Watering the garden just got easier

This is more than a programmable tap with a timer. My own local AI oversees the watering now. It reads soil moisture from sensors in the beds, checks the weather, and decides whether each zone actually needs water. If a bed is already damp, it skips the cycle. If it’s been hot and dry, it waters longer

The setup is simple: a small home-automation hub, a two-zone smart water valve, and a few wireless soil sensors. One zone feeds the flower beds, the other feeds the vegetable garden and containers. Everything talks locally over Zigbee, so it still works even without internet

The part I like best is that it’s my own setup; local ai, opensource software, my hardware. The schedule, the data, the decisions - none of it lives in someone else’s cloud, app or platform.

It’s practical: plants stay alive, water doesn’t get wasted, and I don’t have to stand there with a hose.

What actually works in our OpenClaw setup (and the pain it fixed)

If you're spinning up OpenClaw and hitting the usual walls (context overflow, wrong model for the job, forgotten conversations, flaky pipelines), here's the stack and discipline that got us past it.

1. MRDE: route before you prompt
We built a Model Routing Decision Engine so every request hits the right model tier first, not after trial and error.

• Local private: sensitive stuff stays on-device (gemma-4-26B-MLX, ornith:9b for fast local lanes).
• Local heavy: deep reasoning when latency doesn't matter (ornith:35b, qwen3.6-35b for legal).
• Cloud coding/synthesis: complex troubleshooting (kimi-k2.7-code:cloud, kimi-k2.6:cloud, deepseek-v4-flash:cloud).
• Cloud fast fallback: quick answers when local is cold (gemma4:31b-cloud).

Pain solved: no more asking a 2.8T-parameter cloud model to grep logs, and no more running private queries through cloud APIs by accident.

2. Two-tier memory + RAG

• Immutable corpus: law sources, primary docs, transcripts. Append-only, never rewritten.
• Evolving memory: daily notes, decisions, lessons, atomic reports. Rewritten and refined.
• RAG v2: 10 corpora, ~66k chunks, all embedded. The assistant recalls before answering, then writes back compact, cited notes.

Pain solved: the system stops hallucinating continuity. It actually remembers yesterday, last week, and the source of the claim.

3. The loop: capture → recall → act → write back
Everything runs on a small, durable loop:

• Capture: drop it in the inbox (AirDrop, Telegram, share sheet, cron).
• Recall: search memory + RAG before any real work.
• Act: use the right tool/model for the task.
• Write back: one compact note with provenance (file path, source ID, or daily note).

For bigger tasks we add a gauntlet: run the output through critic models, check facts, verify file hashes, then keep or repair.

Pain solved: slop dies here. The system produces fewer, higher-quality artifacts instead of endless chat noise.

4. Scheduled pipelines (the nightshift)
A single cron at 02:00 dispatches phased jobs: I/O-bound tasks, then cloud API tasks, then local ML/vision, then reflection/audit. Local-ML concurrency is capped at 1 so vision models don't fight for the GPU.

Pain solved: long-running jobs finish overnight instead of interrupting the day, and the Mac doesn't melt.

5. Voice as default input
Whisper STT → local LLM → Kokoro TTS. Zero API cost, hands-free, and it actually gets used.

Pain solved: typing long prompts on mobile is miserable. Voice removes friction.

Advice for new OpenClaw builders

• Lock your default model before you build a dozen workflows. Routing is cheaper than re-prompting.
• Write memory back immediately after meaningful work, not at end of day.
• Use small verification loops (syntax checks, dry runs, file hashes) before trusting any autonomous edit.
• Run heavy/local-ML jobs in a single queue with concurrency caps, not in parallel cron storms.
• Prefer local TTS/STT once it's good enough. The cost and latency win is real.

The big shift: stop treating OpenClaw like a chatbot and start treating it like an operating system with memory, scheduling, and routing. The rest follows.

#OpenClaw #LocalAI #AIAgents #ai

Amazing soup in Vancouver

Photographed my paint drawers and my AI assitant inventoried every color + flagged what's running low. Studio hacks are getting weird but life’s too short to squeeze every tube.

just sayin'😉

Don’t you just love being in a room full of art ?

Art therapy at Kimoto Gallery, Ucluelet.

First Bend in the River
12x24” acrylic on canvas
available at Kimoto Gallery, Ucluelet.

This chill Frog was watching me work - just hanging out for a while. Then he came over to get in on some hose water.

Coffee n haircut vibes

Fresh Raspberries are pretty hard to beat.

Just sayin’

What’s on the easel ?

This pair of paintings I’m grinding it out on. I have a hard deadline - it’s gonna a be a long night.

Coffee and brush-miles
Let’s Go.

#artstr #painting #artwork #in-progress #studio

Enjoying the day

I have a deadline and work to do, but I’m still gonna take time to enjoy the day.

Coffee and some morning sunshine on my face.

Next : a productive session at the easel.