Topic

Superconductor

All digests tagged Superconductor

How I used AI to build a slop-free web page thumbnail

· 4:58

How I used AI to build a slop-free web page

The speaker details a process for achieving high-quality web design for the Multiplayer AI Manifesto page, emphasizing that while AI was used, the core content and creative direction were human-driven. The process involved writing all copy manually, specifying a desired 'vibe,' and utilizing a 'random-string trick' in prompts to generate design variety. The site was built by launching multiple AI agents (including Fable 5.1) on the Superconductor platform, comparing their screenshots, and then engaging in extensive, iterative, multi-agent chat sessions to refine the final product.

Key takeaways

  1. Content Creation

    All copy was written by hand, and the desired visual 'vibe' was specified in the source document, avoiding AI writing for the text.

  2. Design Variety Trick 2:00

    To achieve design diversity, the speaker used a 'random-string trick' in the prompt, instructing the AI to generate a long alphanumeric string and apply it to the design without mentioning the string itself.

  3. Multi-Agent Testing 2:20

    The process involved sending a Notion link to Superconductor to build the site, requesting a sequence of screenshots using Playwright. The speaker launched 14 different AI implementations (e.g., Fable 5.1, CodeXes, open-source models) to compare results.

  4. Iterative Refinement 3:00

    The final site was refined through a long, multiplayer AI chat session (333 messages), where the speaker and co-founder provided visual feedback (via screenshots) to the chosen agent (Fable 5.1) for continuous improvement.

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Multiplayer agentic engineering — Arjun Singh, Superconductor thumbnail

· 18:44

Multiplayer agentic engineering — Arjun Singh, Superconductor

The talk outlines 'multiplayer agentic engineering,' focusing on how human teams and AI agents can collaborate effectively across diverse systems. Key recommendations include making workflows model-agnostic, integrating agents into every human interface (Slack, GitHub), ensuring work visibility via artifacts, and treating all external signals (emails, meetings) as code inputs. Crucially, the speaker emphasizes that these advanced agentic workflows must operate within isolated cloud environments to enforce least privilege and prevent data exfiltration.

Key takeaways

  1. Model Agnosticism is Critical 5:01

    Do not rely on a single LLM or harness, as the best model changes frequently. Utilizing open-weight models (like GLM 5.2) allows teams to stay in control of costs and maintain workflow continuity.

  2. Agent Interfaces Must Be Universal 6:48

    Agents should not be trapped on a single laptop or platform (e.g., Slack). The agent session must maintain context when moving between relevant interfaces like Slack, the desktop app, and GitHub.

  3. External Signals Must Become Code 10:10

    Treat all external signals—customer calls, meetings (e.g., a Google Meet bot), bug reports from Sentry, or emails—as inputs that can automatically trigger and prioritize work for the coding agent.

  4. Work Must Be Visible Everywhere 9:09

    To improve collaboration, agents should make their work visible across all platforms using standardized artifacts (screenshots or videos), eliminating context switching.

  5. Use Isolated Cloud Environments 12:22

    Running agents in a cloud sandbox is essential for security, enabling non-technical staff to trigger real work without having development environments on their local machines. This enforces the principle of least privilege.

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