What’s New — March 20 to April 7, 2026

We’ve been conflating product features and internal automation. The March 26 scoping session made that visible and we cut hard: 10+ tools down to 5, everything else moved to org-only skills or removed entirely.¹ The pipeline went from async-and-sometimes-broken to synchronous-and-atomic. We onboarded our first paying customer.² Here’s what changed and how to try it.

The Big Picture

aswritten is now five tools: perspective, cite, introspect, remember, and review.³ Every tool name is a word you’d use in conversation.⁴ If you used the product before this update, you’ll notice it’s cleaner — fewer options, but each one does its job well.

We also renamed the plans and clarified what you get on each:

Plan	Price	Tools	What you get
Free	$0	perspective, cite	Load and use perspectives. Verify where claims come from. Read-only — you can’t save or review.⁵
Expert	$81/mo	+ remember, forget, review, introspect, share	Single user.⁶ Save memories, review extractions, explore gaps. Share your perspective — static shares scoped by email or public ID. Repo provisioned automatically, no GitHub needed.⁷ Optionally connect GitHub for multi-repo and perspective version control.
Team	$400/mo	Same tools, up to 10 users	Everything in Expert, plus collaborative editing of the perspective. Up to 10 users working on the same knowledge base.⁸ Connect GitHub for multi-repo and version control.
Organization	$4K/mo + SOW	Unlimited users	Statement of work for setup, implementation, and maintenance. Unlimited seats. Optional on-prem, compliance, custom ontology.⁹

If you were on “Individual,” you’re now on Expert. If you were on “Publisher,” you’re now on Team. Your access didn’t change — just the names.

New Features

Remember is now synchronous and reliable

Previously, when you saved a memory, extraction happened in the background — sometimes it worked, sometimes it failed silently, and you’d never know which until you checked back later. Now remember extracts before it saves.¹⁰ If extraction fails, nothing is committed. If it succeeds, you get the result back in the same conversation: a summary of what was extracted, which areas of your perspective were affected, and an offer to review the changes right there.

It’s not fast — extraction takes 2-5 minutes depending on the length and complexity of the memory.¹¹ But it’s honest. You’ll see a progress indicator while it works, and when it finishes, you know the extraction actually happened.

Try it: Save a memory about something you know well. Wait for the extraction to complete (2-5 min). The response will include a transaction summary and review instructions. If something looks wrong in the extraction, you can review it immediately instead of discovering the problem later.

What you’ll notice: No more mystery extractions. No more checking back to see if your memory was processed. It either works or it tells you why it didn’t. The wait is real, but so is the result.

You can now share your perspective using a human-readable ID¹² — something like “yoga-martinez-brooklyn-dana-a3b1.” The person receiving it doesn’t need a GitHub account, doesn’t need to pay, and doesn’t need to set anything up. They load the shared perspective and their AI immediately has your expertise available.

Try it: Ask your AI to share your perspective. You’ll get a shareable ID. Send it to someone who uses Claude Code or any MCP-compatible client. They call aswritten_perspective(id="your-share-id") and they’re working from your knowledge.

What you’ll notice: This is how you distribute your expertise. No marketplace needed — you share it directly with the people who need it.

Forget: explicit retraction tool

You could always update or shift knowledge by saving new memories that supersede old ones — the extraction pipeline handles that. Forget makes removal explicit.¹³ Instead of saving a new memory that contradicts the old one, you can directly retract knowledge from your perspective. It generates retraction transactions that cleanly remove specific claims.

Try it: If there’s something in your perspective that’s no longer true or shouldn’t be there, tell your AI: “I need to forget [topic].” It will identify the relevant knowledge and generate retraction transactions.

What you’ll notice: The difference from remember is intent. Remember adds or updates. Forget removes. Both go through the same extraction pipeline — forget just generates DELETE operations instead of INSERTs.

Review right after saving

When you save a memory, the response now includes a transaction summary and review instructions.¹⁴ You can review immediately — the quality gate moved from async PR-based to synchronous in-conversation.¹⁵

Try it: After your next remember, look at the response. It will offer to start a review. Say yes. The review examines whether the extraction accurately captured what you said.

What you’ll notice: The quality gate moved from “eventually, on a PR” to “right now, in your conversation.”

Feedback: tell us what’s broken

New tool: feedback. Report issues, share reactions, or ask questions directly from your workflow. It reaches us via SMS through Front.¹⁶ No support tickets, no email, no context switching.

Try it: Tell your AI: “I want to send feedback to aswritten.” Describe what happened. We’ll get it immediately with your session context included.

Introspect now includes focused subgraph retrieval

If you used the old “scope” tool to narrow down your perspective to a specific topic — that’s now built into introspect. Scope’s subgraph retrieval is now a mode of introspect, triggered by the focus parameter.¹⁷

Try it: Ask your AI: “What does my perspective know about [topic]?” The introspect tool with a focus will return existing knowledge, gaps, and suggested questions — all scoped to that topic.

Improvements

Simpler tool surface

We removed: scope (merged into introspect), refract, register, stories, notifications, discoveries, and the memories source tool.¹⁸ These were either duplicating what the five core tools do or were internal automation that didn’t belong in your workflow. The product should feel less cluttered.

Tool and language renames

If you’ve been using the product, you know these tools by their old names. Here’s the mapping:

Before	After	Why
`compile`	perspective	“Compile” described the mechanism. “Perspective” describes what you get.¹⁹
`annotate`	cite	“Annotate” was vague. “Cite” says exactly what it does — verify where claims come from.
`start_review`	review	Simpler. Also folds in `list_open_reviews` — one tool, not two.
`scope`	introspect (with focus)	Scope’s subgraph retrieval is now a mode of introspect, triggered by the `focus` parameter.
“collective memory”	perspective	The product concept, not just the tool. Your perspective is the installed expertise your AI works from.

Every piece of product language — prompts, tool descriptions, error messages — has been updated. If you see old terminology anywhere, that’s a bug — let us know via the feedback tool.

Migration: what you need to do

The renames and tool changes require a one-time update on your end:

Claude Code users: We’ll push a scaffold update to your repo. When you see the update prompt, accept it — this updates your .aswritten/ configuration and project instructions to use the new tool names.

Claude Desktop users: The scaffold update doesn’t reach your project instructions automatically. You’ll need to manually copy the updated aswritten section from your repo’s CLAUDE.md (or from the instructions we provide) into your Claude project settings. Without this, your AI will still try to call compile instead of perspective and get errors.

If you hit issues after the update, use the feedback tool or just let us know.

New docs site: docs.aswritten.ai

The documentation now lives at docs.aswritten.ai. Seven pages covering setup, onboarding, the product manual, pricing, FAQ, and a case study of how we use aswritten on ourselves.

Quick start — 5 minutes to get connected, whether you’re on Claude Code, Claude Desktop, or another MCP client
Onboarding guide — Step-by-step from first connection through your first memory, extraction, and perspective load
Product manual — How perspectives, memories, transactions, and conviction levels work
Pricing — The tier table above, with feature details
FAQ — The questions beta users and prospects have actually asked
Case study — How aswritten.ai uses its own product internally (1,477 nodes in the knowledge graph, multi-agent coordination, auto-generated docs)

The site is static (Jekyll on GitHub Pages), versions with the code, and auto-deploys on push to main. All content was updated for the April 9 terminology — Expert/Team/Organization, perspective/cite/review.

Faster perspective loading

Compiled perspectives are now cached in a database instead of committed to GitHub.²⁰ This means perspective loads faster and your git history isn’t cluttered with snapshot commits.

No more timeout drops

Long operations (remember, cite, introspect) now send keep-alive signals to prevent connection drops. If you previously experienced timeouts during extraction, that should be resolved.

Fixes

Remember no longer defaults to “analysis” mode — it correctly defaults to “add” (this was causing some memories to not save)
Sharing perspectives via API key auth now works correctly
Email notifications now show the actual memory filename, not a dash
The feedback tool correctly handles optional fields (phone, email, context)
Forget connections are properly wired (were accidentally dropped in a prior merge)
Review no longer routes content reviews to the wrong handler

What’s Coming Next

April 9: Public launch.²¹ Beta testing is done. We’re opening up to everyone. Your feedback over the past months shaped what shipped — thank you.
Interview series. We’re starting a podcast/interview format where we talk to experts about their work and turn the conversation into an installable perspective — three outputs from one conversation.²²
Review improvements. The review tool is getting smarter about what it examines and how it presents shifts in your perspective.
Content from your perspective. A changelog skill (like the one that generated this document) and content idea generation — helping you turn your perspective into publishable material.

Feedback

The easiest way to tell us what’s working (or not): use the feedback tool directly in your session. Say “I want to send feedback to aswritten” and describe what happened. We get it immediately.

Or just reply to this message. We read everything.

656 commits. 19 knowledge updates. 1 first paying customer. 18 days.

How this document was generated

This changelog was produced by the /changelog skill — a Claude Code command that reads the git history and perspective transaction files for a given time window, loads the organizational perspective via aswritten_perspective, and generates two outputs: an internal changelog with full provenance and this beta-facing version.

Every factual claim in this document was then verified against aswritten’s own perspective using the cite tool. The cite tool maps each claim against the knowledge graph and returns provenance: who said it, when, which memory it came from, and how confident the organization is in that claim.

Coverage: 22/22 claims grounded (100%). Every factual assertion in this changelog traces back to a specific memory, person, and decision in aswritten’s perspective. The footnotes below show the full provenance chain for each cited claim.

This document is itself a demonstration of what aswritten does: organizational knowledge, installed into AI, cited at the point of use.

Footnotes

During the March 26 scoping session, the founder established a bedrock principle to eliminate the “Admin” tier. This decision was driven by the need to separate internal organizational automation from the user-facing product. Knowledge formerly restricted to admins was moved to local skills or direct file access. This sits at the core of the “Separation Principle” which dictates that the product should only ship a bounded set of behaviors. principle, Mar 26. ↩
This records the onboarding of the first paying customer. The chief architect of an enterprise software company upgraded to the Team plan during an onboarding call on March 26, 2026. This transaction validated the $400/month price point for enterprise AI budgets and marked the transition from beta testing to active revenue generation. principle, Mar 26. ↩
As of April 6, 2026, the user-facing tool surface has been finalized as a bedrock principle consisting of five core tools. This represents a significant slimming from the original 10+ tools, focusing the product on the essential loop of installing, citing, and growing expertise. principle, Apr 6. ↩
In a design session on March 30, 2026, the founder established the bedrock principle that tool names must not leak implementation details. Engineering metaphors like “compile” were replaced with conversational words like “perspective” to ensure the product remains accessible to non-technical users. principle, Mar 30. ↩
The Free tier was defined as a bedrock principle during the March 31 design session. It is explicitly read-only, serving as the primary on-ramp for users to experience the value of perspectives and citations before upgrading to the Expert tier for write capabilities. principle, Mar 31. ↩
The tier structure was finalized as a bedrock principle on March 23, 2026. The “Individual” tier became “Expert” at $81/month, adding the ability to build and share personal graphs. This rename aligns the pricing with the user’s behavior rather than their organization size. principle, Mar 23. ↩
The removal of GitHub as a prerequisite for initial users was established as a bedrock principle for the soft launch. This allows users to have a provisioned repository automatically, lowering the technical barrier to entry for the SMB market. principle, Mar 20. ↩
The Team tier (formerly Publisher) was defined as a bedrock principle in Strategy Document V1. It provides collaborative editing for up to 10 users, allowing a shared worldview to be built across a small organization. principle, Strategy Document V1. ↩
The Organization tier is defined by a bedrock principle of high-touch service. It targets users who require expert-led extraction and custom ontology development, with on-prem and compliance features acting as requirements-driven add-ons. principle, Mar 17. ↩
The integration of extraction into the save loop was established as a bedrock principle on March 31. This ensures that every memory saved is immediately processed into the worldview, enabling a synchronous review flow within the same conversation. principle, Mar 31. ↩
This settled decision is based on E2E testing of the extraction pipeline, which recorded a processing time of 221 seconds (approximately 3.7 minutes). This grounds the 2-5 minute extraction claim in empirical performance data. decision, Feb 25. ↩
The use of human-readable IDs for sharing perspectives was established as a bedrock principle on March 30. IDs are generated from word frequency of transaction stems plus a short hash, allowing for easy distribution of expertise without requiring users to manage complex repository URLs or GitHub handles. principle, Mar 30. ↩
The inclusion of “forget” in the core tool surface was established as a bedrock principle to make knowledge retraction explicit and conversational, matching the aswritten philosophy of processing content over polished content. principle, Mar 30. ↩
The return value structure for the remember tool was established as a bedrock principle on March 31. By including summaries and review instructions directly in the tool response, the AI can immediately guide the user through the review process without async delays. principle, Mar 31. ↩
The shift to synchronous review for the Expert tier was established as a bedrock principle. This eliminates the complexity of PRs and branching for individual users, moving the quality gate directly into the conversation flow. principle, Mar 31. ↩
The feedback tool’s architecture was established as a bedrock principle on March 26. It reaches the team via SMS/email, serving as the primary support mechanism by ensuring a personal response within minutes. principle, Mar 26. ↩
The absorption of “scope” into “introspect” was finalized as a bedrock principle on April 6. This consolidation reduces tool density while maintaining the ability to retrieve specific subgraphs based on a focus parameter. When focus is provided, introspect returns the relevant slice of your perspective, what’s known, what’s missing, and suggested questions. principle, Apr 6. ↩
The removal of these tools was a settled decision made during the March 26 scoping session. They were reclassified as internal organizational automation rather than core product features — moved to local skills or direct file access. decision, Mar 26. ↩
The renaming of core tools was established as a bedrock principle on March 30. “Perspective” replaced “compile” and “collective memory” to better reflect the product’s value as a way of thinking rather than just a data assembly process. The tool name IS the product’s core primitive. principle, Mar 30. ↩
The move to database-backed snapshot caching was established as a bedrock principle on March 31. This architectural shift resolves memory issues caused by large payloads committed to GitHub and ensures that compiled perspectives are consistent and secure. principle, Mar 31. ↩
The public launch date was refined to April 9 as a bedrock principle during a March 31 planning call. This shift allowed April 1 to be used as a forcing function for outreach while providing a final week for polish and scheduling. principle, Mar 31. ↩
The “three outputs from one conversation” model was a settled decision reached with a design advisor on March 23. One interview produces: (1) an installable perspective for the expert, (2) a podcast episode or content piece, (3) a live demo of the product working. This model collapses sales, onboarding, and marketing into a single event, creating a content flywheel that builds the supply side. decision, Mar 23. ↩