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

SecWiki News
SecWiki News
量子位
The Cloudflare Blog
美团技术团队
T
The Exploit Database - CXSecurity.com
博客园 - 【当耐特】
Spread Privacy
Spread Privacy
P
Proofpoint News Feed
C
CXSECURITY Database RSS Feed - CXSecurity.com
博客园 - 三生石上(FineUI控件)
T
Tor Project blog
博客园 - 司徒正美
宝玉的分享
宝玉的分享
T
Threatpost
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
S
Secure Thoughts
T
Threat Research - Cisco Blogs
Hacker News: Ask HN
Hacker News: Ask HN
Jina AI
Jina AI
博客园 - 聂微东
A
Arctic Wolf
I
Intezer
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Know Your Adversary
Know Your Adversary
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
爱范儿
爱范儿
Hugging Face - Blog
Hugging Face - Blog
C
Cyber Attacks, Cyber Crime and Cyber Security
小众软件
小众软件
T
Tailwind CSS Blog
The Hacker News
The Hacker News
L
LINUX DO - 最新话题
Hacker News - Newest:
Hacker News - Newest: "LLM"
WordPress大学
WordPress大学
S
SegmentFault 最新的问题
TaoSecurity Blog
TaoSecurity Blog
Project Zero
Project Zero
博客园 - 叶小钗
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Cloudbric
Cloudbric
雷峰网
雷峰网
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
大猫的无限游戏
大猫的无限游戏
D
Darknet – Hacking Tools, Hacker News & Cyber Security
T
Troy Hunt's Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
V2EX - 技术
V2EX - 技术
The GitHub Blog
The GitHub Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
P
Privacy & Cybersecurity Law Blog

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? My AI workflow evolved from prompts to a near-autonomous workflow MLSharp Help - 3DGS Viewer & Generator I put my cognitive field based AI's runtime on GitHub Is Numble the first AI-proof game? A3: Kubernetes for autonomous AI agent fleets | Emergent Principles Deepali Vyas ("The Elite Recruiter") GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Unionized ProPublica staff are on strike over AI, layoffs, and wages Unleashing the Advantage of Quantum AI We're heading for an AI-fueled 'dementia crisis,' brain scientist warns The AI-Assisted Breach of Mexico's Government Infrastructure [pdf] GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
GitHub - pssah4/digital-innovation-agents: Digital Innovation Agents is an AI-augmented workflow that connects business analysis and software engineering in one consistent skill set.
pssah4 · 2026-06-01 · via Hacker News - Newest: "AI"

When code costs almost nothing, the plan becomes the product.

A V-Model workflow that walks your AI coding assistant through Business Analysis, Requirements Engineering, Architecture, Coding, Testing, and a Security Audit, with quality-gated handoffs between every phase.

Full documentation: pssah4.github.io/digital-innovation-agents

Shipping code is a solved problem. What most teams still lack is evidence that the features they ship matter to a real user. Digital Innovation Agents pair a battle-tested innovation methodology with a state-of-the-art coding workflow, so your AI never builds the wrong thing at speed. Works across Claude Code, Cursor, Codex, OpenCode, Gemini CLI, and GitHub Copilot.

V-Model workflow for AI coding assistants: six phases (Business analysis, Requirements engineering, Architecture, Coding, Testing, Security audit) plus a Closing handoff. Two consistency buses run beneath the phases: BACKLOG.md as status source of truth and ARCHITECTURE.map as code source of truth. Four dashed feedback loops show test fix, mid-course discovery, security fix, and living-documents writeback.


What this is

The project ships thirteen skills that run inside your AI coding assistant. Six are V-Model phase skills (business analysis, requirements engineering, architecture, coding, testing, security audit). Two are entry-point skills for non-greenfield projects (reverse engineering, dia-migration). One is the on-demand workflow guide (/dia-guide). Four are foundation skills (project conventions, consistency check, humanizer, dia-bootstrap). Every phase skill owns one part of the V-Model, has its own quality gates, and hands off a structured artifact to the next phase. The guide is called separately whenever the user wants an orientation read. Every decision stays traceable from a real user problem through requirements, architecture, code, tests, and a security audit.

Three entry points cover greenfield, brownfield, and migration projects:

  • Greenfield: /business-analysis starts with structured discovery (users, needs, insights, critical hypotheses) and walks forward through the V-Model.
  • Brownfield: /reverse-engineering walks the V backwards over an existing codebase and produces plan-context, ADRs, an arc42 snapshot, a FEATURE inventory, a backlog seed, and an evidence-based BA draft. Every claim is sourced to a file path or doc section. Nothing invented.
  • Migration: /dia-migration brings an older DIA project (v1) or a pre-existing V-Model variant up to current conventions: cleans status drift, normalises ID schemas, flattens analysis/, regenerates the backlog as single source of truth.

Innovation methodology, not just automation

The BA and RE agents ship a catalog of 32 innovation methods (qualitative interviews, extreme users, fly on the wall, cultural probes, persona synthesis, stakeholder maps, jobs to be done, brainwriting, TRIZ, wizard of oz, pre-mortem, value proposition quantification, and more) organised as method cards in the docs.

During a BA or RE session, when your answers go thin, the agent stops the interview and proposes the matching field method with a one-page card: what it produces, when to reach for it, how to run it, team and time, things that go wrong, and what to bring back to the session. The actual research work stays human-to-human: interviews with real users, observations in the real context, prototypes on real hands. The agent's job is to spot the gap and pick the right method, not to replace the work.

Quick start

Pick your platform. Each installer drops the same thirteen skills with the same templates and quality gates into your tool of choice.

Claude Code (recommended)

/plugin lives in the Claude Code CLI, not in the VS Code or JetBrains extensions. If claude --version returns command not found, install the CLI first:

curl -fsSL https://claude.ai/install.sh | bash    # official installer
# or: brew install --cask claude-code              # macOS Homebrew
# or: npm install -g @anthropic-ai/claude-code     # any OS with Node

Reopen your shell (source ~/.zshrc or ~/.bashrc), then install the plugin:

/plugin marketplace add https://github.com/pssah4/digital-innovation-agents.git
/plugin install digital-innovation-agents@pssah4-skills

Type / in any new session to see the skills in autocomplete. The dia-bootstrap skill loads automatically at session start as a brief orientation.

VS Code, JetBrains, and Cursor extensions cannot install plugins. Running /plugin marketplace add ... inside the VS Code Claude Code extension returns /plugin isn't available in this environment. Install once through the CLI as above. The skills land under ~/.claude/skills/ and the IDE extension picks them up from the same global directory on the next session start. On Windows without WSL, the CLI is experimental; install through WSL or copy the manually:

The manual install copies the complete plugin bundle (skills, tools, hooks, scripts) under a stable path and symlinks the skills into ~/.claude/skills/. Skills invoke tooling at ${DIA_PLUGIN_ROOT}/tools/..., so DIA_PLUGIN_ROOT is exported from the install location. Re-run the block to update; it pulls the latest commit and rewrites the bundle in place. Skills renamed or removed in newer DIA versions (for example dia-orchestrator from v2) are deleted explicitly so no stale skill folders survive the upgrade.

# Stable plugin location. Override with DIA_PLUGIN_ROOT env if needed.
DIA_PLUGIN_ROOT="${DIA_PLUGIN_ROOT:-$HOME/.local/share/dia-plugin}"

# Clone or update the plugin bundle
if [ -d "$DIA_PLUGIN_ROOT/.git" ]; then
  git -C "$DIA_PLUGIN_ROOT" fetch --tags --prune
  git -C "$DIA_PLUGIN_ROOT" reset --hard origin/main
else
  mkdir -p "$(dirname "$DIA_PLUGIN_ROOT")"
  rm -rf "$DIA_PLUGIN_ROOT"
  git clone https://github.com/pssah4/digital-innovation-agents.git "$DIA_PLUGIN_ROOT"
fi

mkdir -p ~/.claude/skills

# Remove legacy DIA skills that were renamed or dropped
for legacy in dia-orchestrator; do
  rm -rf "$HOME/.claude/skills/$legacy"
done

# Symlink the current DIA skill set (covers future renames automatically)
for skill in project-conventions reverse-engineering business-analysis \
             requirements-engineering architecture coding testing \
             security-audit consistency-check humanizer dia-guide \
             dia-migration dia-setup dia-bootstrap; do
  rm -rf "$HOME/.claude/skills/$skill"
  ln -sfn "$DIA_PLUGIN_ROOT/skills/$skill" "$HOME/.claude/skills/$skill"
done

# Persist DIA_PLUGIN_ROOT so skills can resolve tools/ at runtime
shell_rc="$HOME/.zshrc"
[ -f "$HOME/.bashrc" ] && shell_rc="$HOME/.bashrc"
if ! grep -q "DIA_PLUGIN_ROOT=" "$shell_rc" 2>/dev/null; then
  echo "export DIA_PLUGIN_ROOT=\"$DIA_PLUGIN_ROOT\"" >> "$shell_rc"
fi
export DIA_PLUGIN_ROOT

After the first install, open a new shell so DIA_PLUGIN_ROOT is set, then start claude. Skills resolve their helper scripts at $DIA_PLUGIN_ROOT/tools/... regardless of the user-project cwd.

Cursor

/add-plugin digital-innovation-agents

Or search for "digital-innovation-agents" in the Cursor plugin marketplace.

GitHub Copilot (CLI and VS Code)

GitHub Copilot has no marketplace command. Install by copying the .github/ directory plus the helper tools into your project. The agents call flow.py, anchor.py, the migration scripts, and the consistency check, so tools/ and scripts/ must be available locally.

Re-run the block to update; the source checkout is pulled to the latest commit and each target subfolder is wiped before copy, so no stale Copilot agents, chat modes, or helper scripts survive an upgrade.

# Clone or update the source checkout
if [ -d /tmp/dia/.git ]; then
  git -C /tmp/dia fetch --tags --prune
  git -C /tmp/dia reset --hard origin/main
else
  rm -rf /tmp/dia
  git clone https://github.com/pssah4/digital-innovation-agents.git /tmp/dia
fi

mkdir -p .github

# Wipe old DIA copies before installing the current set
for sub in agents chatmodes instructions templates; do
  rm -rf ".github/$sub"
  cp -r "/tmp/dia/.github/$sub" ".github/$sub"
done
cp /tmp/dia/.github/copilot-instructions.md .github/copilot-instructions.md

# Install the helper tools (flow.py, anchor.py, migration, hooks)
# at the project root so the agents can invoke them
for sub in tools scripts hooks; do
  rm -rf "$sub"
  cp -r "/tmp/dia/$sub" "$sub"
done

# Skills resolve tools/ relative to the project root in this layout,
# so DIA_PLUGIN_ROOT points at the project itself
echo 'export DIA_PLUGIN_ROOT="$(pwd)"' >> .envrc 2>/dev/null || true

The Copilot install brings the helper tools into the project rather than to a global location because Copilot agents run with the project as their working directory and have no plugin-bundle path to fall back on.

Copilot Chat picks the agents up automatically on the next session. In Copilot Chat:

@business-analyst I want to build a tool that helps teams run better retrospectives
@requirements-engineer Here is my BA document, create epics and features
@architect Design the architecture based on the requirements handoff
@developer Implement the first feature
@debugger Tests are failing, analyze the error log

The Copilot agents run the same Exploration / Ideation / Validation cycle, the same templates, and the same quality gates as the Claude Code skills.

Codex

Tell Codex:

Fetch and follow instructions from https://raw.githubusercontent.com/pssah4/digital-innovation-agents/main/.codex/INSTALL.md

Detailed docs: .codex/INSTALL.md

OpenCode

Tell OpenCode:

Fetch and follow instructions from https://raw.githubusercontent.com/pssah4/digital-innovation-agents/main/.opencode/INSTALL.md

Detailed docs: .opencode/INSTALL.md

Gemini CLI

gemini extensions install https://github.com/pssah4/digital-innovation-agents

To update:

gemini extensions update digital-innovation-agents

Verify the install

Start a session in your chosen platform and try one of these:

/dia-setup                 Activate the workflow in this project
/dia-guide                 Full guided cycle from idea to security audit
/business-analysis         Start a structured business analysis
/reverse-engineering       Brownfield entry for an existing codebase

/dia-setup is the first call in any new project. It asks for the mode (off, git-only, or github-sync), writes .dia/config.toml, and adds a managed anchor block to your existing CLAUDE.md, AGENTS.md, GEMINI.md, .cursorrules, or similar agent files. Re-run any time to change the mode or remove the anchor.

Or ask a natural-language question like "help me analyse this business problem". The agent should invoke the matching skill.

Troubleshooting:

  • Claude Code or Cursor: restart the session, the SessionStart hook loads the skill overview automatically.
  • Codex: verify the symlink with ls -la ~/.agents/skills/digital-innovation-agents.
  • OpenCode: check logs with opencode run --print-logs "hello" 2>&1 | grep -i digital-innovation.
  • Gemini CLI: run gemini extensions list.

The skills

The thirteen skills split into three groups: V-Model phase skills (the ten that own a phase or move you between phases), foundation skills (rules and consistency), and the orientation skill (using-digital- innovation-agents loads on session start to introduce the workflow).

V-Model phase skills

Phase What it does Claude Code Copilot
Reverse Engineering Brownfield entry. Walks the V backwards over an existing codebase and produces plan-context, ADRs, arc42, FEATURE inventory, backlog seed, and an evidence-based BA draft with every claim sourced. /reverse-engineering @reverse-engineer
DIA Migration Migrates a v1 project, an older V-Model variant, or a brownfield repo to current DIA conventions. Idempotent, branch-safe, no source-code edits. /dia-migration built-in
Business Analysis Exploration, Ideation, and Validation cycle with structured interviews, probing techniques, and the 32-method discovery catalog. /business-analysis @business-analyst
Requirements Engineering Epics, FEAT-EE-FF features, tech-agnostic success criteria, user stories across functional / emotional / social levels, critical hypotheses. /requirements-engineering @requirements-engineer
Architecture ADRs in MADR format with the abstraction rule (no code paths in core sections), arc42 snapshot, wayfinder maintenance, plan-context bridge to implementation. /architecture @architect
Coding Context handoff, critical review against the real codebase, PLAN-NN persistence with coverage gate, bug-capture entry, artifact writeback during implementation. /coding @developer
Testing Unit and integration tests with the AAA pattern, FIRST principles, coverage targets, and a fix-loop until green. /testing built-in
Security Audit OWASP Top 10, LLM Top 10, SAST, SCA, Zero Trust review with a fix-loop. Two modes: per-item audit and periodic full-codebase audit. /security-audit @security-auditor
V-Model Workflow Guide On-demand orientation: reads project state, audits the latest handoff entry, recommends the next phase skill, and emits the Closing Handoff after a green security audit. The guide does not perform CRUD or drive transitions; phase skills are autonomous. /dia-guide built-in
Debugging Root-cause analysis, systematic error resolution, causal chain documentation. Bugs land as FIX-EE-FF-NN rows in the backlog plus detail files in _devprocess/requirements/fixes/. default agent @debugger

Foundation skills

Skill What it does Claude Code
Project Conventions Three-layer documentation model (Wayfinder, Rule sets, Backlog, Detail artifacts), directory structure, naming standards, writing-style rules. /project-conventions
Consistency Check Verifies the V-Model artifact graph: dead links, orphan features, status drift, missing references. Modes A (syntactic), B (semantic), C (full). Mandatory at every phase boundary. /consistency-check
Humanizer Strips AI vocabulary, em dashes, negative parallelisms, and filler from every artifact. Enforces sentence case and active voice. /humanizer
DIA Bootstrap Loads automatically on session start. Carries the entry-point catalog, helper-script path resolution rule, activation contract, opt-out behaviour. Not invoked manually. dia-bootstrap

Scope levels

The skills adapt their depth to your project scope. Match the tier to the size of the question.

Scope Exploration Ideation Validation Typical duration
Simple Test Minimal (user and problem) Describe the solution Skip Hours to 1-2 days
Proof of Concept Shortened (user, needs, HMW) Full Hypotheses and feasibility 1-4 weeks
MVP Full 10-section Exploration board Full Full market assessment 2-6 months

A Simple Test does not need a stakeholder map. An MVP does not get away without one.

Tech-agnostic requirements

Success Criteria stay free of technology vocabulary. No OAuth, REST, PostgreSQL, or React in the contract between the user and the team. Technical details live in a separate Technical NFRs section and in the ADRs that follow in /architecture. See the Tech-agnostic Requirements page in the docs for the full ruleset.

Living documents

ADRs, features, architecture docs, and the backlog update continuously during implementation. At release time, documentation reflects what was actually built, not what was originally planned. The _devprocess/context/BACKLOG.md file is the single source of truth for project state, and every phase skill touches it in the same edit pass as the code it affects.

Design principles

  1. Understand the problem before designing the solution.
  2. Separate what the system does (user-observable, tech-free) from how it does it (ADRs, NFRs).
  3. Propose the right research method instead of grinding through a question list when your answers go thin.
  4. No phase proceeds until its quality gate is met.
  5. Every agent reads the real codebase before producing output. The project's CLAUDE.md always takes precedence over generic skill instructions.

Documentation

Every guide, tutorial, concept page, and method card lives at pssah4.github.io/digital-innovation-agents.

Start here:

Versions

Version Status Install
v3 (main) Active, recommended. Three-layer documentation model, FEAT-EE-FF IDs, FIX/IMP detail files, PLAN-NN persistence, GitHub flow.py integration, subtype-aware Done-definition. See Quick start above
v2.x Frozen snapshot, no longer maintained git clone --branch v2.4.0 https://github.com/pssah4/digital-innovation-agents.git
v1.0.0 Frozen snapshot, no longer maintained git clone --branch v1.0.0 https://github.com/pssah4/digital-innovation-agents.git

See CHANGELOG.md for details. Existing v1 or v2 projects upgrade through /dia-migration. v1 and v2 are historical snapshots and not actively maintained; for current behaviour use the marketplace or platform-specific install on v3.

License

MIT License. Copyright (c) 2025 Sebastian Hanke. See LICENSE.

Acknowledgments

Built with:

  • Claude Code Skills, Claude Agent SDK, and GitHub Copilot Agents
  • Innovation methodology from design thinking and lean startup practice
  • Jobs-to-be-Done framework
  • arc42 architecture documentation template
  • MADR (Markdown Architectural Decision Records)
  • OWASP Top 10 and LLM Top 10
  • AAA pattern and FIRST principles for testing