Browse the Tinker Zone
Everything we publish, newest first — pick a folder to filter, or scroll the latest below.
Building Jarvis AI & Agents Tutorials Behind the Scenes Open Source Inventions
-
Learned Intuition: A Reflex Layer That Stops Your Agent Before It Does the Wrong Thing
Your agent had all the context it needed and still did the wrong thing — AMYGDALA gives it a learned reflex layer that pauses dangerous actions…
-
AEGIS: A Multi-Layered Security Framework for Autonomous AI Agents
The honest question isn’t whether your agent deployment could be a problem — it’s which specific problems apply to yours, and what mitigations are actually proportionate.…
-
Budget Prompting: Cutting the Cost of Always-On Memory Agents 2–3×
Leave your agent running overnight and the bill is brutal: every turn re-bills the whole context window. Budget Prompting is 20 techniques that cut per-turn cost…
-
PREFRONTAL: Giving Your Agent an Executive Function with a Recipe Execution Substrate
Your model is a brilliant worker and a terrible executive — PREFRONTAL is the missing executive layer: a recipe execution substrate that picks the right playbook,…
-
MNEMOSYNE: Four Hooks That Upgrade Your Agent’s Memory Without Forking It
Your long-running agent’s memory has four quiet failure modes — slow lookups, task-blind retrieval, silent contradictions, and detail destroyed at compaction — and MNEMOSYNE fixes all…
-
Why Your Pre-Push Privacy Gate Is Lying to You — and the Recipe as the Missing Middle Layer
Every individual push passed the privacy gate. The accumulated history still leaked 16 times — here’s the per-delta-vs-cumulative trap, and the named, replayable abstraction that sits…
-
Total Recall: Pointer-Based Compaction and Task-Conditioned Retrieval for Persistent LLM Agents
Most AI agents compact old context by summarizing it — quietly losing the one detail that mattered. Total Recall is a lossless, event-sourced memory architecture that…
-
Running an AI Agent 24/7: What Nobody Tells You
75 crashes, 45 wrong messages, and 138 restart loops. What actually happens when you leave an AI agent running around the clock.
-
How to Track AI Token Costs in Real Time
See where every AI token goes — in real time, not on next month’s invoice. Practical strategies that cut our daily costs by 60%.
-
How to Set Up Self-Improving AI Cron Jobs
The META pattern: AI cron jobs that rewrite their own prompts after each run. Day 1 mediocre, Day 30 expert. No human intervention.
-
The Field Guide for AI Agents: 32 Lessons from Running One 24/7
32 hard-won lessons from running an AI agent 24/7. The operational manual nobody else has written.
-
TinkerClaw: We Forked OpenClaw. Here’s What We Changed and Why.
262 fork commits, a real-time token dashboard, cognitive memory, and self-improving crons. What TinkerClaw adds to OpenClaw — and why we built it.











