惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

云风的 BLOG
云风的 BLOG
C
CERT Recently Published Vulnerability Notes
阮一峰的网络日志
阮一峰的网络日志
G
Google Developers Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
P
Privacy International News Feed
N
News and Events Feed by Topic
博客园 - Franky
Spread Privacy
Spread Privacy
P
Privacy & Cybersecurity Law Blog
T
Tor Project blog
博客园_首页
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Hugging Face - Blog
Hugging Face - Blog
P
Proofpoint News Feed
博客园 - 叶小钗
S
Securelist
Stack Overflow Blog
Stack Overflow Blog
The Cloudflare Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
V
Vulnerabilities – Threatpost
量子位
D
Docker
NISL@THU
NISL@THU
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
美团技术团队
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Engineering at Meta
Engineering at Meta
小众软件
小众软件
F
Fortinet All Blogs
Cisco Talos Blog
Cisco Talos Blog
N
News | PayPal Newsroom
F
Full Disclosure
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
B
Blog RSS Feed
博客园 - 三生石上(FineUI控件)
WordPress大学
WordPress大学
Apple Machine Learning Research
Apple Machine Learning Research
有赞技术团队
有赞技术团队
Martin Fowler
Martin Fowler
T
Threat Research - Cisco Blogs
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
H
Heimdal Security Blog
L
Lohrmann on Cybersecurity
IT之家
IT之家
Webroot Blog
Webroot Blog
P
Palo Alto Networks Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Cloudbric
Cloudbric
Blog — PlanetScale
Blog — PlanetScale

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
Agents That Remember Where They Were
IT Lackey · 2026-05-05 · via DEV Community

This is part nine in a series about managing the growing pile of skills, scripts, and context that AI coding agents depend on. Part one introduced progressive disclosure. Part two unified your local assets across platforms. Part seven covered shared team skills via Git repos.

Ask an agent to ship a release and it will start confidently. It runs the build, opens the changelog, checks the branch. Then something interrupts the session — you close the terminal, the context window fills up, you need to switch tasks. When you come back, the agent has no idea where it left off. You either restart from scratch or spend time reconstructing what happened.

This is the central problem with agents and multi-step work. They're good at individual tasks. They're not naturally good at procedures — sequences of steps that span time, accumulate state, and need to be resumable when interrupted.

akm ships three features that address this directly: workflow assets for stored, resumable procedures; vault assets for secret-aware environment config; and a writable git stash that keeps your skill collection in sync across machines. This post explains what each one does and how they fit together.

The Problem: Tasks Versus Procedures

A task is "write this function." A procedure is "ship this release." Tasks have a beginning and end that fit inside a single context window. Procedures have steps, dependencies between steps, and state that persists across sessions.

When agents handle procedures today, the state lives only in the conversation. That's fine for a five-minute task. It breaks down for anything that takes an hour, involves multiple sessions, or needs to be audited later. If something fails at step four of seven, there's no standard way to resume at step five without replaying the whole context.

The workaround most developers reach for is a checklist in a markdown file. The agent checks off items as it goes. This works, but it's manual, fragile, and the state isn't queryable. You can't ask "which deployments are currently in-progress" if the state is scattered across markdown checkboxes in different files.

Workflow assets are the structured version of that checklist.

Workflow Assets: Stored Procedures Your Agent Can Step Through

Workflows live in workflows/ in your stash. Each workflow is a markdown file with frontmatter declaring the procedure's parameters and a standard step format. You write the workflow once; the agent follows it on every run.

Here's what a release workflow looks like:

---
description: Ship a production release
params:
  version: "The version to release (e.g. 1.2.3)"
---
# Workflow: Ship Release

## Step: Validate inputs
Step ID: validate
### Instructions
Check that version follows semver and that the release branch exists.
### Completion Criteria
- Version matches x.y.z
- Branch release/{{ version }} exists

## Step: Build
Step ID: build
### Instructions
Run `bun run build` and verify dist/ was generated.

## Step: Deploy to staging
Step ID: staging
### Instructions
Run `./scripts/deploy.sh staging` and verify the health check passes.

## Step: Deploy to production
Step ID: production
### Instructions
Run `./scripts/deploy.sh production` after staging health check is green.

Enter fullscreen mode Exit fullscreen mode

The workflow defines the procedure. To run it, the agent creates a run — an instance of that procedure with a specific set of params:

akm workflow start workflow:ship-release --params '{"version":"1.2.3"}'
# Returns a run ID: run-abc123

Enter fullscreen mode Exit fullscreen mode

Now the procedure has state. The agent calls akm workflow next to get the current actionable step:

akm workflow next workflow:ship-release
# Returns: Step "validate" — Check that version follows semver...

Enter fullscreen mode Exit fullscreen mode

When the agent completes a step, it marks it done with notes:

akm workflow complete run-abc123 --step validate --state completed --notes "Version 1.2.3, branch release/1.2.3 confirmed"

Enter fullscreen mode Exit fullscreen mode

--state defaults to completed when omitted, so the --state completed above is redundant but explicit.

And the next call to akm workflow next returns the following step. The run persists independently of the conversation. If the session ends, a new agent picks up exactly where the previous one left off:

akm workflow next workflow:ship-release
# Returns: Step "build" — still in progress from the interrupted session

Enter fullscreen mode Exit fullscreen mode

Want to see the full state of a run?

akm workflow status run-abc123

Enter fullscreen mode Exit fullscreen mode

workflow status also accepts a workflow ref directly, resolving to the most-recently-updated run:

akm workflow status workflow:ship-release

Enter fullscreen mode Exit fullscreen mode

That shows each step with its status and any notes the agent recorded. You can list all active runs:

akm workflow list --active

Enter fullscreen mode Exit fullscreen mode

The procedure is now auditable. You know which step failed, when, and what the agent noted. You can hand the run off to a different agent or a different developer. The state is outside the context window where it's durable.

If you need a starting point, akm workflow template prints a starter workflow doc you can adapt.

Resuming blocked or failed runs

Sometimes a run gets blocked — a step requires human input, an external dependency is unavailable, or a tool call fails. When that happens, the run transitions to blocked or failed. Use workflow resume to flip it back to active without discarding progress:

akm workflow resume run-abc123

Enter fullscreen mode Exit fullscreen mode

Completed runs cannot be resumed. Use workflow list to find runs by status.

Vault Assets: The Agent Knows What It Needs, Not What the Values Are

Procedures that touch production environments need secrets — database URLs, API keys, deploy tokens. Putting those secrets in a skill file or a prompt is an obvious problem. But the agent still needs to know which secrets a given procedure requires.

Vault assets solve this. A vault is a .env file stored in vaults/ in your stash. The design has one rule: values are never surfaced in structured output. The agent can inspect a vault and learn what keys exist. It never sees what those keys are set to.

akm vault show vault:production
# Returns: { keys: ["DATABASE_URL", "API_KEY", "DEPLOY_TARGET"], comments: {...} }

Enter fullscreen mode Exit fullscreen mode

This is enough for the agent to confirm "yes, the right secrets are configured for this environment" without the secrets appearing anywhere in the conversation or the context window.

When a script actually needs the values — at runtime, not at planning time — the agent emits a shell source snippet:

source <(akm vault load vault:production)
./deploy.sh

Enter fullscreen mode Exit fullscreen mode

The values are loaded into the shell environment for the subprocess. They never pass through the agent's text output. The agent's conversation log is clean.

Combined with a workflow, this fits naturally into an environment verification step. The agent calls akm vault show vault:production to confirm all required keys are present, marks the step complete, then later calls akm vault load vault:production in the shell command that actually needs the secrets. The workflow knows what's required. The agent confirms it. The shell gets what it needs.

Writable Git Stash: Your Skills Sync Like Code

So far in this series, stashes have been read-only: you pull in a team repo or a remote source, and akm indexes it. In 0.5.0, a stash can be writable.

When you create a stash with --writable, akm save will stage, commit, and push your changes back to the remote:

akm add git@github.com:your-org/skills.git --provider git --name team-skills --writable

Enter fullscreen mode Exit fullscreen mode

# After editing or adding an asset
akm save team-skills -m "Add deploy workflow"

Enter fullscreen mode Exit fullscreen mode

The behavior depends on the stash configuration:

State What happens
Not a git repo Skipped
Git repo, no remote Stage and commit only
Git repo, has remote, writable: false Stage and commit only
Git repo, has remote, writable: true Stage, commit, and push

Your default stash — the one akm init creates — is auto-initialized as a local git repo. So by default, akm save gives you a commit history of every change you've made to your skill collection, without requiring a remote. Add a remote and flip writable: true when you're ready to sync across machines.

This changes how you think about managing your personal stash. It's not a pile of files in ~/.akm. It's a versioned repository. You can see when you wrote a skill, what it looked like before you changed it, and whether your teammates have made updates since you last pulled.

How These Three Features Work Together

Consider a deployment procedure that a team runs regularly. Before 0.5.0, you'd write a deploy skill and hope the agent followed the steps in the right order. With 0.5.0:

Step 1: Write the workflow once.

akm workflow create ship-release
# Edit workflows/ship-release.md with your team's exact steps

Enter fullscreen mode Exit fullscreen mode

Step 2: Add a vault with the production secrets.

The vault file lives at vaults/production.env in your stash. The keys are there; the values are managed separately through whatever secret management you use.

Step 3: Save both to the team stash.

akm save team-skills -m "Add ship-release workflow and production vault"

Enter fullscreen mode Exit fullscreen mode

Every developer on the team pulls the update with akm update --all. Now everyone has the same workflow and the same vault definition.

Step 4: When it's time to deploy, the agent runs the procedure.

# Agent starts a run
akm workflow start workflow:ship-release --params '{"version":"2.0.0"}'

# Gets the first step
akm workflow next workflow:ship-release
# → "Validate inputs: confirm version and vault keys"

# Checks the vault without reading secrets
akm vault show vault:production
# → { keys: ["DATABASE_URL", "API_KEY", "DEPLOY_TARGET"] }

# Marks the step complete
akm workflow complete run-xyz --step validate --notes "All keys present"

# Gets the next step
akm workflow next workflow:ship-release
# → "Build: run bun run build..."

Enter fullscreen mode Exit fullscreen mode

If the session ends at the staging step, a fresh agent picks up with:

akm workflow next workflow:ship-release
# → "Deploy to staging" — still pending from the previous session

Enter fullscreen mode Exit fullscreen mode

No context reconstruction. No "where did we leave off?" The procedure state is in the workflow run, not the conversation.

When the deploy is done, commit any skill or workflow improvements back to the team repo:

akm save team-skills -m "Improve staging health check step"

Enter fullscreen mode Exit fullscreen mode

The team gets the improvement on next akm update.

Getting Started

If you're on akm already, upgrade to the latest version:

npm install -g akm-cli@latest
# or
akm upgrade

Enter fullscreen mode Exit fullscreen mode

To try workflows:

akm workflow template
# Copy the output to workflows/your-first-workflow.md and edit it
akm workflow create your-first-workflow
akm workflow start workflow:your-first-workflow

Enter fullscreen mode Exit fullscreen mode

To add a vault, drop a .env file in vaults/ in your stash. The format is standard .env — one KEY=value per line, comments with #.

To make your default stash writable, add a remote to the git repo in ~/.akm/stash and update your stash config with --writable. Run akm save -m "Initial commit" to verify it pushes.

The repo is at github.com/itlackey/akm. The Getting Started guide covers initial setup if you're coming in new.

Agents are most useful when they can handle real work end-to-end. Real work usually involves multiple steps, sensitive configuration, and sessions that get interrupted. Workflows, vaults, and a writable stash close those gaps. Give them a try on the next multi-step task you'd normally hand off with a checklist.