Categories AI

Agent Feedback Tips – Ben’s Bites

Hello everyone! I’m excited to share a new approach I’m experimenting with in my building process.

When agents request feedback, the process often feels cumbersome, categorized roughly as follows:

  1. Type your response

  2. Use voice-to-text for your input

  3. Add images to your feedback

  4. Encourage the agent to utilize their browser

Recently, I began screen-recording my thoughts and sharing that video file directly with my agent.

This recent screenshot captures my process from about half an hour ago. It assembles a comprehensive visual report that is straightforward to review. I can navigate to various websites and applications, showcasing examples of excellence from others, while emphasizing key aspects that are recreated with GIFs for clarity.

The system generates an ‘actions’ checklist at the bottom, making it feel seamless to progress from screenshot to feedback to actionable steps for the agent.

This approach is already proving effective. Plus, I have these HTML files saved in my projects for future reference. They’ll be great for maintaining a build log as well.

While this method may not be ideal for those who are mindful of tokens, I could potentially leverage ffmpeg to create actual video clips if necessary. Agents typically process frames effectively, so it would mainly benefit me in that scenario.

I’ve also turned this process into a simple skill:

name: video-to-html

description: Use when the user wants you to convert their video into a structured HTML document.

This skill transforms the user’s video into a structured HTML document by transcribing the content and extracting keyframes linked to important timestamps. When discussing static topics, it even creates short GIFs from those keyframes.

I’d love to hear about any interesting use cases or variations you might have! 😊

Ben’s Bites is supported by Hyperagent from Airtable

Hyperagent, the cloud agent system equipped with complete computing environments, is offering $10 million in inference credits to assist founders in building and managing agent-first companies. The first 500 qualifying applicants will gain access to this limited founder offer. Applications close May 31st.

  • Your Claude plan is changing if you use third-party tools (such as Conductor, Zed, Openclaw, T3 Code, etc.) with it.

    • A separate limit will apply for all such usage, provided as extra monthly credits equivalent to your plan’s value.

    • No subsidized tokens will be allowed—unused credits won’t roll over, and any usage after exhausting these credits will be billed at API rates.

    • Using Claude in Claude Code, the Claude app, etc., will remain the same and will not be affected.

    • Changes will take effect starting June 15th, but they will increase your weekly rate limits by 50% for the subsequent two months.

  • Google recently unveiled some Gemini on Android updates ahead of I/O, adding features such as auto-form completion, converting lengthy voice notes to concise text, and some app automations under the name Gemini Intelligence. They also introduced a new class of laptops termed Googlebooks, which should not be confused with Google Books.

  • Notion has launched a developer platform, highlighting a markdown API as its most significant feature. Developers can sync external data into Notion, build tools for Notion Agents, run code on Notion’s infrastructure, and eventually integrate agents like Claude/Codex as team members. This tool is likely to see engagement beyond traditional developers.

  • Vercel published an AI Gateway production index based on real usage across applications and agents. Anthropic leads spending (61%—largely due to opus), while Google leads token volume (38%—driven by flash), and agentic workloads represent 59% of overall token usage. Most large teams use multiple models instead of relying on a single provider.

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