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meeting notes :ahmed-kristof future of our engineering #4

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opened 2025-12-18 13:30:26 +00:00 by despiegk · 0 comments

despiegk commented

2025-12-18 13:30:26 +00:00

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HeroRoadmap — Agentic Architecture & Execution Model

(Transcribed and normalized from technical discussion)

1. Operating Principles

Standardization on Rust

The team will standardize all core development on Rust.
With AI-assisted development, the cost of porting and rewriting has dropped significantly, making this both practical and efficient.
This enables:
- a single language ecosystem
- shared tooling and macros
- consistent performance, safety, and maintainability

Clean foundations over legacy layering

Rather than adapting around existing complex systems, we will:
- work closer to low-level primitives
- wrap only what we truly need
- keep abstractions minimal and intentional
This reduces long-term complexity and increases agent effectiveness.

2. HeroLib & Component Structure

HeroLib (Rust)

HeroLib becomes the core capability library, structured as composable packages:

Core
- Networking (HTTP, SSH, TCP)
- Messaging (MQTT)
- Logging & observability primitives
- Text, parsing, HeroScript support
Clients
- External services (Hetzner, Postgres, Redis, etc.)
- Each client independently buildable and testable
OS
- System-level primitives:
  - process management
  - filesystem
  - virtualization
  - networking
  - installers and platform tools
Aggregation layer
- Higher-level binaries aggregate capabilities from the above packages.

Each package:

exposes a small, explicit surface
includes a minimal binary for testing/demo
is designed to be wrapped for agent usage

3. HeroScript / Rai as the Control Plane

Script-first interaction model

Instead of large RPC surfaces or many MCP servers:
- functionality is exposed via HeroScript / Rai
- agents send scripts, not API calls
Benefits:
- simpler mental model
- more readable and inspectable
- faster agent adaptation
- lower coordination overhead

Embedded execution

Each component:
- embeds a lightweight Rai engine
- registers itself over a socket
A single supervisor (e.g. Zinit):
- manages processes
- eliminates the need for bash scripts, systemd units, or manual orchestration
All components self-register and self-manage.

This creates a REPL-like, scriptable runtime usable by:

humans
agents
higher-level orchestration systems

4. Agentic Development Model

Agents as first-class executors

Agents are expected to:
- write code
- run commands
- test, benchmark, and iterate
Human role shifts toward:
- defining primitives
- constraining contexts
- validating outcomes
- designing clean abstractions

Knowledge over instructions

The system is designed to encode how to do things, not just commands:
- “how to manage processes”
- “how to initialize a VM”
- “how to provision compute”
Agents consume this knowledge directly via scripts and wrappers.

5. Data & Synchronization Model

Fossil-inspired backend (rewritten in Rust)

A new Rust-native, Fossil-like datastore is used for:
- efficient delta-based storage
- syncing between peers
- versioned metadata
Performance characteristics:
- very high read/write throughput
- efficient synchronization
Git import support is added for interoperability.

Files as truth

Structured files (HeroScript, TOML, Markdown) are:
- the primary data representation
- parsed directly from the datastore
WebDAV layer allows:
- direct mounting as a filesystem
- no checkout/check-in loops
The datastore becomes the single source of truth.

Decentralized coordination via Holochain

Holochain is used selectively for:
- peer discovery
- group membership
- synchronization coordination
- billing primitives (UNIT / mutual credit)
No central server required:
- peers sync directly
- read-only or read-write replicas are optional

6. Virtualization & Infrastructure Direction

Move away from “cloud-first” thinking

The system is designed for agents, not humans.
Agents do not need traditional cloud abstractions.
Focus is on:
- lowest-level hardware access
- high-bandwidth, low-latency paths
- simple, composable primitives

VM initialization

Instead of cloud-init:
- a minimal HeroInit binary runs inside the VM
- driven entirely by HeroScript
VM boot sequence:
- start Zinit
- execute initialization scripts
- nothing else required

Virtualization primitives

Wrap only what is necessary:
- Cloud Hypervisor
- QCOW2
- storage backends
Expose a small, curated feature set to agents.
Avoid exposing full complexity of systems like Kubernetes; instead:
- provide a simplified, agent-optimized subset

7. Execution Model & Team Focus

Small, high-skill core

A small group drives:
- abstraction design
- primitive definition
- architectural coherence
Others are:
- brought up to speed via well-defined tasks
- shielded from unnecessary complexity

Cleanliness is non-negotiable

Minimal surface areas
Explicit contexts
No parallel architectures
No uncontrolled experimentation

Immediate next steps

Deep dive into HeroLib
Identify primitives needed (VMs, storage, networking)
Create issues and branches per capability
Standardize prompts and agent workflows
Align new and existing work into one architecture

8. Core Message

We are building a clean, minimal, agent-native platform where:

Rust provides the foundation
HeroScript / Rai provides control
Agents execute most work
Humans design primitives and constraints
Data, compute, and coordination are decentralized by design

This positions Hero, Lumina, and GeoMind as infrastructure for the agentic era, not an extension of legacy cloud models.

# HeroRoadmap — Agentic Architecture & Execution Model *(Transcribed and normalized from technical discussion)* ## 1. Operating Principles ### Standardization on Rust * The team will **standardize all core development on Rust**. * With AI-assisted development, the cost of porting and rewriting has dropped significantly, making this both practical and efficient. * This enables: * a single language ecosystem * shared tooling and macros * consistent performance, safety, and maintainability ### Clean foundations over legacy layering * Rather than adapting around existing complex systems, we will: * work closer to **low-level primitives** * wrap only what we truly need * keep abstractions minimal and intentional * This reduces long-term complexity and increases agent effectiveness. --- ## 2. HeroLib & Component Structure ### HeroLib (Rust) HeroLib becomes the **core capability library**, structured as composable packages: * **Core** * Networking (HTTP, SSH, TCP) * Messaging (MQTT) * Logging & observability primitives * Text, parsing, HeroScript support * **Clients** * External services (Hetzner, Postgres, Redis, etc.) * Each client independently buildable and testable * **OS** * System-level primitives: * process management * filesystem * virtualization * networking * installers and platform tools * **Aggregation layer** * Higher-level binaries aggregate capabilities from the above packages. Each package: * exposes a **small, explicit surface** * includes a minimal binary for testing/demo * is designed to be wrapped for agent usage --- ## 3. HeroScript / Rai as the Control Plane ### Script-first interaction model * Instead of large RPC surfaces or many MCP servers: * functionality is exposed via **HeroScript / Rai** * agents send scripts, not API calls * Benefits: * simpler mental model * more readable and inspectable * faster agent adaptation * lower coordination overhead ### Embedded execution * Each component: * embeds a lightweight Rai engine * registers itself over a socket * A single supervisor (e.g. Zinit): * manages processes * eliminates the need for bash scripts, systemd units, or manual orchestration * All components self-register and self-manage. This creates a **REPL-like, scriptable runtime** usable by: * humans * agents * higher-level orchestration systems --- ## 4. Agentic Development Model ### Agents as first-class executors * Agents are expected to: * write code * run commands * test, benchmark, and iterate * Human role shifts toward: * defining primitives * constraining contexts * validating outcomes * designing clean abstractions ### Knowledge over instructions * The system is designed to encode **how to do things**, not just commands: * “how to manage processes” * “how to initialize a VM” * “how to provision compute” * Agents consume this knowledge directly via scripts and wrappers. --- ## 5. Data & Synchronization Model ### Fossil-inspired backend (rewritten in Rust) * A new Rust-native, Fossil-like datastore is used for: * efficient delta-based storage * syncing between peers * versioned metadata * Performance characteristics: * very high read/write throughput * efficient synchronization * Git import support is added for interoperability. ### Files as truth * Structured files (HeroScript, TOML, Markdown) are: * the primary data representation * parsed directly from the datastore * WebDAV layer allows: * direct mounting as a filesystem * no checkout/check-in loops * The datastore becomes the **single source of truth**. ### Decentralized coordination via Holochain * Holochain is used selectively for: * peer discovery * group membership * synchronization coordination * billing primitives (UNIT / mutual credit) * No central server required: * peers sync directly * read-only or read-write replicas are optional --- ## 6. Virtualization & Infrastructure Direction ### Move away from “cloud-first” thinking * The system is designed **for agents, not humans**. * Agents do not need traditional cloud abstractions. * Focus is on: * lowest-level hardware access * high-bandwidth, low-latency paths * simple, composable primitives ### VM initialization * Instead of cloud-init: * a minimal **HeroInit** binary runs inside the VM * driven entirely by HeroScript * VM boot sequence: * start Zinit * execute initialization scripts * nothing else required ### Virtualization primitives * Wrap only what is necessary: * Cloud Hypervisor * QCOW2 * storage backends * Expose a **small, curated feature set** to agents. * Avoid exposing full complexity of systems like Kubernetes; instead: * provide a simplified, agent-optimized subset --- ## 7. Execution Model & Team Focus ### Small, high-skill core * A small group drives: * abstraction design * primitive definition * architectural coherence * Others are: * brought up to speed via well-defined tasks * shielded from unnecessary complexity ### Cleanliness is non-negotiable * Minimal surface areas * Explicit contexts * No parallel architectures * No uncontrolled experimentation ### Immediate next steps 1. Deep dive into HeroLib 2. Identify primitives needed (VMs, storage, networking) 3. Create issues and branches per capability 4. Standardize prompts and agent workflows 5. Align new and existing work into **one architecture** --- ## 8. Core Message We are building **a clean, minimal, agent-native platform** where: * Rust provides the foundation * HeroScript / Rai provides control * Agents execute most work * Humans design primitives and constraints * Data, compute, and coordination are decentralized by design This positions Hero, Lumina, and GeoMind as **infrastructure for the agentic era**, not an extension of legacy cloud models.

despiegk closed this issue

2025-12-18 13:30:30 +00:00

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