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Spec Kit: Github's NEW tool That FINALLY Fixes AI Coding — Transcript

by Better Stack · 1,827 words · 269 segments · language en · Watch on YouTube

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  1. 0:00Think about the last time you asked an
  2. 0:02AI tool to write code. It probably gave
  3. 0:05you something that looked correct but
  4. 0:07didn't quite work. That's where vibe
  5. 0:09coding falls short. But it might not be
  6. 0:12a problem with the particular model
  7. 0:13you're using. It's most likely because
  8. 0:16of lack of specification clarity. That
  9. 0:18is where specdriven development comes to
  10. 0:21rescue. GitHub just released a new
  11. 0:23open-source toolkit called SpecKit,
  12. 0:26which completely changes the game. Today
  13. 0:28we're going to look at SpecKit, see how
  14. 0:30it works, and I will show you a little
  15. 0:32demo how to use it, and we'll find out
  16. 0:35if this is really the future of coding.
  17. 0:40In traditional development, you write
  18. 0:41code, then document what it does. In
  19. 0:44specdriven development, you do the
  20. 0:47opposite. You write a specification, a
  21. 0:49living executable artifact, and that
  22. 0:52spec defines what you intend to build.
  23. 0:54From there, all stakeholders and AI
  24. 0:57tools align around the same source of
  25. 0:59truth. This approach closes the gaps
  26. 1:01between intent and implementation and
  27. 1:04leads to cleaner, safer, and more
  28. 1:06reliable code. The main idea is that
  29. 1:09language models are great at patterns,
  30. 1:11but not so great at reading your mind.
  31. 1:14Broad prompts like, "Add photo sharing
  32. 1:16to my app," leaves the AI guessing
  33. 1:19thousands of details, most of which
  34. 1:21never match your real intent. Specdriven
  35. 1:24development eliminates that guesswork.
  36. 1:26It gives AI clear structured guidance so
  37. 1:29it builds exactly what you want. Few
  38. 1:31months ago, Amazon launched Kira, which
  39. 1:34was the first framework to really focus
  40. 1:36on specdriven development. And James did
  41. 1:38an excellent deep dive on that in a
  42. 1:40separate video if you want to check it
  43. 1:41out here. But now there's a new player
  44. 1:43in town, SpecKit. It is GitHub's
  45. 1:46open-source toolkit for specd driven
  46. 1:48development with AI coding agents. It
  47. 1:51features a CLI tool, templates, and
  48. 1:55steering prompts designed to work with
  49. 1:57tools like GitHub Code Pilot, Claude
  50. 1:59Code, and Gemini CLI. It aims to
  51. 2:02transform your ad hoc prompting into a
  52. 2:05structured, verifiable development
  53. 2:06workflow. Here's how it works. Specit
  54. 2:09organizes your development into four
  55. 2:11gated phases, each with a validation
  56. 2:14checkpoint before moving forward. The
  57. 2:16first phase is specify. This is where
  58. 2:18you describe what you want to build and
  59. 2:20why focusing on user journeys and
  60. 2:23outcomes. The AI agent uses that to
  61. 2:26generate a detailed spec which also
  62. 2:28evolves as your understanding grows. The
  63. 2:31second phase is plan. This phase defines
  64. 2:33the stack and architectural constraints.
  65. 2:36You tell the agent your specifications
  66. 2:38and it constructs a technical plan that
  67. 2:40honors those constraints. Third phase is
  68. 2:43tasks. This is where the spec and plan
  69. 2:46is broken down into small actionable
  70. 2:48tasks. This gives you manageable
  71. 2:50testable units that AI can implement one
  72. 2:52by one. And the fourth phase is
  73. 2:54implement. This is where AI tackles
  74. 2:57tasks incrementally. You can review each
  75. 3:00change before implementation instead of
  76. 3:02running bulky code dumps. That way the
  77. 3:04model knows what to build, how to build
  78. 3:07it, and where to focus. You can verify
  79. 3:09and refine this at each step. It gives
  80. 3:12you total granular control over
  81. 3:14execution. This toolkit was born out of
  82. 3:16frustration with the coding models
  83. 3:18behaving like a search engine instead of
  84. 3:20a literal-minded pair programmer. At its
  85. 3:23core, it's a shift towards intent as the
  86. 3:26source of truth. Instead of code, the
  87. 3:29spec becomes the authorative artifact
  88. 3:31and the models constantly circle back to
  89. 3:34the spec document for guidance on how to
  90. 3:36proceed. So now I'm going to show you
  91. 3:38with a little project how we can use
  92. 3:40specit in our own projects. To kick
  93. 3:42things off, you just need to run this
  94. 3:44command in your terminal specifying your
  95. 3:46project name and then choose which
  96. 3:49agentic framework to use. In this demo,
  97. 3:51I will be using GitHub copilot. The kit
  98. 3:54will initialize all the necessary files
  99. 3:56for your project and then you can
  100. 3:57proceed to open the workspace in your
  101. 4:00code editor. The first thing you will
  102. 4:01see when you open the code editor is
  103. 4:03that specit has created this script
  104. 4:05folder and templates folder. And these
  105. 4:08are just boilerplate spec templates
  106. 4:10which are used to generate your actual
  107. 4:12spec files. And the scripts are the ones
  108. 4:14that execute and prepare those
  109. 4:16documents. We don't have to change
  110. 4:17anything here. We can just go ahead and
  111. 4:19prepare our project by typing specify
  112. 4:22followed by our prompt. This initial
  113. 4:24prompt should be an overall description
  114. 4:26of your project. what the goal is, what
  115. 4:28the basic features are, and maybe even
  116. 4:30describe what a simple user journey
  117. 4:32looks like. In this example, I will be
  118. 4:34creating a simple Pokedex team builder
  119. 4:37where I can search for Pokemon and add
  120. 4:39them to my team. I will also be using
  121. 4:41Gro Code Fast one as the base model for
  122. 4:44this project. So, let's go ahead and run
  123. 4:46the command. And once that's done, you
  124. 4:48will see that specit has created a new
  125. 4:51branch for this development and it has
  126. 4:53also created a spec markdown file. In
  127. 4:56this file, we see that the model has
  128. 4:58successfully understood the assignment
  129. 5:00and created a primary user story along
  130. 5:03with acceptance scenarios. I also like
  131. 5:06that it thinks about edge cases as well
  132. 5:08and other potential roadblocks. And
  133. 5:10whenever the model comes to a situation
  134. 5:12where it can't decide on a path forward,
  135. 5:15it will add this block titled needs
  136. 5:17clarification. So you can specify the
  137. 5:20requirements yourself. And we can also
  138. 5:22see here that it has crafted some
  139. 5:23functional requirements and key entities
  140. 5:26as well. Honestly, this is super cool
  141. 5:28because I would be too lazy to write out
  142. 5:30all these specifics for the model to
  143. 5:32follow. So, it's good that spec kit is
  144. 5:35able to guide the model to craft all of
  145. 5:37this for us. And remember, if you ever
  146. 5:40need to change something here or decide
  147. 5:42on a totally different direction to
  148. 5:44take, this is the file where you can
  149. 5:46make those edits. But if we're happy
  150. 5:48with the spec file, next we can proceed
  151. 5:50to the plan phase. And here we should
  152. 5:52more concretely describe the tech stack
  153. 5:54of our application along with other
  154. 5:56details that we deem necessary. Here I
  155. 5:59just pasted in some basic technical
  156. 6:01requirements for the project along with
  157. 6:03some other helpful commands like using a
  158. 6:06debounce on the Pokemon search endpoint
  159. 6:08so we don't overwhelm the API. And once
  160. 6:10you're happy with all of that, let's
  161. 6:12execute the plan command. And you can
  162. 6:14see here that specit gets more detailed.
  163. 6:17It adds a data model and a research
  164. 6:19document as well as contracts for the
  165. 6:22object types which is super cool. And in
  166. 6:25the data model file, it even crafted a
  167. 6:28zod schema object. But I really love the
  168. 6:30research document because here we can
  169. 6:32see the ration behind the model choosing
  170. 6:35specific frameworks and it also gives us
  171. 6:38explanations about its reasoning along
  172. 6:40with other considerations for
  173. 6:42alternative solutions and it also
  174. 6:44respects the text stack choices you give
  175. 6:47it plus it tries to think of other
  176. 6:49necessities which you might not have
  177. 6:51considered as well. So that is really
  178. 6:54powerful. So then we move on to the plan
  179. 6:56file which has laid out all the
  180. 6:58development phases in concrete steps and
  181. 7:00it has also ticked the ones that are
  182. 7:03already completed. This all looks very
  183. 7:05good to me. So now we can move on to the
  184. 7:07next phase, the task execution phase.
  185. 7:10Now we already have the spec and plan in
  186. 7:12place. So for the tasks command, we can
  187. 7:14just start by asking the model to create
  188. 7:16an MVP version of our project. And this
  189. 7:19is where the magic happens. SpecKit will
  190. 7:22now create a very detailed tasks list
  191. 7:25which outlines step by step what we need
  192. 7:27to do to get to our development goal.
  193. 7:30Let's open up the tasks list. And we can
  194. 7:32see here that it has given every task a
  195. 7:34unique number. And that keeps everything
  196. 7:37well and organized. So you can execute
  197. 7:39tasks in order and review them as you
  198. 7:42go. I see here that tasks one to four
  199. 7:44are dedicated to setting up the
  200. 7:46environment. So let's go ahead and ask
  201. 7:48the model to execute those. There is no
  202. 7:51slash command for this phase, but as I
  203. 7:53understand the recommended way to
  204. 7:55proceed is to write implement followed
  205. 7:58by the task numbers to tell the model
  206. 8:00which tasks to execute at the specific
  207. 8:02given command. So first let's run the
  208. 8:04setup tasks so you can also keep track
  209. 8:06of the progress. So from here on out
  210. 8:08it's a very free flow approach of just
  211. 8:11asking the model which tasks to
  212. 8:13implement and then just following along,
  213. 8:15seeing the progress and iterating on the
  214. 8:17process. And once they're done, we can
  215. 8:20see that the model has also ticked them
  216. 8:22as completed. I noticed that in this
  217. 8:24particular template that they have, it
  218. 8:26very much likes the test-driven
  219. 8:28development approach where it writes the
  220. 8:30tests first and then implements the
  221. 8:32features. You can probably change that
  222. 8:33in the spec or the plan if you want to
  223. 8:36go for a different development approach.
  224. 8:38So after a few commands and iterations,
  225. 8:40my model has finished implementing all
  226. 8:42of the tasks. And here's the result. As
  227. 8:45you can see, we have a nice little
  228. 8:47functioning Pokedex where I can search
  229. 8:49for any Pokemon and add them to my team.
  230. 8:52The API seems to be working perfectly.
  231. 8:54And the project also looks very clean.
  232. 8:57It uses Chats and UI elements as I
  233. 9:00prompted it to do. And by the looks of
  234. 9:02everything, it's very well and
  235. 9:04functional. So, there you have it. We
  236. 9:06just vibecoded a nice little web project
  237. 9:08using SpecKit. I hope by now you see how
  238. 9:11this meticulous specdriven development
  239. 9:14approach can help improve the AI model's
  240. 9:16ability to craft a cleaner, more refined
  241. 9:19code. It also gives you more precision
  242. 9:21to steer the model in the direction you
  243. 9:24want to go. And I do have to mention
  244. 9:26that although SpecKit is designed to
  245. 9:28work with most of the coding models, the
  246. 9:30choice of the coding model still makes a
  247. 9:33difference. While testing out this tool,
  248. 9:35I also tried scaffolding a project using
  249. 9:37GPT4.1
  250. 9:39and it didn't give me as good of a
  251. 9:41result as when I used the Grock model.
  252. 9:43So, choosing the right coding model is
  253. 9:45still necessary to achieve the best
  254. 9:47results. It's clear that specdriven
  255. 9:49development is a paradigm we'll be
  256. 9:51seeing much more of in the future of
  257. 9:53coding. But what are your thoughts about
  258. 9:55specit? Are you using specdriven
  259. 9:58development in your coding practices?
  260. 10:00Let us know in the comments down below.
  261. 10:02And folks, if you like these types of
  262. 10:04technical breakdowns, let us know by
  263. 10:06smashing that like button underneath the
  264. 10:08video. And also, don't forget to
  265. 10:10subscribe to our channel for more videos
  266. 10:12like this one. This has been Andress
  267. 10:14from Better Stack, and I will see you in
  268. 10:16the next videos.
  269. 10:20[Music]

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