A fully integrated AI operating layer for Linux. One compiled binary, zero cloud dependencies, 80+ models, every OS action, a full IDE, an autonomous finance engine, and deep desktop integration that no SaaS competitor can replicate — because it requires owning the OS.
| Feature | Electra | Cursor | Claude Code | VS Code | Antigravity |
|---|---|---|---|---|---|
| Multi-model routing (80+ models) | ★ | ~ | ✗ | ✗ | ✗ |
| Full GUI IDE (GTK3, GtkSourceView) | ✓ | ✓ | ✗ | ✓ | ~ |
| Terminal / CLI mode | ✓ | ✗ | ✓ | ~ | ✗ |
| Agentic tool-calling coder | ✓ | ✓ | ✓ | ~ | ✓ |
| Agent Swarm (parallel workers) | ★ | ✗ | ✗ | ✗ | ✗ |
| LSP integration (pyright, tsserver…) | ✓ | ✓ | ✗ | ✓ | ✗ |
| Ghost text inline completions | ✓ | ✓ | ✗ | ~ | ~ |
| Streaming diff preview | ✓ | ✓ | ✗ | ✗ | ~ |
| Open VSX extension support | ✓ | ✗ | ✗ | ✓ | ✗ |
| AT-SPI screen awareness | ★ | ✗ | ✗ | ✗ | ✗ |
| D-Bus two-way desktop control | ★ | ✗ | ✗ | ✗ | ✗ |
| Voice input / TTS output | ✓ | ✗ | ✗ | ✗ | ✗ |
| Offline / local models (Ollama) | ✓ | ✗ | ✗ | ~ | ✗ |
| Telegram bridge | ★ | ✗ | ✗ | ✗ | ✗ |
| Home Assistant integration | ★ | ✗ | ✗ | ✗ | ✗ |
| Finance bot / earn online | ★ | ✗ | ✗ | ✗ | ✗ |
| Heartbeat background task agent | ★ | ✗ | ✗ | ✗ | ✗ |
| Discord / Reddit / RSS / Spotify agents | ★ | ✗ | ✗ | ✗ | ✗ |
| Git panel (built-in) | ✓ | ✓ | ✗ | ✓ | ~ |
| Image generation & analysis | ✓ | ✗ | ✗ | ✗ | ✗ |
| Project knowledge base (/pk) | ✓ | ✓ | ✓ | ✗ | ✓ |
| ChromaDB vector memory | ✓ | ✗ | ✗ | ✗ | ✗ |
| Patreon tier system | ✓ | ✗ | ✗ | ✗ | ✗ |
| Single compiled binary (Nuitka) | ★ | ✗ | ✗ | ✗ | ✗ |
| Source code Q&A agent | ★ | ✗ | ✗ | ✗ | ✗ |
| Codeberg integration | ★ | ✗ | ✗ | ✗ | ✗ |
| Novel / long-form writing mode | ★ | ✗ | ✗ | ✗ | ✗ |
| Live Code Map (workspace awareness) | ✓ | ✓ | ✓ | ✗ | ~ |
| Cinnamon / GNOME / KDE / XFCE support | ★ | ✗ | ~ | ✓ | ✗ |
| Right-click context actions (Nemo) | ★ | ✗ | ✗ | ✗ | ✗ |
★ = Electra-unique or category leader · ✓ = present · ~ = partial · ✗ = absent
| Tier | Daily Requests | Premium Providers | Agent Swarm | Priority |
|---|---|---|---|---|
| Free | 50 / day | Standard pool | ✗ | Base |
| Private | 500 / day | Standard pool | ✗ | Base |
| Corporal | 1,500 / day | Standard pool | ✗ | Medium |
| Sergeant | 4,000 / day | Standard pool | ✗ | High |
| Major — $40/mo | 10,000 / day | ds- bt- ol- unlocked | ✓ | Top |
| Commander — $100/mo | Unlimited ∞ | ds- bt- ol- unlocked | ✓ | Top |
Major+ subscribers get paid providers auto-prioritized in Coder and Command mode routing. GUI model picker sorts premium models to top.
The binary targets the oldest practical glibc (2.34 via Ubuntu 22.04 base) so it runs on essentially any distro released since 2021. MakuluLinux (Cinnamon on Ubuntu 24.04) is the primary development and showcase platform with the deepest integration (right-click context actions, Super+E bar, AT-SPI, D-Bus).
/overdrive · Badge: ⚡ OD in GUI info bar./loopeng on|off · individual subsystems: /loopeng critic on|off · /loopeng decomp on|off · /loopeng replan on|off
tokenColors syntax highlighting from VS Code themes, and actually launching detected LSP servers registered from extensions. Snippet engine partially done — tabstop jumps and TM_ vars shipped, full nesting remains.--auto-fix: dispatches the coder agent to implement the fix autonomously. Commands: /ci watch owner/repo [--auto-fix] [--chat <id>] · /ci status · /ci unwatch · /ci fix owner/repo <run_id>. State persisted in ~/.electra/ci_watch.json and ci_state.json./gh fix issue <number> (specific) or /gh fix issue (interactive list). Telegram notification at each stage. New GitHub API primitives added: get_issue(), create_branch(), create_pull_request(), list_open_issues(), get_run_logs().debugpy is the first target; Node.js inspector second. Large effort — 3–6 weeks properly scoped.platform_compat.py shim approach identified. GTK3 available on both platforms via MSYS2/Homebrew. AT-SPI and D-Bus are Linux-only — needs graceful degradation stubs. Expands addressable audience significantly. Linux remains the native home.~/.electra_project_brain.md: every file and what it does (updated on write), every architectural decision and why it was made, every bug fixed and how, user preferences learned over time ("always run AST validation before patching"). The coder, command, and loop engineering agents all read this document — dramatically improving context accuracy with zero extra API calls. No SaaS AI tool can replicate this because they have no persistent local storage. The longer a user uses Electra, the smarter it gets. That is a compounding moat competitors cannot buy their way into.
scrot or gnome-screenshot plus vision models — far more capable than browser-only tools and completely unique to a locally-running platform.
electra_state.json
HIGH
~/.electra/state.json written after every session and read before any prompt
is constructed. Tracks: per-domain operational confidence scores
(command_mode: 0.87, file_regex_ops: 0.61, etc.),
autonomy trust dial (0.0–1.0), contradiction log, domain failure rates, and last-updated
timestamp. This file is the behavioral substrate — it changes what Electra does,
not just what it knows. The critical difference: current memory systems inject text
into prompts. This system mutates operational parameters before prompts are built.
electra_state.json and
directly shape system prompt language: confidence > 0.85 → "Proceed autonomously";
confidence 0.6–0.85 → "Proceed but verify key steps"; confidence < 0.6 → "Confirm before
destructive operations." The existing _COMMAND_FAILURES_FILE already captures
per-command failure history — this extends it to a scored, decaying, cross-session confidence
model per domain class.
DRY_RUN_MODE with a floating AUTONOMY_LEVEL (0.0–1.0) that
adjusts dynamically based on session outcomes. A clean session (all tools succeed, user
accepts output) raises trust slightly. A session with rollbacks, user corrections, or
repeated failures lowers it. At 1.0: full autonomy, zero confirmations. At 0.5: confirm
before destructive operations. At 0.0: confirm every tool call. Users can manually anchor
the dial via /trust 0.7 or let it self-calibrate. This is the difference
between Electra acting like a junior dev that needs approval and a senior dev you trust
to run with a task.
~/.electra/contradictions.json, and injected into future sessions
as context tension — not as an instruction, but as a named unresolved conflict the AI
can reason about. This transforms Project Brain from a knowledge store into a consistency
guardian.
/state report): "Since last week, your command-mode confidence has risen
from 0.71 to 0.89. Regex operations remain your weakest domain at 0.58. Two unresolved
contradictions detected." The system surfaces its own internal evolution explicitly.
Phase 4 is complete. Phase 5 is active. Electra AI is a full-stack Jarvis-style AI platform: a compiled binary, 80+ models, a complete IDE, autonomous background agents, finance engine, deep OS integration, and service connections that no SaaS competitor can replicate. The June 2026 sprint delivered OVERDRIVE (small model boost), True Loop Engineering v2 (Critic Pass reading real files, AI-driven Decomposer, Dynamic Replan, CI Watch Loop, Issue-to-PR automation), and the GUI Output Terminal pane.
Phase 5 priority: next-level unconventional features. Five breakthrough capabilities identified that no competitor is shipping — Project Brain (persistent semantic memory that compounds over time), Speculative Execution (pre-fetch while user is still typing), Specialist Agent Panels (security/performance/test experts in parallel), Predictive Heartbeat (acts before you ask), and the Visual Feedback Loop (screenshot → act → verify via vision models). These are ordered by impact-to-effort ratio and represent the clearest path to making Electra genuinely irreplaceable rather than merely competitive.
Phase 6 target: IMPRINT — the architectural gap no competitor has closed. Most AI systems can retrieve memory. Very few carry behavioral continuity. IMPRINT introduces a persistent behavioral state substrate (~/.electra/state.json) that survives session boundaries: per-domain confidence scores that decay and recover through experience, a graduated autonomy trust dial (replacing the binary DRY_RUN switch), a contradiction detector that flags when Electra is about to act against a previously recorded preference, and a behavioral pressure layer that mutates operational parameters — not prompts — based on accumulated experience. The distinction is architectural: today Electra changes what the AI knows per session. IMPRINT makes Electra change how it behaves across sessions. Every session leaves a mark.
The OS moat keeps compounding. Every sprint adds capabilities that require owning the Linux distro and running locally. No cloud AI tool can read your screen with AT-SPI, control your desktop via D-Bus, maintain a persistent semantic model of your project across sessions, or fire a Telegram alert when a background task completes. Electra does all of this in one binary — and with Project Brain, it gets smarter about your specific project every single day.
GitHub: github.com/raymerjacque/Electra_AI_Center
Electra AI Center: https://makululinux.us/electra.html
AI-OS: https://makululinux.us/ai-os.html
Full Guide: https://makululinux.us/ai-terminal-guide.html
Daily Updates/Community: https://www.patreon.com/makululinux
Source Code: https://makululinux.us/electra_agent.html