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Running a local coding agent on a Mac Mini — the actual setup

Running a local coding agent on a Mac Mini Running a local coding agent on a Mac Mini — the actual setup By Vilius Vystartas I have an agent that does my low-stakes coding. File edits, test fixes, build verification. The kind o…

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Running a local coding agent on a Mac Mini






Running a local coding agent on a Mac Mini — the actual setup



By Vilius Vystartas



I have an agent that does my low-stakes coding. File edits, test fixes, build verification. The kind of work you'd normally do yourself but it's faster to delegate. It also writes Playwright tests, reviews code, updates documentation, and runs deploys.



It runs locally — Mac Mini M4, 24 GB. No cloud API calls for the coding part. The orchestration layer still uses a cheap cloud model for planning and routing. The actual file editing is done by Pi, a coding agent that connects to oMLX, an OpenAI-compatible local LLM server.



The same setup can drive Claude Code, Codex, or any coding agent that speaks OpenAI-compatible API. Pi is what I use, but the oMLX server works with anything.



All the model names, config files, and paths are inside the script at the bottom.






Two models



I keep two and swap depending on the task. The 24 GB can't hold both at once.



One as good as I can have on this machine — 9B class, ~20 tok/s. Primary coding model.



Another fast — 4B class, ~27 tok/s. File edits, quick fixes, daily tasks.



The swap script moves one out, brings the other in, restarts the server. Takes about 5 seconds.






What Pi does




  • File edits and refactoring

  • Writing and fixing tests (Playwright, unit tests)

  • Build verification

  • Code review

  • Documentation updates

  • Running deploys



Anything more complex than a one-liner goes through RPC mode. The orchestration layer writes a prompt, Pi executes, the result comes back. No tmux, no process wrangling.






Pi extensions — what they do, why I use them





  • pix-optimizer — ponytail + caveman (lazy dev mode and token compression). Keeps Pi output tight and skips boilerplate.


  • context-mode — workspace routing and tool call interception. Keeps Pi from wandering into the wrong directories.


  • pi-subagents — spawns sub-agents. Parallel work without blocking the main session.


  • pi-workflow-engine — multi-step task orchestration. Lets Pi handle sequences without losing context.


  • pi-mcp-adapter — MCP server connectivity. Connects to context7 and scrapling for external tools.


  • @fgladisch/pi-caveman — additional compression on top of pix-optimizer.






Known issues




  • Can only keep one model loaded at a time. Two = OOM. Swap script handles it.

  • Thinking mode must be disabled. Defaults to chain-of-thought, kills speed.

  • Full chat history in prompts crashes the local model. Prompts must be just the files and changes.

  • Print mode skips safety controls. Use RPC mode for anything non-trivial.

  • First request after a model swap can time out. Retry once.






The blueprint






curl -fsSL https://workswithagents.dev/static/setup-local-llm-pi.sh | sh


1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - Running a local coding agent on a Mac Mini — the actual setup
id: 471bdc64-c9e8-403c-b69a-a96ef7cd1bdf
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "Running a local coding agent o" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Running a local coding agent on a Mac Mi")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*Running a local coding agent on a Mac Mi*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "Running a local coding agent on a Mac Mi"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
🛡️
Exploit PoC Security Sandbox & Payload Analyzer TEXT
Danger Index:25/100 SAFE_ANALYSIS_ONLY
✅ Keine offensichtlich destruktiven Befehle erkannt.
Standard-Analystenprüfung vor Ausführung empfohlen.
Erkannte Gefahrensignaturen (1):
HIGHPAYLOAD_DROPPER:Download-and-Execute Dropper-Muster (Piped Shell-Execution).
curl -fsSL https://workswithagents.dev/s
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich Running a local coding agent on a Mac Mi.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
🔗 Semantisch verwandte Zero-Days MariaDB 11.7 VEC
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