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Multi-agent orchestration · multi-model · shared memory

Many agents. Many models. One brain.

It starts as your agent's memory: a private, local store that remembers your project's decisions and feeds them back, so you stop re-explaining yourself every session. The same memory then lets a team of agents work together: different model families checking each other's work over shared context instead of a group chat. Claude Code, Codex and Vibe today; Hermes in alpha. Two commands. Free forever, on your machine.

How it works

Three jobs you can hand the fleet.

You stay in the session you already have open. The local daemon spawns the workers, and the agent that checks a piece of work is never the one that produced it: Codex reviews what Claude wrote, a vision model judges what the generator drew. Every worker reads the same shared memory, and every verdict is recorded.

  1. Design mode proven

    Pressure-test a design before you build it.

    Point it at a spec or an RFC. A Codex critic files objections; you rule on each one; the author revises; the next round checks the fixes held. Capped at eight rounds, then it converges or escalates to you. We used it on Develop mode's own spec: eight rounds, fourteen objections, then sign-off.

    How Design mode works →
  2. Develop mode live

    Parallel implementation with a second opinion built in.

    You define the work units. Claude implementers run them in parallel, each in its own git worktree. Codex reviews every patch and a judge scores it against a five-point rubric; anything that fails goes round again, up to a cap, then comes back to you. Verified work merges to an integration branch. It never touches main; that merge is yours.

    How Develop mode works →
  3. Image mode new

    Generate images with a critic in the loop.

    You write the spec, a Codex generator renders it, and a separate vision model marks the result against the spec. In our first smoke test the judge rejected a gradient-shaded circle because the spec said flat vector, and the pipeline redrew it. That strictness is the point: a bad image is caught before you see it.

    How Image mode works →

Most multi-agent tools put agents in a chat room. They lose track of who did what, and no agent can trust work it did not watch happen. Hydrate's workers never talk to each other at all: they read and write one shared memory under a single coordinator, which is how a Claude implementer and a Codex reviewer hold the same context on the same task.

Multi-agent orchestration · stable

A process you can trust. Not a group chat.

The daemon owns all state, spawns the workers, enforces the rules and drives the fleet to convergence. Parallelism is bounded by a spawn cap, and workers are hydrated with their project's memory but walled off from every other target's context.

  • Typed artifacts, not chat — workers never message each other. They communicate through plans, patches, reviews and verdicts, and through git.
  • Cross-family review — Claude implements; Codex reviews and judges, with Fable standing in when Codex is unavailable. Each catches the other's blind spots.
  • Human gates throughout — you rule on objections, you open the integration gate, and the merge to main is always yours.
How orchestration works
A Design session converging
design_start    draft: docs/specs/develop-mode.md
design_round    Codex critic files 5 structured objections
design_resolve  you rule: 4 accepted, 1 contested
design_round    revisions hold; 0 material objections remain
design_signoff  finalised design + full decision log

Develop mode's own spec was converged this way: 8 rounds, 14 objections, human sign-off.

Your memory, on your machine · the foundation

The same prompt, twice. Once cold, once hydrated.

Left: a fresh Claude Code session, no project context. Generic answer. Right: same prompt after Hydrate injects four facts it learned in your previous session (API_BASE, the auth pattern, the data-fetching library, the "do not touch redux" rule). It all lives in a local store on your own machine: no account, no API key, nothing sent to a cloud we run. You can read, edit and delete any of it, and it is free forever for solo work.

Memory transfer between two coding sessions: a new session with no context on the left, the same prompt answered correctly on the right because four extracted facts (API_BASE, auth-pattern, tanstack-query, do-not-touch-redux) were injected from project memory across the session boundary.
Cold vs. hydrated session: facts injected at SessionStart via the Claude Code hook.

on by default Recall now ranks by trust × freshness × relevance, not raw similarity, so well-sourced, repeatedly-confirmed facts surface above one-off noise. Provenance-weighted recall is the first memory-evolution default to flip on.

opt-in preview Capture-time claim management, a synthesised user model and skills memory are shipping behind flags, default-off, while the cross-runtime benchmark calibrates. Safe to try; not yet a promise. Inside the memory layer →

Live recording · Hydrate v0.6.7 · Claude Opus 4.8

See it in action.

Two unedited screen recordings. First you add Hydrate. Then you watch a real Claude Code session survive a /clear with its working context intact. No scripting, no cuts.

1

Add Hydrate

You have Claude Code. You have a project. Two commands and a local memory layer is wired in: brew install, hydrate setup, hydrate init.

2

Watch it work

A live session adds a --word-count flag to glow. The dashboard on the right fills with activity as Hydrate captures the work. Then /hydrate-distill/clear/hydrate-last: the fresh session picks up exactly where the last one left off.

7 minutes, unedited. Splitscreen: Claude Code terminal (left) and the live Hydrate dashboard (right). Click to play.
Side-by-side terminal comparison. Without Hydrate, 40% of input tokens (4,000 of 10,000) are wasted re-explaining the project (stack, repo layout, feature flags, logging library, test conventions) before the actual request. With Hydrate, the same context is injected concisely from project memory, leaving 100% of the budget for actual work. A bar chart at the bottom shows relative cost: Without Hydrate 100%, With Hydrate 60%, i.e. a 40% lower input token cost with Hydrate.
40% of a typical prompt's input tokens are spent re-explaining the project. Hydrate puts that budget back into work.
Cost calculator

What does Hydrate save your team?

Slide to your team size and plan type. Numbers update instantly. Based on benchmark data - indicative figures for planning.

Full ROI breakdown
20
Save ~£2,900 / month
20 devs · 71% session rescue + cache improvement · indicative
Multi-model · cross-runtime

One brain. Every runtime keeps its own model bill.

The same memory across Claude Code, Codex, Mistral Vibe and MCP clients, with Hermes in alpha. Each runtime authenticates and pays for its own model; Hydrate is the layer they share. A decision captured in one injects into the next prompt of any other, which is exactly what lets an Author in one model family and a Critic in another work over shared state.

Five coding tools (Claude Code, VS Code, Codex CLI, Mistral Vibe, and a generic MCP client showing JSON-RPC) all displaying the same onboarding code, connected to a central glowing memory cube labelled ~/.hydrate/data.db. Blue dashed arrows show bidirectional sync between every tool and the central memory; one orange dashed arrow highlights the currently-active connection from Claude Code.
laptop — paired over the tailnet
hydrate peer pair 027-674   # found window on mini
  ✓ paired · scope mini/hydrate
 
hydrate_ask_peer("mini/hydrate", "what now?")
  { status: ok, project: hydrate, git_sha: e035139, … }

Verified live: a laptop and a Mac mini, direct over the tailnet, about 12 ms.

Peernet · machine to machine · new

Ask your other machine what it is working on.

Peernet is opt-in peer messaging between activated sessions on different machines, over your own LAN, VPN or tailnet. No third-party relay, no cloud round-trip: your own daemons talk directly. And the answerer is the daemon, not a live session with shell access. It returns metadata only, the active project, the git SHA, a session summary, with zero filesystem access and zero mutation on the machine that answers.

  • Pair with one code — a six-digit code, single use, two-minute expiry, three attempts. No IP addresses, no config blobs.
  • A daemon answers, not a shell — the main daemon is never exposed; peer traffic gets its own dedicated listener and a per-peer revocable credential.
  • Leased and audited — presence heartbeats every 30 seconds and expires on its own; every ask is minted a thread id on the record.
How Peernet works
BETA Pricing

Start free. Lock $5/mo Pro for your first 12 months.

Register during beta (whichever edition you pick) and your Pro rate is locked at $5/mo for your first 12 months; $9/mo retail thereafter. How this works →

BETA · locks $5/mo for 12 months

Free

$0/ forever

Up to 2 active projects, full hooks + dashboard. No account. Registering during beta also locks the $5/mo Pro rate for your first 12 months.

Install + lock rate
Post-beta

Team

$29/ user / month

Shared project memory across teammates. Indicative launch rate; Team is not part of the beta lock.

Contact sales →

Enterprise

Custom

Self-host or managed. SSO, org-scoped policy facts, audit logs, air-gap support. Online and offline, data synced via git.

Learn more →