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Show HN: Pragma – Stop copying context between AI agents

Pragma, a code-public desktop application for orchestrating multiple AI agents, was released as a preview on GitHub, allowing users to combine agent harnesses, models, tools, and context sources into reusable workflows. The app, which requires Node.js 22 and pnpm 10.12.1, features cross-harness dynamic memory and policy-controlled promotion of experiences into a stable knowledge base or reusable Skills. Pragma is currently available as unsigned builds for macOS Apple Silicon and Intel.

read6 min views1 publishedAug 12, 2026
Show HN: Pragma – Stop copying context between AI agents
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Turn the way you work with AI into a reusable asset.

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Examples Pragma is a code-public desktop application for orchestrating multiple agent harnesses, models, tools, context sources, and human decisions into reusable AI workflows.

A Mission can move from one specialist to another without losing its decisions, artifacts, or accumulated experience. Pragma does not replace Claude Code, Codex, PI, Qoder CLI, Antigravity CLI, or the next great agent—it makes them work together.

The more you use Pragma, the more it compounds. Events from different tasks, harnesses, and models become cross-harness dynamic memory; useful experience and facts can then be promoted automatically, under policy and review controls, into a stable knowledge base or reusable Skills.

Important

Pragma is currently a preview. The latest Desktop release provides unsigned builds for macOS Apple Silicon and Intel. See Current status before adopting it for critical work.

Download the package for your Mac from GitHub Releases, install it, and then:

  • Open Settings and connect a model provider or an installed local runtime. - Choose the workspace Pragma is allowed to use.
  • Talk with Pragma to create your own Expert, ExpertTeam, or Flow.
  • Start a task with the result and use it as much as you like. As Missions accumulate, cross-harness memory turns repeated experience into stable knowledge and reusable Skills.

The current app is not code-signed. To open a Desktop release, use this order:

  • Try opening Pragma normally. - If macOS blocks it, open System Settings → Privacy & Security and chooseOpen Anyway. - Only if it still cannot open, and you have verified that the package came from the official release, clear the app's quarantine attribute:
sudo xattr -r -d com.apple.quarantine /Applications/Pragma.app

You do not need to change the global Allow apps downloaded from setting for this unsigned release.

The Desktop distribution guide explains the release contents, checksums, and limitations.

Requirements: Node.js 22 or later and pnpm 10.12.1.

git clone https://github.com/pqpo/pragma.git
cd pragma
pnpm install --frozen-lockfile
pnpm --filter @pragma/desktop dev

The repository includes runnable examples rather than abbreviated API fragments:

pnpm --filter @pragma/examples example:context

pnpm --filter @pragma/examples example:runtime-codex
pnpm --filter @pragma/examples example:runtime-claude-code

See the examples guide for Expert sessions, delegation, ExpertTeams, Flows, human review gates, MCP, Skills, plugins, memory, recovery, and portable bundles.

Compose Experts, ExpertTeams, Flows, subflows, tools, and human checkpoints. Each step can bind the model, agent harness, permissions, and context that fit the task. The resulting method can be versioned, evaluated, exported, and shared.

Pragma treats context as a Host-owned ContextStore

instead of trapping it inside one chat product. Events from different tasks, harnesses, and models enter a shared Memory Pipeline and become evidence-backed episodic and semantic memory. As that dynamic memory accumulates, background work can automatically start a policy-controlled promotion workflow that turns it into stable knowledge or reusable Skills; authoritative changes are activated only after the required review.

The ContextStore contract is extensible. This repository currently includes in-memory, JSON, filesystem, Mission Board, and Memory-backed implementations; other databases or retrieval systems can be added through Host adapters.

Reusable workflows need regression signals. Evaluations capture the tasks and expectations that matter to you, so changes to a prompt, Flow, model, runtime, or context source can be checked at the system level instead of judged from a single demo.

These assets compound: workflows produce evidence, memory turns evidence into knowledge, and evaluations reveal whether the next revision is actually better.

Use the right model × harness for each step. A model inside a coding agent, browser agent, or domain tool is a different execution capability. Pragma routes work without locking the whole workflow to one vendor.Carry context across the whole Mission. Requirements, decisions, artifacts, review findings, and task state move forward by value or controlled reference. Each Expert receives the context it needs without replaying every transcript.Compose without losing governance. Experts, Teams, and Flows can become steps or governed tools. Nested work remains inside one Execution with a shared audit trail for handoffs, output, approvals, usage, cancellation, and recovery.Keep humans in control. Flows can for clarification, approval, or review, and Desktop owns local workspace access and permission decisions.Move methods between systems. A.pragma

bundle can carry portable DSL and selected project assets. Desktop can import it, while another Host can load it through@pragma/interpreter

and run the compiled object through@pragma/core

.

Flow         = Expert + ExpertTeam + SubFlow + Human checkpoints
Expert tools = Expert + ExpertTeam + Flow

In this example configuration, UI design, requirements, architecture, implementation, and independent review use different specialists. Accepted decisions and artifacts flow between stages, and useful facts, experience, and Skills remain available to the next Mission.

The model and runtime names in the diagram are illustrative. Routing is a Host binding: the reusable method is not coupled to those exact providers.

Use Desktop to configure providers and local runtimes, create Experts and Flows in Studio, run Missions, inspect context and memory, manage evaluations, and import or export .pragma

bundles.

Pragma DSL describes Experts, ExpertTeams, Flows, capabilities, context stores, runtime profiles, automations, and evaluations as versioned YAML. The Interpreter parses, links, validates, migrates, compiles, and dumps these definitions. Start with the portable bundle example and the DSL architecture guide.

Embed the execution model into another Host with @pragma/core

, or load portable definitions and bundles with @pragma/interpreter

. Runnable integrations live in examples/src; the

bundle transfer guidecovers Host bindings and portability boundaries.

Area Current status
Project maturity Preview; breaking changes are still possible
Desktop release macOS Apple Silicon and Intel; unsigned
Windows / Linux Desktop Not included in the current public release
Runtime adapters Claude Code, Codex, PI, and Qoder CLI packages are implemented
Composition Expert, ExpertTeam, Flow, SubFlow, and HumanTask
Context Host contract plus in-memory, JSON, filesystem, Mission Board, and Memory-backed stores
Memory Evidence pipeline with episodic and semantic modules; knowledge and Skill refinement are preview features
Evaluation Versioned evaluations and Flow Run Dry execution
Portability .pragma bundle import, export, validation, binding, and compilation
Distribution No code signing or automatic updates yet

For detailed implementation boundaries, see the current architecture overview.

Usage guidesExperts and sessionsFlows and patternsContextMemoryPluginsPortable Desktop bundlesAgent architectureProduct positioning and differentiation

Read the Contributing Guide before opening a pull request. Use GitHub Issues for reproducible bugs and feature proposals, and follow the Security Policy for vulnerability reports.

Pragma uses the Pragma Source Available License 1.0, a custom source-available license that is not OSI-approved. The full license controls: in particular, third-party hosted services and commercial embedding require prior written authorization. Use of the Pragma name, logo, and official identity is also governed by the Trademark Policy.

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