate more quickly.
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Cursor AI: Interactive report for agent context usage in canvas
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Cursor can now show your agent's context usage as an interactive report in a canvas.
— Cursor (@cursor_ai) 4 juin 2026
The context explorer breaks down where tokens go across the system prompt, tool definitions, rules, skills, and more. pic.twitter.com/FccilnZzOzCursor can now show your agent's context usage as an interactive report in a canvas. The context explorer breaks down where tokens go across the system prompt, tool definitions, rules, skills, and more.
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Anthropic Engineer Reveals Claude’s Simple Internal Prompting Secrets
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An engineer at Anthropic just shared how the team prompts Claude internally. It looks nothing like the 3,000-word mega-templates the gurus sell you, and the difference is the entire lesson. Look at what it contains. It names real tools from memory: /goal, AskUserQuestion, the
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Flows Agent lets you iterate and modify the pipeline dynamically
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Flows Agent lets you iterate through conversation. Tell it to try a warmer voice, swap the background, or generate a version in Spanish. The agent modifies the pipeline and re-runs without rebuilding from scratch.