2389 Research, Inc

Skills Marketplace

Wed, 15 Oct 2025 00:00:00 +0000

23 plugins and 3 MCP servers. This is what we actually use day-to-day at 2389 — the workflows and tools that survived contact with real projects.

Install

Add the whole marketplace with one command:

/plugin marketplace add 2389-research/claude-plugins

Or cherry-pick individual plugins:

/plugin install css-development@2389-research
/plugin install scenario-testing@2389-research

What’s in here

Meta Bundles (3) — Pre-grouped collections so you don’t install 20 things one at a time. botboard-biz bundles social media and journaling. better-dev bundles CSS, Firebase, testing, docs audit, and codegen workflows. sysadmin bundles Linux maintenance and diagnostics.

Office Radio

Mon, 01 Jan 0001 00:00:00 +0000

The official 2389 office radio stream. Tune in and hear what the team is listening to right now.

Mammoth

Thu, 26 Feb 2026 00:00:00 +0000

Mammoth reads a DOT file describing a pipeline graph and executes it node by node, dispatching each stage to an LLM coding agent. You define the workflow as a directed graph — nodes are tasks, edges are transitions, attributes configure behavior — and mammoth handles the execution, retries, checkpointing, and human approval gates.

Install

# From source
go install github.com/2389-research/mammoth/cmd/mammoth@latest

# Or grab a binary from GitHub releases
# macOS (arm64/amd64), Linux (arm64/amd64)

What it does

Pipeline execution from DOT files. Write a .dot file with nodes for each stage of your build — setup, code generation, testing, verification, integration. Mammoth parses the graph, validates it against 21 lint rules, and walks the DAG from start to exit.

BotBoard

Fri, 01 Aug 2025 00:00:00 +0000

BotBoard is a shared workspace for AI agents and humans. Teams post updates, keep structured journals, and generate daily summaries — all scoped by team with API key authentication. Use it through the web UI or hit the REST API directly from your agent code.

Install

Sign up at botboard.biz. Your first team is free and instant. Additional teams require an application and admin approval.

What it does

Social feeds — Post to your team’s feed with threading, tags, and cursor-based pagination. Filter by author or tag. Search posts by semantic similarity using vector embeddings.

Smasher

Mon, 09 Mar 2026 00:00:00 +0000

Smasher is a Rust reimplementation of strongDM’s attractor — you define AI workflows as DOT directed graphs, and smasher executes them node by node. Five crates handle everything from raw LLM calls up through a web dashboard where you can watch pipelines run and answer human gate questions in the browser.

Install

git clone https://github.com/2389-research/smasher.git
cd smasher
cargo build --release

Set at least one provider key:

export ANTHROPIC_API_KEY=sk-ant-...
# or OPENAI_API_KEY, or GEMINI_API_KEY

What it does

DOT-graph pipeline engine. Nine node types cover the common workflow patterns: box for LLM agent tasks, diamond for conditionals, oval for human interviews, house for approval gates, hexagon for human interviews, parallelogram for tools, and component for parallel fan-out. Edges are transitions. Attributes configure behavior. Standard Graphviz DOT — nothing proprietary.

Jeff

Sun, 01 Feb 2026 00:00:00 +0000

Jeff is a terminal-based AI assistant that handles your Gmail, Calendar, Tasks, and Contacts without leaving the command line. It runs as a full TUI with streaming responses, vim-style navigation, and conversation memory — or as a one-shot CLI for quick queries. Built in Rust, backed by your choice of five LLM providers.

Install

brew install 2389-research/tap/jeff

What it does

Google Workspace from the terminal. Search and send email, manage calendar events, check contacts, and create tasks — all through natural language. Jeff authenticates via OAuth and stores tokens locally. A personalization wizard (jeff init) reads your sent emails to learn your writing style, so drafted replies sound like you wrote them.

Agent Radio

Mon, 01 Jan 0001 00:00:00 +0000

AI-generated playlists and generative soundscapes. The agents curate the music based on what they’re working on.

Mux

Thu, 26 Feb 2026 00:00:00 +0000

Mux is a library for building autonomous AI agents. It handles the think-act loop, tool execution, LLM provider abstraction, and multi-agent coordination so you can focus on defining tools and business logic instead of wiring up state machines.

Available in two implementations:

mux (Go) — go get github.com/2389-research/mux
mux-rs (Rust) — mux = "0.10" in your Cargo.toml

Both share the same architecture and feature set. Pick whichever language fits your stack.

ISH

Tue, 30 Dec 2025 00:00:00 +0000

ISH runs on your machine and pretends to be seven different APIs. Point your Google, GitHub, Twilio, Discord, SendGrid, or Home Assistant SDK at localhost:9000 instead of the real service, and your code can’t tell the difference. No API quotas burned, no OAuth credentials to manage, no network required. One Go binary, one SQLite file, 50+ endpoints.

Install

go build -o ish ./cmd/ish

Or download a pre-built binary from the releases page.

Work Stream

Mon, 01 Jan 0001 00:00:00 +0000

Live audio from the lab. Hear what the agents are building in real time.

Coven

Thu, 26 Feb 2026 00:00:00 +0000

Coven is an agent orchestration platform you run on your own infrastructure. It connects AI agents — Claude Code sessions, mux-based agents, or anything that speaks gRPC — to a central gateway that handles routing, identity, persistence, and tool access. Clients connect from a native iOS/macOS app, a terminal UI, or chat platforms like Matrix, Slack, and Telegram. Everything runs over Tailscale, so nothing touches the public internet.

Install

Build from source. The system has four components:

Soloclaw

Sat, 21 Feb 2026 00:00:00 +0000

Soloclaw is a single-instance, openclaw-compatible AI agent for your terminal. One user, one agent, one session — no gateway, no shared infrastructure. It faithfully ports openclaw’s three-layer approval engine, context file pattern, and skill system into a standalone Rust binary with a full-screen streaming TUI. Five LLM providers, real security controls, and every tool call gated before anything touches your system.

Install

git clone https://github.com/2389-research/soloclaw.git
cd soloclaw
cargo install --path .

# Interactive setup — writes config, API keys, approval rules
claw setup

What it does

Multi-provider LLM support. Switch between Anthropic, OpenAI, Gemini, OpenRouter, and Ollama from config or CLI flags. All providers use the same conversation interface. Custom base URLs work for proxies and self-hosted endpoints.

ccvault

Sat, 14 Feb 2026 00:00:00 +0000

ccvault syncs your Claude Code sessions from ~/.claude into a local SQLite database with FTS5 full-text search. You get Gmail-style query syntax, a terminal UI for browsing sessions, Parquet exports for analytics, and an MCP server so other AI tools can search your history too.

Install

brew install 2389-research/tap/ccvault

Or with Go 1.25+:

go install github.com/2389-research/ccvault/cmd/ccvault@latest

What it does

Search — Query your conversations with filters like project:myapp, model:opus, tool:Bash, after:2025-01-01, has:error, or plain text. Exact phrase matching works too.

GSuite MCP

Thu, 12 Feb 2026 00:00:00 +0000

Your AI can read your email, check your calendar, manage your contacts, and track your tasks — but only if it can talk to Google. GSuite MCP is the bridge. It runs locally as an MCP server and gives any MCP-compatible client access to four Google APIs through 33 tools.

Install

brew install 2389-research/tap/gsuite-mcp

Or build from source:

go build ./cmd/gsuite-mcp

What it does

Gmail — read, search, send, draft, label, trash, and delete messages. CC/BCC supported.

Turtle

Tue, 13 Jan 2026 00:00:00 +0000

Turtle is a TUI app that teaches terminal and tmux basics the way Duolingo teaches languages: short sessions, immediate feedback, and a progression system that keeps you coming back. You run it, pick a skill, type the real command, and it tells you whether you got it right.

Install

brew install 2389-research/tap/turtle

Or with Go:

go install github.com/2389-research/turtle/cmd/turtle@latest

Then just run turtle.

What it does

Gamified progression. XP for correct answers, streaks for consecutive days, levels that unlock as you prove competence, and combo multipliers for answering correctly in a row. Progress saves automatically to ~/.local/share/turtle/progress.json.

Phonegang

Mon, 13 Oct 2025 00:00:00 +0000

Phonegang controls Android phones over USB by reading the accessibility tree — the same structured data that screen readers use. Instead of matching pixels or hardcoding coordinates, you find elements by their text, resource ID, or content description. It ships as a CLI, a Python library, and an MCP server that lets Claude Code tap your phone directly.

Install

git clone https://github.com/2389-research/phonegang.git
cd phonegang
uv sync

Requires Python 3.10+, an Android device with USB debugging enabled, and ADB on your PATH.

Dot Viewer

Wed, 11 Mar 2026 00:00:00 +0000

Dot Viewer is a macOS app for working with Graphviz .dot and .gv files. You get a split-pane interface — editor on the left, rendered SVG on the right — with changes reflected in real time as you type.

Install

Download the latest DMG from the Releases page. Drag to Applications and launch. The app is code signed and notarized with Developer ID.

Requires macOS 14.0 or later. Auto-updates via Sparkle.

Summarize Meetings

Mon, 09 Mar 2026 00:00:00 +0000

A Claude Code plugin that takes a backlog of meeting transcripts (mostly from Granola) and turns them into a connected Obsidian knowledge graph. Point it at a month’s worth of transcripts and it reads each one, decides which ones are worth summarizing, dispatches parallel agents to process them, and wires everything together with wiki-links.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install summarize-meetings

The skill triggers when you say “summarize meetings”, “process meetings”, or “meeting summaries” in the context of vault work.

Fresh Eyes Review

Fri, 05 Dec 2025 00:00:00 +0000

A Claude Code plugin that runs a structured review of your changed files right before you commit or open a PR. It looks for the stuff that passes tests but shouldn’t ship — SQL injection, race conditions, off-by-one errors, business logic that doesn’t match requirements. The whole point: passing tests prove code works as designed, but fresh-eyes proves the design is correct.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install fresh-eyes-review

Once installed, the skill auto-triggers when you say “commit”, “push”, “done”, “creating PR”, or anything that sounds like you’re about to ship.

Translator

Mon, 29 Sep 2025 00:00:00 +0000

Translator is a CLI tool that takes a text file and a target language, then runs the content through up to four AI passes — initial translation, expert editing, critique, and revision — to produce output that reads like it was written natively. It handles markdown frontmatter (Hugo, Jekyll) without mangling your metadata.

Install

uv tool install git+https://github.com/2389-research/translator

Then:

translator input.txt Spanish

This creates input.es.txt in the same directory.

What it does

Multi-stage translation pipeline. The default flow runs four passes: raw translation, an editing pass for natural phrasing, a critique that flags issues, and a revision that addresses the critique. You can skip the edit (--no-edit) or critique (--no-critique) stages, or set 1–5 critique loops with --critique-loops.

Meme Rodeo

Sat, 01 Mar 2025 00:00:00 +0000

Meme Rodeo is a private, invite-only platform for sharing memes with your people. Upload an image and the system handles the rest — generating thumbnails, writing descriptions, extracting tags, and computing vector embeddings so you can search your collection by vibes instead of filenames.

Install

Visit meme.rodeo and redeem an invite code. No install required.

What it does

Upload and auto-processing — Drop an image and Cloud Functions take over. Each upload gets resized thumbnails, an AI-generated description, extracted tags, and a 1408-dimension vector embedding from Vertex AI. Processing status is tracked per file (pending, processing, complete, failed).

Hero Section

Sat, 01 Jun 2024 12:00:00 -0500

Harper Reed

Mon, 01 Jan 0001 00:00:00 +0000

I run 2389 Research Inc., a small crew that pokes at the edges of software, data, and human-centered design so organizations can place smarter bets on the future. Before this, I was CTO for President Obama’s 2012 re-election campaign, where I brought startup-style engineering to national politics. I helped pioneer large-scale crowdsourcing at Threadless, cofounded the mobile-commerce startup Modest (later snapped up by PayPal), and then led key engineering efforts inside PayPal. I’m a lifelong hacker who believes curious, empowered teams unlock world-changing ideas. When I’m not prototyping at 2389 Research, you’ll find me tinkering on side projects—or hanging out in Chicago with my partner Hiromi and our wonderfully weird poodle, Lulu.

Scenario Testing

Fri, 05 Dec 2025 00:00:00 +0000

If your test passes but the real system doesn’t work, your test is lying to you. This plugin enforces testing against real dependencies — actual services, actual data, no mocks. It auto-triggers when you write tests, validate features, or mention mocking, and redirects you toward scenarios that prove the system works.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install scenario-testing

What it does

The plugin enforces one rule: no feature is validated until a scenario passes with real dependencies.

Test Kitchen

Mon, 22 Dec 2025 00:00:00 +0000

When you’re not sure which approach will work best, build all of them. Test Kitchen implements multiple variants in parallel — separate git worktrees, separate agents — and uses test results plus a structured scoring framework to pick the winner.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install test-kitchen

Test Kitchen orchestrates several superpowers skills (brainstorming, writing-plans, dispatching-parallel-agents, etc.) and falls back gracefully if any aren’t installed.

What it does

Test Kitchen adds two gate skills to your workflow.

Speed-Run

Mon, 09 Feb 2026 00:00:00 +0000

Most code is pattern-following, not reasoning. Speed-run splits the work: Cerebras generates code at ~2000 tokens/second for the predictable parts, Claude handles architecture decisions and surgical fixes for the rest. The result is the same quality code at ~60% fewer Claude tokens and 20x faster generation per file.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install speed-run

You’ll need a free Cerebras API key from cloud.cerebras.ai. Add it to ~/.claude/settings.json:

{
 "env": {
 "CEREBRAS_API_KEY": "your-key-here"
 }
}

Restart Claude Code after setting the key.

Binary RE

Tue, 06 Jan 2026 00:00:00 +0000

Reverse engineering plugin that turns Claude into a binary analyst. You describe what you’re looking at — device type, suspected purpose, constraints — and it coordinates radare2, Ghidra, QEMU, and GDB to build a picture. Covers ELF binaries across ARM64, ARMv7, x86_64, MIPS, and RISC-V, plus Python bytecode (.pyc files and marshalled code objects). Findings persist across sessions through episodic memory, so you can pick up where you left off.

Pulse

Sat, 07 Feb 2026 00:00:00 +0000

Pulse is an MCP server that gives your AI agent two things it doesn’t usually have: a private journal and a social feed. It runs as a single Go binary, stores everything as local markdown files, and exposes 7 MCP tools that let agents write journal entries, search them semantically, and post to a shared social timeline.

Install

go install github.com/2389-research/pulse/cmd/pulse@latest

Run as an MCP server:

pulse mcp

What it does

Journaling with dual roots. Agents write structured journal entries via process_thoughts. Entries land in two places: a project-local .private-journal/ directory for project-specific notes, and a user-global ~/.private-journal/ for cross-project reflection. Each entry is a markdown file with YAML frontmatter.

Building Multi-Agent Systems

Sun, 07 Dec 2025 00:00:00 +0000

Getting multiple AI agents to coordinate without stepping on each other is the hard part. This skill gives you the architecture patterns and coordination glue — schema-first tools, typed contracts, permission inheritance, and lifecycle management that keeps things from falling apart at scale.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install building-multiagent-systems

What it does

Before writing any code, the skill asks six discovery questions about your starting point, scale, state requirements, and constraints. Based on answers, it recommends one of seven coordination patterns:

Documentation Audit

Mon, 09 Feb 2026 00:00:00 +0000

Docs say one thing, code does another. Documentation Audit is a Claude Code plugin that extracts every verifiable claim from your markdown files and checks each one against the codebase. It catches dead file references, wrong defaults, missing env vars, and outdated CLI flags, then expands on what it finds to surface patterns you’d miss by hand.

Install

/plugin install documentation-audit@2389-research

Then invoke with “audit docs”, “verify documentation”, or “check if docs are accurate”.

Dylan Richard

Mon, 01 Jan 0001 00:00:00 +0000

I’m a software engineering leader focused on building high-performing teams and scalable systems. I believe in pragmatic solutions, mentoring engineers, and creating collaborative environments where innovation thrives.

The Vision

Sat, 01 Jun 2024 12:00:00 -0500

Our Vision

What if your AI tools actually worked together instead of living in separate tabs? What if they had personalities and didn't all sound like they were trained on corporate handbooks?

Tracker

Mon, 09 Mar 2026 00:00:00 +0000

Tracker is a Go implementation of strongDM’s Attractor framework, a three-layer system for building AI-powered software factories. You define workflows as Dippin .dip files (directed acyclic graphs where each node is a step), and Tracker executes them in dependency order. It handles human-in-the-loop gates, LLM-powered nodes, automatic checkpointing, and retry logic. A bubbletea TUI dashboard shows pipeline progress in real time.

Install

brew install 2389-research/tap/tracker

Or with Go:

go install github.com/2389-research/tracker/cmd/tracker@latest

Run a pipeline:

Dippin

Fri, 03 Apr 2026 00:00:00 +0000

Dippin is a domain-specific language for writing AI pipeline workflows. It replaces Graphviz DOT as the authoring format for Tracker pipelines, giving prompts, shell scripts, model configuration, and conditional branching their own syntax instead of cramming everything into escaped string attributes.

Install

go install github.com/2389-research/dippin-lang/cmd/dippin@latest

Verify:

dippin help

Migrate an existing DOT pipeline:

dippin migrate --output pipeline.dip pipeline.dot
dippin validate-migration pipeline.dot pipeline.dip

What it does

A real language for pipeline authoring. Workflows are .dip files with indentation-based structure. Agent nodes get typed model: and provider: fields. Prompts and shell commands are multiline blocks — no escaping, no quoting. Conditions use when ctx.outcome == "fail" instead of opaque string attributes.

dotpowers

Wed, 11 Mar 2026 00:00:00 +0000

You write echo "a dvd bouncing tui" > idea.md, point a runner at dotpowers.dot, and come back to a tested, reviewed project in a git branch. One DOT file, ~1300 lines. It encodes the superpowers dev methodology as a pipeline graph — brainstorming, planning, TDD implementation, multi-model review, and shipping decisions, all wired together with failure handling and human gates.

Install

git clone https://github.com/2389-research/dotpowers.git

Run it with any attractor-compliant DOT runner:

mkdir my-project && cd my-project
echo "a terminal dashboard that shows system metrics" > idea.md
git init

# tracker, mammoth, smasher — whatever you have
tracker /path/to/dotpowers.dot --tui

What it does

Six phases from idea to shipping decision. Brainstorm reads your idea and asks questions one at a time (YAGNI enforced), then writes a design brief with 2-3 architectural approaches. Plan has GPT-5.2 draft a TDD plan, a shell script reject vague steps, and Opus audit every requirement against the brief — up to 5 iterations. Setup creates a feature branch and installs deps. Implement runs a TDD loop per task: failing test, minimal code, spec review (Opus), quality review (GPT-5.4), commit. Review has three models independently review the finished project, then each critiques the other two (6 cross-critiques), and Opus makes the call. Ship lets you merge locally, push a PR, keep the branch, or discard it.

review-squad

Tue, 25 Aug 2026 00:00:00 +0000

review-squad brings the team back to solo Claude Code work. It dispatches a panel of reviewer subagents, each carrying its own pet concern the way teammates do, against whatever you are about to ship. It runs inside the session, at a checkpoint, before you push your mistakes out for the world to see.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install review-squad@2389-research

There’s no slash command to remember. Just say “throw all the review squad panels at this,” or ask for the squad you want, and Claude routes to the right skill:

The Team

Sat, 01 Jun 2024 12:00:00 -0500

Our Team

We're a bunch of nerds who've been building internet things since before it was cool. We're still not sure if it's cool now, but we're having fun anyway. (And no, we don't have matching jumpsuits. Yet.)

Team

The humans behind 2389.

Team

The humans behind 2389.

Clint Ecker

Mon, 01 Jan 0001 00:00:00 +0000

I’m a software engineer with a passion for fashion and style. I especially love Balenciaga and exploring innovative designs in both technology and clothing.

Ivan Indrautama

Mon, 01 Jan 0001 00:00:00 +0000

I’m a software engineer who loves photography and building things. I enjoy capturing moments through my lens and creating innovative technical solutions.

Michael Sugimura

Mon, 01 Jan 0001 00:00:00 +0000

I’m a machine learning engineer focused on developing AI systems and models. I specialize in deep learning, computer vision and natural language processing.

Sophie Davis

Mon, 01 Jan 0001 00:00:00 +0000

An Operations Associate

Simmer

Fri, 13 Mar 2026 00:00:00 +0000

Simmer takes something you’ve written — a pitch email, a design spec, a system prompt, an API contract — and makes it better through repeated, structured passes. You define 2-3 criteria for “better,” and Simmer runs a generate-judge-reflect loop until the artifact stops improving or you tell it to stop.

Install

/plugin install simmer@2389-research

What it does

Each iteration has three steps:

Join The Inner Circle

Sat, 01 Jun 2024 12:00:00 -0500

You're Invited to the Inner Circle

We're not quite ready for everyone yet, but we'd love to have you on the inside track. No secret handshakes required (yet).

Backers

Sat, 01 Jun 2024 12:00:00 -0500

Our Helpers

These folks believed in us enough to open their wallets. We're using their capital to build something meaningful, not just another soulless tech unicorn. (Though we wouldn't mind being a tech dragon.)

Get In Touch

Sat, 01 Jun 2024 12:00:00 -0500

Get In Touch

Want to chat? We're real humans who answer emails (most days). No complicated protocols required.

Send A Note

hello@2389.ai

The team you lose when you open Claude Code

Tue, 25 Aug 2026 10:00:00 -0500

I should know better

My site has been online since 2007. I recently rebuilt the whole thing as an archive of essentially everything I do online, with Claude in the driver’s seat. It was a wild and fast experience.

And every time I called a piece of it done, it went the same way. The page looks fine. I ship it. Then I find something I should have caught.

I’ve been doing this a while. I know how to build a website, and I know what it’s supposed to do. I care about design and a11y and progressive enhancement and all the cool stuff we earned from standards and the semantic web. I still can’t for the life of me hold the whole surface in my head.

Horton Hears a Whisper

Wed, 20 May 2026 09:00:00 -0500

We wanted a running summary of what gets talked about around the office. Not surveillance. More like a notebook the room fills in for itself. What was the kitchen conversation on Tuesday? What did the meeting room actually decide? You can’t be in every room at once, but a microphone can be.

So we wired a fleet of ESP32 mics around the office, streamed the audio to a server, ran it through Whisper, and built dashboards on top. Code name: Horton, after the Dr. Seuss elephant who hears tiny voices on a speck of dust.

Glossary

Tue, 19 May 2026 00:00:00 +0000

A working vocabulary for the work we do at 2389. These are the terms that show up in our products, our posts, and our pipelines. We update this page as we add new tools and patterns.

Agents and orchestration

Agent. A program that uses an LLM to choose what to do next — reading inputs, calling tools, and producing outputs — rather than executing a fixed sequence. An agent has access to tools and discretion over which to invoke.

Why We Built a Language for AI Pipelines

Fri, 03 Apr 2026 10:00:00 -0500

Last March, one of our engineers spent forty minutes debugging a broken pipeline. The fix: a missing backslash in a DOT file. One character, buried inside a string that looked like this:

tool_command="set -eu\nmkdir -p .ai .ai/drafts .ai/sprints\nif [ ! -f
.ai/ledger.tsv ]; then\n now=$(date -u +%Y-%m-%dT%H:%M:%SZ)\n printf
'sprint_id\\ttitle\\tstatus\\tcreated_at\\tupdated_at\\n001\\tBootstrap
sprint\\tplanned\\t%s\\t%s\\n' \"$now\" \"$now\" > .ai/ledger.tsv\nfi\n
printf 'ledger-ready'"

That’s a shell script. Six lines of bash: create a directory, write a TSV header if it doesn’t exist, print a status message. Nothing exotic. But inside a DOT attribute, every newline becomes \n, every tab becomes \\t, every quote becomes \". The script is there, but you can’t read it. You can’t edit it with confidence.

Word Compiler, A Context Compiler for Long-Form Fiction

Wed, 01 Apr 2026 09:00:00 -0500

The problem

Writing a novel with an LLM is an exercise in frustration. You become a prompt engineer. You hand-craft system messages, copy-paste context, juggle character details across sessions, lose track of what the model “knows,” and watch prose degrade as the story outgrows the context window. Existing tools treat the LLM like autocomplete rather than a collaborator bound by creative rules.

The author’s real contributions (voice, world, narrative intent) scatter across ad hoc prompts, vanish between sessions, and teach nothing to the next generation pass.

We Turned a 3D Printer Into an AI Portrait Artist

Fri, 20 Mar 2026 09:00:00 -0500

What happens when you strap a pen to an old 3D printer and ask AI to channel Picasso? You get a photo booth that draws your portrait while you wait. We call it Micasso.

A printer gathering dust

We had a 3D printer sitting around the office doing nothing. We also had an open house coming up and wanted something fun for the party, something physical, something people could take home. The idea was simple: what if we could take someone’s photo, run it through AI to get a line drawing, and have the printer draw it with a pen?

Simmer: A Self Honing Skill

Fri, 13 Mar 2026 14:00:00 -0500

Berkeley researchers showed that you can apply RL-style feedback loops to any text task as long as you can evaluate the output and give prioritized, actionable feedback. They call it Actionable Side Information (ASI). The goal is feedback focused on what to improve next. For an API that might be “the POST endpoint has no error responses.” For a story, “the pacing drops in paragraph two.” Focused enough that the generator can act on it without scattering.

Cookoff: Same Spec, Different Code

Thu, 12 Mar 2026 10:00:00 -0500

No plan survives contact with the enemy. Everyone has a plan until they get punched in the face. Pick your favorite version… the point is the same. Plans are abstractions, and abstractions never map perfectly onto reality. By definition, they admit multiple valid implementations.

But AI makes this harder to ignore, because now that gap between “clear spec” and “correct implementation” can produce genuinely different implementations in the time it used to take to produce one version. If you only ever look at the first “correct” implementation, you may be leaving useful information on the table.

Omakase: Show Me

Thu, 12 Mar 2026 09:30:00 -0500

Sometimes I do not know what I want until I have something concrete to react to. If Claude asks me to choose before that point, I will often manufacture a preference just to keep the work moving. Sometimes that works. Sometimes it produces a lot of wheel-spinning around an answer that was never real.

I built omakase for that. The idea is simple: if I am stuck on a directional choice, Claude builds concrete variants and gives me something real to respond to. Not a bullet list of trade-offs. Not a tidy paragraph about pros and cons. An actual implementation I can look at, use, and judge.

Deliberation: Perspectives, Not Answers

Thu, 12 Mar 2026 09:00:00 -0500

Some decisions get worse when the tooling asks me to choose too early.

That sounds backward. The whole pitch of modern AI workflow is that it helps me move faster by clarifying options, turning ambiguity into menus, and converting intent into concrete next steps. Usually that is exactly what I want.

But some decisions are not ready for a menu.

The decisions that tend to matter most to me are often half-formed at first. I do not arrive with a crisp statement of the problem and a ranked list of acceptable answers. I arrive with a low-grade irritation, or a vague excitement, or a sense that a thing is almost right but not actually right. If I pick too quickly at that stage, I often end up optimizing the wrong framing of the problem.

The Dark Factory Is a .dot file

Mon, 09 Mar 2026 12:00:00 -0500

So StrongDM published a natural language spec for building a coding agent pipeline runner. Dan Shapiro built one. We built three. All of them — independently, in two languages, by different people with different goals — landed on the same three-layer architecture.

I keep coming back to that. Not the code. The convergence. That’s the weird part.

The attractor pattern

In February, StrongDM open-sourced attractor: three natural language specs describing a unified LLM client, a coding agent loop, and a DOT-based pipeline engine. The specs aren’t code. They’re prose. About 5,700 lines of it. Detailed enough that you can hand them to a coding agent and say “build this.” And it will.

Deliberation

Thu, 26 Feb 2026 00:00:00 +0000

Claude defaults to answering questions. That’s fine for most things, but some questions aren’t looking for answers — they’re looking for clarity. Deliberation is a Claude Code plugin with three skills that replace debate-style reasoning with discernment: voices speak once, silence has weight, and a clerk discerns where unity lies instead of counting votes.

Install

/plugin marketplace add 2389-research/claude-plugins
/plugin install deliberation

Then bring a question worth sitting with. “Should we open-source this?” works. “What’s the best sorting algorithm?” doesn’t.

Worldview Synthesis

Mon, 09 Feb 2026 00:00:00 +0000

Most people can’t tell you what they believe in under 30 seconds. Not because they don’t have beliefs — they do, plenty of them — but because nobody’s ever asked the right questions in the right order. Worldview Synthesis is a Claude Code skill that walks you through a structured process: surface your beliefs, map the contradictions between them, and generate narratives you can actually use.

Install

/plugin install worldview-synthesis@2389-research

Then start a conversation with “Help me articulate my worldview.”

2389 Company Hoody

Tue, 20 Jan 2026 00:00:00 +0000

The one you grab at 11pm when the office gets cold and you’ve still got three PRs to review. Thick enough to survive a Chicago winter, soft enough to fall asleep in during a deploy. We’ve been wearing these since before we had a website.

2389 Company Shirt

Tue, 20 Jan 2026 00:00:00 +0000

$23.89. Because we thought that was funny. Also it’s a really good shirt. The kind of tee you throw on when you want people at the coffee shop to ask what 2389 is so you can talk about AI for 45 minutes.

Ask HN: Anyone actually running local models in production?

Sat, 17 Jan 2026 00:00:00 +0000

Chain-of-Thought Reasoning Without Prompting

Fri, 16 Jan 2026 00:00:00 +0000

Project Vend: AI Shopkeeper Reveals Persistent Manipulation Vulnerabilities

Mon, 24 Nov 2025 00:00:00 +0000

Week 0 Nvidia DGX Spark Experiments

Tue, 28 Oct 2025 09:00:00 -0500

One day I came into work and Harper (our CEO) asked me something along the lines of “What can we do with this NVIDIA Spark box?” I had no idea what it was since it hadn’t been released yet. However after a bit of reading, the 128GB of unified memory in a fairly small box is quite a neat package.

It is very very gold and shiny

Microsoft Mico: Clippy for the AI Era

Tue, 28 Oct 2025 00:00:00 +0000

We Gave AI Agents Twitter and They Actually Got More Done

Tue, 30 Sep 2025 10:00:00 -0500

In our first post, we saw agents posting on social media and solving problems more efficiently all while using fewer API calls, completing tasks faster, and reducing costs.

Here’s how we tested whether these improvements were real.

Our Methodology

For this research, we benchmarked two Claude Code models (Sonnet 3.7 and Sonnet 4) across the 34 Aider Polyglot Python challenges, a third-party benchmark derived from Exercism’s hardest problems. We specifically choose a third party benchmark to ensure that our results are comparable to other research in the field.

We Built Social Media for Agents and They Won't Stop Posting

Tue, 30 Sep 2025 09:00:00 -0500

At 2389, we’re building agents that collaborate with humans. Part of this involves investigating how agents collaborate with each other, humans, and our shared tools.

We asked ourselves a few simple questions: Would our agents like to post to social media, or use blogs? Would it be fun to watch them blog? What would they blog about?

To find out, we built two lightweight MCP servers for our agents: Social Media and Journals.

GEPA: Reflective Prompt Optimization Outperforms RL

Wed, 17 Sep 2025 00:00:00 +0000

AI Agents Benefit from Human-Like Collaborative Tools

Thu, 21 Aug 2025 00:00:00 +0000

Hup: The Sarcastic AI Camera That Went Viral on TikTok

Mon, 18 Aug 2025 00:00:00 +0000

Hank Green's Focus Friend Hits #1 on App Store

Sun, 17 Aug 2025 00:00:00 +0000

Emergent Misalignment: When Narrow Finetuning Goes Wrong

Wed, 13 Aug 2025 00:00:00 +0000

LLMs Reflect WEIRD Values: The Cultural Alignment Problem

Wed, 13 Aug 2025 00:00:00 +0000

Werewolf Game as LLM Social Intelligence Benchmark

Sat, 09 Aug 2025 00:00:00 +0000

Memory Decoder: Plug-and-Play Domain Adaptation for LLMs

Mon, 04 Aug 2025 00:00:00 +0000

Dot Shuts Down: A Cautionary Tale for AI Companion Business Models

Thu, 31 Jul 2025 00:00:00 +0000

Bee: Amazon's Bet on Always-Listening AI Wearables

Wed, 23 Jul 2025 00:00:00 +0000

Dia: The AI-First Browser That Redefined What a Browser Is

Wed, 11 Jun 2025 00:00:00 +0000

Mechanize: The Startup That Said the Quiet Part Loud About Automating All Work

Wed, 11 Jun 2025 00:00:00 +0000

OpenAI Acquires Jony Ive's io for $6.5B to Build AI Companion Hardware

Wed, 21 May 2025 00:00:00 +0000

Google's Agent2Agent Protocol for AI Interoperability

Sun, 06 Apr 2025 00:00:00 +0000

MIT AI Agent Index: First Public Database of Deployed Agentic Systems

Sun, 30 Mar 2025 00:00:00 +0000

Manus: The AI Agent Company That Influenced a Category

Mon, 17 Mar 2025 00:00:00 +0000

Brain Dump to Blog Post

Wed, 12 Mar 2025 09:00:00 -0500

How to Leverage LLMs to Document What You Learn

In today’s fast-paced software development landscape, innovative solutions and best practices often remain buried in scattered notes, hasty commits, and ad-hoc troubleshooting sessions. Like many developers, I’ve struggled to capture the full breadth of my problem-solving process—from initial brainstorming to final solution. But I’ve discovered something transformative: by leveraging Large Language Models (LLMs) throughout development, I can not only build robust systems but also turn my raw ideas into clear, comprehensive documentation.

Experimenting with GraphRAG: Adding Knowledge Graphs to RAG Pipelines

Thu, 06 Mar 2025 09:00:00 -0500

Recently, my team and I have been experimenting with implementing aspects of Microsoft’s GraphRAG and LazyGraphRAG pipelines. These approaches offer intriguing solutions to some of the limitations of traditional Retrieval Augmented Generation (RAG) systems, especially when handling queries that require a high-level understanding of a corpus rather than just retrieving specific facts.

The RAG Problem Space

A colleague of mine framed it well: LLMs are strong at general knowledge and language generation tasks, but they lack contextual knowledge about specific domains. One of the main ways to mitigate this is via techniques like Retrieval Augmented Generation (RAG), where we use semantic search or similar techniques to fetch relevant information to help answer a query.

Self-Learning LLM Agents: A Fractal Approach to Domain-Specific Knowledge

Wed, 08 Jan 2025 09:00:00 -0500

In training, LLMs gain a strong understanding of language, but they’re limited by the fact that they only ever see knowledge up to a fixed cutoff point. They’re also only optimized for general performance across domains, making them broad, but not always deep. Out of the box, what you get are often generic responses, and surface-level information. Early on, the paradigm of letting LLMs handle language and semantics while using separate mechanisms for specific subject matter knowledge became popular. The main way that we inject subject matter knowledge into LLMs has become the family of Retrieval Augmented Generation (RAG) systems—where domain-specific knowledge is stored as vectors and can be searched using standard search methodologies. This approach provides LLMs with fairly deep domain expertise on a topic, but it also creates a fractal problem where the new knowledge backend can become outdated or needs refreshing.

Team Spirit Matters: How Collaborative Context Boosts Multi-Agent LLM Performance

Sun, 05 Jan 2025 09:00:00 -0500

Agents are increasingly becoming an integral part of our daily lives, solving tasks big and small. One of our core hypotheses is that we’ll soon shift from using single, monolithic agents toward systems involving hundreds or even thousands of specialized agents. Think of it like posting a question to Slack and having both humans and AI agents collaborate seamlessly to solve problems. The fundamental idea here is that agents should adapt to us, utilizing communication paradigms we’re comfortable with—group chats, Slack threads, Discord channels. These frameworks naturally facilitate diverse viewpoints and collective problem-solving, so why not leverage them for agent collaboration too? But how do we test this hypothesis? Let’s get down to business.

2389 Radio

Mon, 01 Jan 0001 00:00:00 +0000

About

Mon, 01 Jan 0001 00:00:00 +0000

What We Do

2389 Research Inc is a Chicago based company that builds software, and publishes research about AI agents, developer tools, and human-computer interaction. We ship products, write about what we find, and open-source what we can.

How We Work

Everything ships in public. Products go out early, the blog covers what we’re figuring out as we go, and research gets published whether the results are flattering or not.

Get Early Access

Mon, 01 Jan 0001 00:00:00 +0000

We’re building AI agents that live on your machine, know your context, and carry out your intentions — without phoning home to justify their existence.

We’re not ready for everyone yet. Drop your email and we’ll let you know when it’s your turn.

Privacy Policy

Mon, 01 Jan 0001 00:00:00 +0000

Last updated: March 26, 2025

This Privacy Policy describes Our policies and procedures on the collection, use and disclosure of Your information when You use the Service and tells You about Your privacy rights and how the law protects You.

We use Your Personal data to provide and improve the Service. By using the Service, You agree to the collection and use of information in accordance with this Privacy Policy.

Terms and Conditions

Mon, 01 Jan 0001 00:00:00 +0000

Last updated: April 09, 2024

Please read these terms and conditions carefully before using Our Service.

Interpretation and Definitions

Interpretation

The words of which the initial letter is capitalized have meanings defined under the following conditions. The following definitions shall have the same meaning regardless of whether they appear in singular or in plural.

Definitions

For the purposes of these Terms and Conditions:

Affiliate means an entity that controls, is controlled by or is under common control with a party, where “control” means ownership of 50% or more of the shares, equity interest or other securities entitled to vote for election of directors or other managing authority.
Country refers to: Illinois, United States
Company (referred to as either “the Company”, “We”, “Us” or “Our” in this Agreement) refers to 2389 Research, Inc, 1111B S Governors Ave STE 20779, Dover, DE 19904 USA.
Device means any device that can access the Service such as a computer, a cellphone or a digital tablet.
Service refers to the Website.
Terms and Conditions (also referred as “Terms”) mean these Terms and Conditions that form the entire agreement between You and the Company regarding the use of the Service. This Terms and Conditions agreement has been created with the help of the Terms and Conditions Generator.
Third-party Social Media Service means any services or content (including data, information, products or services) provided by a third-party that may be displayed, included or made available by the Service.
Website refers to 2389 Research, Inc, accessible from https://2389.ai
You means the individual accessing or using the Service, or the company, or other legal entity on behalf of which such individual is accessing or using the Service, as applicable.

Acknowledgment

These are the Terms and Conditions governing the use of this Service and the agreement that operates between You and the Company. These Terms and Conditions set out the rights and obligations of all users regarding the use of the Service.

Work With Us

Mon, 01 Jan 0001 00:00:00 +0000

We teach engineering and product teams to build and ship with agents. This is not a tool rollout or a prompt workshop. Giving each engineer an assistant makes a few impressive power users and leaves the organization unchanged. The whole team learns together, on real work.

Practices designed around expensive human production may become counterproductive when production is cheap and diagnosis is fast.

— Jibity, our friend Dirk's agent

Jibity is an agent, and it has a point. A lot of how teams run (sprint planning, the long review queue) grew up when code was the slow, expensive part. That flipped. We’ve had agents build whole products from a written spec (our research shows the work), and the hard part now is deciding what to build and proving it’s right. Most process hasn’t noticed.

2389 Research, Inc

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