Grammarly is being rebranded as "Superhuman Go" with new integrations with the other products of the Superhuman family. Coda.io is being rebranded as "Superhuman Docs" and features a significant upgrade to its AI capabilities. I have exploited this new AI side panel (which is based on Anthropic LLMs) to implement complex Agentic Workflows, withour needing any Packs, Formulas, Buttons, or Automations. The workflow is defined as a set of SKILLS in English that are stored as Coda Pages. The data is stored in normal Coda Tables. The AI system "executes" the SKILLS pages and uses MCP to read and update the Coda tables as it processes the workflow. This technique will be familiar to users of Claude Code, Claude Cowork, Antigravity, Cursor, Open Claw, etc. It also beats the capabilities of the recently launched Notion Custom Agents. This video demonstrates a use case where we replace experienced Civil Engineers to read the customers requirements for industrial water pumps in mines and quarries. The complex rules that govern the configuration of thes large (4 ton) water pump systems are defined in the SKILLS pages. When the configuration is completed, the AI checks results and, if needed, back-tracks to find the optimal solution automatically. In the next workshop I will be going into much more detail about how we buid these Agentic Workflows with the assistance of the AI and expert inputs from the engineers, their procedure manuals, and reference materials. I was unable to publish this sooner due to the Superhuman Beta Program NDA. But now the product has launched, I can share this here. respect, 🦞Max

A bit on why I keep building here; for anyone wondering whether Superhuman Coda has a place in an AI-first world. Most of the AI conversation right now is dominated by a real and reasonable fear: hallucination and non-determinism. Can you trust a system that might invent a fact, or behave differently each time you run it, to actually run your business? That’s the right question to ask — and I don’t think the answer is to keep AI at arm’s length. It is to orchestrate AI so it reliably achieves a business goal: not a clever demo, but a process a manager can trust day after day. That problem has two halves, and Superhuman Coda happens to be unusually good at both: - Deterministic work belongs in formulas. CFL, buttons, and automations give you reliable, auditable, repeatable execution — the same result every time, with nothing invented — for everything that doesn’t need judgment. - Judgment belongs in inference. Native AI blocks let you place a focused model call exactly where reasoning is genuinely required — and nowhere else, so the unpredictable part stays small and reviewable. And the Superhuman Go AI engine is excellent at taking a specification of the business workflow we want to automate and generating the Tables, Formulas, and AI prompts to implement it! Most of my experiments, a set of docs I called AgentixGo (see here) are really just probes into one question: where is the optimal line between the formula and the inference? Coda lets me move that line freely without ever leaving the document. I don’t know another platform where deterministic logic and AI judgment sit this close together, in a tool a business manager can actually read. Notion has recently launched their “Custom Agents” feature that goes part of the way along this path. But it falls short, and let’s face it; the Notion formula language, and their database model, are way inferior to Coda, and not quite fit for purpose in serious process automations.

I have uploaded the latest video into the CLASSROOM and on YouTube 🦀OPEN CLAW INNER WORKINGS→NOCODE DEMO🤖 We will build a working replica of the innermost loop of OpenClaw to illustrate how it operates. This innermost loop will take a prompt and generate an executable set of TOOL requests to implement that. The TOOLs will modify data in the document by executing Action Formula Language (CFL) commands that can add/delete/edit rows in tables, change control-values, bring up dialogs for the user to see and change, modify information stored in the document's pages, etc. This replicates the way Claude Code, Claude Coworker, OpenClaw, OpenAI Codex, Cursor, work. (What I call the 🦞Lobster-like Agentic Tools). This will build the core functionality that we will use in subsequent workshops to build a complete replica of OpenClaw or Claude Cowork that runs (safely) inside the no-code environment (but can take real-world actions via API integrations). I will be using Coda.io for these demonstrations because it has the most complete set of features needed. But the principles will be equally applicable to Notion, Excel, Airtable, and other no-code platforms.