They lose production facts.
They forget which backend is live, which credential is stale, which deployment fixed the issue, or which test device is real.
Repeatable agent operations
A token-efficient operating framework for AI coding assistants.
AiML SuperAgent turns an AI coding assistant into a long-term project operator. It keeps scoped memory, verifies production reality before changing code, protects secrets, tracks deployments, minimizes wasted context, and produces small safe diffs.
agent.read("REPO_SOURCE_OF_TRUTH.json")
agent.read("WORKING_NOTES.md")
agent.search("only the current task")
agent.verify("production reality")
agent.patch("small safe diff")
agent.test("fast meaningful proof")
agent.note("durable facts only")Why this framework?
Most AI coding assistants fail long-running projects in two ways.
They load stale context.
They reread too much, trust old notes, and burn context on files that do not matter to the current task.
Beyond basic agent rules
The next layer after CLAUDE.md.
Behavior rules help with a single session: think first, keep changes small, avoid assumptions, and verify results. AiML SuperAgent starts there, then adds the missing operating layer: scoped project memory, source-of-truth files, deployment history, secret-safe notes, production checks, and context-minimizing workflows.
The result is not just a better prompt. It is a repeatable system for turning any AI coding assistant into a safer long-term project operator.
Use CLAUDE.md for behavior. Use AiML SuperAgent for long-term project operation.
A CLAUDE.md file can teach an assistant how to behave. AiML SuperAgent teaches it how to operate.
Prompts are temporary. Production memory has to survive the next session.
The smartest model still needs a source of truth.
Less context. Better recall. Smaller diffs.
Behavior
CLAUDE.md is excellent for session rules: think first, avoid assumptions, keep changes small, and verify results.
Memory
AiML SuperAgent adds durable project memory: source-of-truth files, working notes, deployment history, and stale-fact cleanup.
Operations
It turns careful behavior into repeatable execution with secret-safe notes, production checks, context minimization, and small safe diffs.
Model-agnostic
Works with the assistant you already use.
AiML SuperAgent is not tied to one vendor. Use the same memory, verification, deployment, and context-minimizing workflow across Claude, GPT-5.5, Perplexity, Codex, Cursor, Gemini, and local agents.
ClaudeGPT-5.5PerplexityCodexCursorGeminilocal modelsCommercial application
From agent framework to business operating layer.
AiML SuperAgent is the method. AiML Nexus is where that operating discipline becomes a connected AI system for real teams.
AiML Nexus unifies ecommerce, messaging, support, and automation into one AI-powered layer that helps modern retail and service teams move faster without replacing the tools they already use.
Explore AiMLNexus.comAiML Nexus
Connect your entire business into one AI-powered system.
EcommerceMessagingSupportAutomationHeadline feature
Context Minimizer
AiML SuperAgent reduces token waste by keeping durable memory separate from the live context needed for the current task.
Core rule
Do not make the notes smaller. Make the active context sharper.
Start with the facts that survive across tasks, then pull only the files, logs, and commands needed to prove the next change.
Read
Source of truth, working notes, and the current task prompt.
REPO_SOURCE_OF_TRUTH.jsonWORKING_NOTES.mdSearch
Target the exact code paths, config, logs, and deployment state.
rg -n "current problem"rg --filesSkip
Leave generated output, dependencies, and resolved history out of context.
node_modules / .next / distlarge logs / DerivedDataOperating framework
Enough memory to be useful. Not enough context to get confused.
Scoped project memory
Source-of-truth files
Production-first verification
Secret-safe notes
Deployment logs
Small safe diffs
Context Minimizer
Read scoped memory
Start from source-of-truth files and current notes, not the entire repo.
Verify reality
Check code, configs, logs, deployments, and live state before changing behavior.
Make a small diff
Change only what traces directly to the task and preserve unrelated work.
Prove the result
Run the fastest meaningful build, test, browser, or production check available.
Update memory
Record only durable facts, decisions, risks, and stale-note corrections.
Public repo kit
Ship the method, not private production notes.
AiML SuperAgent is designed to be public and reusable. Templates use example names and roles, never real secrets, customer identifiers, or private account data.
Templates
WORKING_NOTES.mdREPO_SOURCE_OF_TRUTH.jsonDEPLOYMENT_LOG.mdINCIDENT_REPORT.mdSAFE_ENV_AUDIT.mdDocs
principles.mdproject memory.mdcontext minimizer.mdverification loop.mdsafe tools and secrets.mddeployment workflow.mdnote hygiene.mdGive the agent enough memory to be useful, but not so much context that it becomes slow, expensive, stale, or confused.
Created byMarvin Freedman