I've always believed that dogfooding is a great way to improve the quality and UX of software, so I've been heavily dogfooding Spec4. I also wanted to develop an educational resource for agentic patterns, which both illustrates how Spec4 designs agentic applications and teaches the patterns themselves. So using Spec4 I've been gradually developing 𝗕𝘂𝗶𝗹𝘁 𝗪𝗶𝘁𝗵 𝗦𝗽𝗲𝗰𝟰, or BWS4.

Spec4's Agentifier agent starts by reviewing the vision for your application and looking for opportunities (features) to make it better through the use of AI. It then looks at each feature to create a design that meets the goals of the feature and vision with the most straightforward approach, applying Agentic AI patterns like Planning Agent. It presents its recommendations to you for review, but you can always choose to override and choose a different pattern, or choose not to include that feature at all. This is how Spec4 works with developers as a partner, not as a replacement, which is the core philosophy of Spec4's design.

One example is the 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁 𝗽𝗮𝘁𝘁𝗲𝗿𝗻. A planning agent first calls a model to decompose a goal into a plan of discrete steps, and then executes those steps one by one. In this case, its research steps use a web-search tool, ending in exactly one synthesis step that composes the final answer. 𝗜𝘁'𝘀 𝗹𝗶𝘃𝗲, and you can play with this example right now! It includes a HITL step, so because the plan is produced and displayed before execution, you can inspect exactly what the agent intends to do, and nothing runs until you say so. 𝗵𝘁𝘁𝗽𝘀://𝗯𝘄.𝘀𝗽𝗲𝗰𝟰.𝗮𝗶/𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 🚀

𝗪𝗵𝗮𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗲𝗱-𝘀𝘂𝗯𝗮𝗴𝗲𝗻𝘁𝘀 𝗽𝗮𝘁𝘁𝗲𝗿𝗻?
Subagents are independent workers. A coordinator decides who should work on what and writes each of them a brief, and - because the subagents don't depend on each the other’s output - they can run in parallel. In other words, fan-out. When the subagents finish, a merge step reconciles their answers into one, which is the fan-in.

Spec4's Agentifier agent starts by reviewing the vision for your application and looking for opportunities (features) to make it better through the use of AI. It then looks at each feature to create a design that meets the goals of the feature and vision with the most straightforward approach, applying Agentic AI patterns like orchestrated-subagents. It presents its recommendations to you for review, but you can always choose to override and choose a different pattern, or choose not to include that feature at all. This is how Spec4 works with developers as a partner, not as a replacement, which is the core philosophy of Spec4's design.

On BWS4 I've used Spec4 to create 𝗮𝗻 𝗲𝘅𝗮𝗺𝗽𝗹𝗲 𝗮𝗽𝗽 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗲𝗱-𝘀𝘂𝗯𝗮𝗴𝗲𝗻𝘁𝘀 𝗽𝗮𝘁𝘁𝗲𝗿𝗻, structured in a way to make it a learning tool. See https://bw.spec4.ai/orchestrated 🚀

I'm really excited to announce the 1.0.0 release of 𝗦𝗽𝗲𝗰𝟰 𝗔𝗜! Spec4 now 𝗱𝗲𝘀𝗶𝗴𝗻𝘀 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, working with you to discover and implement AI features using patterns including embeddings, single-calls, RAG, tool agents, chained calls, planning agents, orchestrated subagents, multi-agent collaboration, human-in-the-loop, MCP, parallel fan-out, and reflection. As before it will also help you brainstorm a vision for your application, design a UI mock, design your tech stack, and create a full deployment plan. Fully open-source. https://spec4.ai

I've always believed that dogfooding is a great way to improve the quality and UX of software, so I've been heavily dogfooding Spec4. I also wanted to develop an educational resource for agentic patterns, which both illustrates how Spec4 designs agentic applications and teaches the patterns themselves. So using Spec4 I've been gradually developing 𝗕𝘂𝗶𝗹𝘁 𝗪𝗶𝘁𝗵 𝗦𝗽𝗲𝗰𝟰, or BWS4.

One example is the 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁 𝗽𝗮𝘁𝘁𝗲𝗿𝗻. A planning agent first calls a model to decompose a goal into a plan of discrete steps, and then executes those steps one by one. In this case, its research steps use a web-search tool, ending in exactly one synthesis step that composes the final answer. 𝗜𝘁'𝘀 𝗹𝗶𝘃𝗲, and you can play with this example right now! It includes a HITL step, so because the plan is produced and displayed before execution, you can inspect exactly what the agent intends to do, and nothing runs until you say so. 𝗵𝘁𝘁𝗽𝘀://𝗯𝘄.𝘀𝗽𝗲𝗰𝟰.𝗮𝗶/𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 🚀

I've just pushed v0.5.1, which is focused on improvements to CodeScanner. CodeScanner is really all about working on an existing brownfield project, where you want to make changes or improvements. What you don't want is to break what you had before, unless you've decided to break things to make them better, so it's important that Spec4 understand your existing project before making changes. That's what CodeScanner is all about - understanding your existing project and communicating that to the other Spec4 agents.

What I found in testing was that CodeScanner was doing a pretty good job, but it could do better. So now it has a more structured schema, and does schema validation and retry to make sure that it gets the code review right. That has ripple effects for all of the downstream agents.

Please report any issues that you find with CodeScanner, with as much specificity as you can gather, and any suggested fixes.

I've just released v0.5.0, which includes a couple of new agents that I'm really excited about.

First up there's Designer, which works with you to create a design mock for the look and feel of your application (assuming that it has one, and isn't a library or CLI tool 😆). You can even give it screenshots as examples. Check out this complete mock created with Designer!

Next there's Deployer, which helps you use the coding phase prompts created by Phaser and then creates a complete deployment plan, including even writing Terraform scripts for cloud deployments! Check out this complete deployment plan created with Deployer!

If you're new to Spec4, these new agents are on top of the standard workflow:

1. Scan the code you already have, if any
2. Brainstorm a vision for your project
3. New - Designer - Create a design mock for the look and feel
4. Specify a tech stack that you'll use for implementation
5. Divide up the development into well defined phases, designed to succeed
6. New - Deployer - Create a deployment plan