Spec Kit: Github's NEW tool That FINALLY Fixes AI Coding — Transcript
Full transcript
- 0:00Think about the last time you asked an
- 0:02AI tool to write code. It probably gave
- 0:05you something that looked correct but
- 0:07didn't quite work. That's where vibe
- 0:09coding falls short. But it might not be
- 0:12a problem with the particular model
- 0:13you're using. It's most likely because
- 0:16of lack of specification clarity. That
- 0:18is where specdriven development comes to
- 0:21rescue. GitHub just released a new
- 0:23open-source toolkit called SpecKit,
- 0:26which completely changes the game. Today
- 0:28we're going to look at SpecKit, see how
- 0:30it works, and I will show you a little
- 0:32demo how to use it, and we'll find out
- 0:35if this is really the future of coding.
- 0:40In traditional development, you write
- 0:41code, then document what it does. In
- 0:44specdriven development, you do the
- 0:47opposite. You write a specification, a
- 0:49living executable artifact, and that
- 0:52spec defines what you intend to build.
- 0:54From there, all stakeholders and AI
- 0:57tools align around the same source of
- 0:59truth. This approach closes the gaps
- 1:01between intent and implementation and
- 1:04leads to cleaner, safer, and more
- 1:06reliable code. The main idea is that
- 1:09language models are great at patterns,
- 1:11but not so great at reading your mind.
- 1:14Broad prompts like, "Add photo sharing
- 1:16to my app," leaves the AI guessing
- 1:19thousands of details, most of which
- 1:21never match your real intent. Specdriven
- 1:24development eliminates that guesswork.
- 1:26It gives AI clear structured guidance so
- 1:29it builds exactly what you want. Few
- 1:31months ago, Amazon launched Kira, which
- 1:34was the first framework to really focus
- 1:36on specdriven development. And James did
- 1:38an excellent deep dive on that in a
- 1:40separate video if you want to check it
- 1:41out here. But now there's a new player
- 1:43in town, SpecKit. It is GitHub's
- 1:46open-source toolkit for specd driven
- 1:48development with AI coding agents. It
- 1:51features a CLI tool, templates, and
- 1:55steering prompts designed to work with
- 1:57tools like GitHub Code Pilot, Claude
- 1:59Code, and Gemini CLI. It aims to
- 2:02transform your ad hoc prompting into a
- 2:05structured, verifiable development
- 2:06workflow. Here's how it works. Specit
- 2:09organizes your development into four
- 2:11gated phases, each with a validation
- 2:14checkpoint before moving forward. The
- 2:16first phase is specify. This is where
- 2:18you describe what you want to build and
- 2:20why focusing on user journeys and
- 2:23outcomes. The AI agent uses that to
- 2:26generate a detailed spec which also
- 2:28evolves as your understanding grows. The
- 2:31second phase is plan. This phase defines
- 2:33the stack and architectural constraints.
- 2:36You tell the agent your specifications
- 2:38and it constructs a technical plan that
- 2:40honors those constraints. Third phase is
- 2:43tasks. This is where the spec and plan
- 2:46is broken down into small actionable
- 2:48tasks. This gives you manageable
- 2:50testable units that AI can implement one
- 2:52by one. And the fourth phase is
- 2:54implement. This is where AI tackles
- 2:57tasks incrementally. You can review each
- 3:00change before implementation instead of
- 3:02running bulky code dumps. That way the
- 3:04model knows what to build, how to build
- 3:07it, and where to focus. You can verify
- 3:09and refine this at each step. It gives
- 3:12you total granular control over
- 3:14execution. This toolkit was born out of
- 3:16frustration with the coding models
- 3:18behaving like a search engine instead of
- 3:20a literal-minded pair programmer. At its
- 3:23core, it's a shift towards intent as the
- 3:26source of truth. Instead of code, the
- 3:29spec becomes the authorative artifact
- 3:31and the models constantly circle back to
- 3:34the spec document for guidance on how to
- 3:36proceed. So now I'm going to show you
- 3:38with a little project how we can use
- 3:40specit in our own projects. To kick
- 3:42things off, you just need to run this
- 3:44command in your terminal specifying your
- 3:46project name and then choose which
- 3:49agentic framework to use. In this demo,
- 3:51I will be using GitHub copilot. The kit
- 3:54will initialize all the necessary files
- 3:56for your project and then you can
- 3:57proceed to open the workspace in your
- 4:00code editor. The first thing you will
- 4:01see when you open the code editor is
- 4:03that specit has created this script
- 4:05folder and templates folder. And these
- 4:08are just boilerplate spec templates
- 4:10which are used to generate your actual
- 4:12spec files. And the scripts are the ones
- 4:14that execute and prepare those
- 4:16documents. We don't have to change
- 4:17anything here. We can just go ahead and
- 4:19prepare our project by typing specify
- 4:22followed by our prompt. This initial
- 4:24prompt should be an overall description
- 4:26of your project. what the goal is, what
- 4:28the basic features are, and maybe even
- 4:30describe what a simple user journey
- 4:32looks like. In this example, I will be
- 4:34creating a simple Pokedex team builder
- 4:37where I can search for Pokemon and add
- 4:39them to my team. I will also be using
- 4:41Gro Code Fast one as the base model for
- 4:44this project. So, let's go ahead and run
- 4:46the command. And once that's done, you
- 4:48will see that specit has created a new
- 4:51branch for this development and it has
- 4:53also created a spec markdown file. In
- 4:56this file, we see that the model has
- 4:58successfully understood the assignment
- 5:00and created a primary user story along
- 5:03with acceptance scenarios. I also like
- 5:06that it thinks about edge cases as well
- 5:08and other potential roadblocks. And
- 5:10whenever the model comes to a situation
- 5:12where it can't decide on a path forward,
- 5:15it will add this block titled needs
- 5:17clarification. So you can specify the
- 5:20requirements yourself. And we can also
- 5:22see here that it has crafted some
- 5:23functional requirements and key entities
- 5:26as well. Honestly, this is super cool
- 5:28because I would be too lazy to write out
- 5:30all these specifics for the model to
- 5:32follow. So, it's good that spec kit is
- 5:35able to guide the model to craft all of
- 5:37this for us. And remember, if you ever
- 5:40need to change something here or decide
- 5:42on a totally different direction to
- 5:44take, this is the file where you can
- 5:46make those edits. But if we're happy
- 5:48with the spec file, next we can proceed
- 5:50to the plan phase. And here we should
- 5:52more concretely describe the tech stack
- 5:54of our application along with other
- 5:56details that we deem necessary. Here I
- 5:59just pasted in some basic technical
- 6:01requirements for the project along with
- 6:03some other helpful commands like using a
- 6:06debounce on the Pokemon search endpoint
- 6:08so we don't overwhelm the API. And once
- 6:10you're happy with all of that, let's
- 6:12execute the plan command. And you can
- 6:14see here that specit gets more detailed.
- 6:17It adds a data model and a research
- 6:19document as well as contracts for the
- 6:22object types which is super cool. And in
- 6:25the data model file, it even crafted a
- 6:28zod schema object. But I really love the
- 6:30research document because here we can
- 6:32see the ration behind the model choosing
- 6:35specific frameworks and it also gives us
- 6:38explanations about its reasoning along
- 6:40with other considerations for
- 6:42alternative solutions and it also
- 6:44respects the text stack choices you give
- 6:47it plus it tries to think of other
- 6:49necessities which you might not have
- 6:51considered as well. So that is really
- 6:54powerful. So then we move on to the plan
- 6:56file which has laid out all the
- 6:58development phases in concrete steps and
- 7:00it has also ticked the ones that are
- 7:03already completed. This all looks very
- 7:05good to me. So now we can move on to the
- 7:07next phase, the task execution phase.
- 7:10Now we already have the spec and plan in
- 7:12place. So for the tasks command, we can
- 7:14just start by asking the model to create
- 7:16an MVP version of our project. And this
- 7:19is where the magic happens. SpecKit will
- 7:22now create a very detailed tasks list
- 7:25which outlines step by step what we need
- 7:27to do to get to our development goal.
- 7:30Let's open up the tasks list. And we can
- 7:32see here that it has given every task a
- 7:34unique number. And that keeps everything
- 7:37well and organized. So you can execute
- 7:39tasks in order and review them as you
- 7:42go. I see here that tasks one to four
- 7:44are dedicated to setting up the
- 7:46environment. So let's go ahead and ask
- 7:48the model to execute those. There is no
- 7:51slash command for this phase, but as I
- 7:53understand the recommended way to
- 7:55proceed is to write implement followed
- 7:58by the task numbers to tell the model
- 8:00which tasks to execute at the specific
- 8:02given command. So first let's run the
- 8:04setup tasks so you can also keep track
- 8:06of the progress. So from here on out
- 8:08it's a very free flow approach of just
- 8:11asking the model which tasks to
- 8:13implement and then just following along,
- 8:15seeing the progress and iterating on the
- 8:17process. And once they're done, we can
- 8:20see that the model has also ticked them
- 8:22as completed. I noticed that in this
- 8:24particular template that they have, it
- 8:26very much likes the test-driven
- 8:28development approach where it writes the
- 8:30tests first and then implements the
- 8:32features. You can probably change that
- 8:33in the spec or the plan if you want to
- 8:36go for a different development approach.
- 8:38So after a few commands and iterations,
- 8:40my model has finished implementing all
- 8:42of the tasks. And here's the result. As
- 8:45you can see, we have a nice little
- 8:47functioning Pokedex where I can search
- 8:49for any Pokemon and add them to my team.
- 8:52The API seems to be working perfectly.
- 8:54And the project also looks very clean.
- 8:57It uses Chats and UI elements as I
- 9:00prompted it to do. And by the looks of
- 9:02everything, it's very well and
- 9:04functional. So, there you have it. We
- 9:06just vibecoded a nice little web project
- 9:08using SpecKit. I hope by now you see how
- 9:11this meticulous specdriven development
- 9:14approach can help improve the AI model's
- 9:16ability to craft a cleaner, more refined
- 9:19code. It also gives you more precision
- 9:21to steer the model in the direction you
- 9:24want to go. And I do have to mention
- 9:26that although SpecKit is designed to
- 9:28work with most of the coding models, the
- 9:30choice of the coding model still makes a
- 9:33difference. While testing out this tool,
- 9:35I also tried scaffolding a project using
- 9:37GPT4.1
- 9:39and it didn't give me as good of a
- 9:41result as when I used the Grock model.
- 9:43So, choosing the right coding model is
- 9:45still necessary to achieve the best
- 9:47results. It's clear that specdriven
- 9:49development is a paradigm we'll be
- 9:51seeing much more of in the future of
- 9:53coding. But what are your thoughts about
- 9:55specit? Are you using specdriven
- 9:58development in your coding practices?
- 10:00Let us know in the comments down below.
- 10:02And folks, if you like these types of
- 10:04technical breakdowns, let us know by
- 10:06smashing that like button underneath the
- 10:08video. And also, don't forget to
- 10:10subscribe to our channel for more videos
- 10:12like this one. This has been Andress
- 10:14from Better Stack, and I will see you in
- 10:16the next videos.
- 10:20[Music]
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