from nieceandtows@programming.dev to programming@programming.dev on 31 May 06:15
https://programming.dev/post/51247328
I use speckit, and while I like the spec/clarify/plan/task/analyze/implement loop (although it can get a bit overwhelming at times), I don’t like that I have to start with writing a spec and implement it to begin with. I am looking for a more of a design phase before the spec phase, where I can talk about the overall application architecture, and then start writing specs for implementing pieces of it.
For instance, let’s say I want to build a github repo provisioner that 1. creates repos with desired setup, and 2. bulk edit repos with secret updates, yaml updates, etc. I don’t want to build both the features at the beginning. I want to first build only the create portion, and then do the bulk edit feature later on. With speckit, I can do this by only telling it to create the spec for the build portion, but later if I want to build the bulk edit portion, the whole application might need to be changed in important places, because it wasn’t a ‘planned’ feature when it was first designed. I want instead to have a design phase where I describe and maintain a doc with the whole application, and when I start the spec for the create portion, the agent can understand that this create portion is only part of a bigger application and can design/implement the create portion accordingly.
Have you come across a situation like this? how do you handle your big applications? Please advise.
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For the fellow community members who are not up to date with the latest AI
BStrends:It is ‘leava all coding to agents’, but at least it’s ‘leave most of the design control to me’. I was, and still am, and old style programmer yelling at AI to get off my lawn, but like any new technology, I’m trying to do my best to learn and make best use of it so that I grow as a developer even though it is meant to ‘save money for the company’. It’s here whether I like it or not, so I’making sure I don’t lose my job because of it, while still being employable when it inevitably crashes to the ground.
Lemmy might not be a good place to ask about AI unfortunately. Most people here HATE it.
I’m 100% with you on this. I don’t love AI but I’m not going to let myself be pushed out of the field by people who cannot program, just because I don’t like something new.
Openspec has an “explore” command you can use to give some thoughts and have agent spit out a high level plan, some back and forth, then create the proposal once you’re happy. I’ve also generated markdown documentation for a subsystem or thought so I can check it in, then continue improving that later, then when ready to turn it into a proposal and implement I start by referencing that document.
It sounds like a big part of what you’re talking about is just pre-feeding future concerns into one proposal for work that you plan to do in the future, also nothing wrong with that. I’ve used “in the future we will need … so design in that direction without implementing in this first iteration” sort of wording.
And not sure if this applies but I’ve found big monolithic code bases become too large for AI to work well in… enforcing some boundaries by breaking code into technical foundation and vertical slice functional modules really helps decouple code and focus on cross-module boundaries and interfaces, similarly to how they help reduce cognitive load for developers, helps for AI too
How is open spec for Greenfield apps? I’ve heard it’s best suited for existing code. I’ll try the ‘in the future’ heads up, thanks
It works pretty well for greenfield, that’s where I’ve been using it. A pretty involved monorepo with a decent bit of code and things are still going reasonably well.
Also, leaning on documents as deliverable artifacts for people and for AI awareness / consumption helps me.
Like put together an architecture document for either the entire application or specific parts and subsystems (or multiple documents with different granularity) those can list future considerations.
I pretty often will include those documents when generating proposals / specs to make sure the AI is building in the right direction. It’s not perfect, there are some rough edges and these are the early days of this whole process.
Spec driven development is a scam.
At least it’s better than just asking the agent to build something without any control over it, which is what a lot of junior devs are doing these days.
I suggest you design the core bits of your project, actually fucking program it yourself, see what works and what doesn’t, review design, and repeat. (This is a programming community.)
I have 18 years of programming experience, this is not about not knowing how to code. It’s about using a new technology effectively without losing your identity as a senior programmer. May be you have the ultimate say in your company, and can stave off agentic coding until the bubble bursts, but I don’t have that luxury. Agentic coding has fucked up all output velocity expectations, so even if you don’t use them, you’re still expected to output at the new velocity, which would just about kill mj love for programming.
I’m not familiar with the tool you’re using and my big, traditionally written projects have largely been organically grown over the years as unpredictable requirements change – mostly I just try to keep things readable enough that I can jump back in when I need to do so on old projects…
It sounds like you want to incorporate LLMs into brainstorming though. Maybe try using the word “elicitation” in your prompts for early phases? e.g. “ROLE: Requirements Elicitation Specialist” or “ROLE: Architecture Design Elicitation Specialist”. You can also meta-prompt to get a system prompt tailored to your specific needs.
Superpowers has brainstorming
Note that the current version injects a lot into the system prompt, and it’s always on. If you using Claude Code, install it in a second profile, so that you choose when to use it. I exploring its features now.
github.com/obra/superpowers
The Basic Workflow
brainstorming - Activates before writing code. Refines rough ideas through questions, explores alternatives, presents design in sections for validation. Saves design document.
using-git-worktrees - Activates after design approval. Creates isolated workspace on new branch, runs project setup, verifies clean test baseline.
writing-plans - Activates with approved design. Breaks work into bite-sized tasks (2-5 minutes each). Every task has exact file paths, complete code, verification steps.
subagent-driven-development or executing-plans - Activates with plan. Dispatches fresh subagent per task with two-stage review (spec compliance, then code quality), or executes in batches with human checkpoints.
test-driven-development - Activates during implementation. Enforces RED-GREEN-REFACTOR: write failing test, watch it fail, write minimal code, watch it pass, commit. Deletes code written before tests.
requesting-code-review - Activates between tasks. Reviews against plan, reports issues by severity. Critical issues block progress.
finishing-a-development-branch - Activates when tasks complete. Verifies tests, presents options (merge/PR/keep/discard), cleans up worktree.
The agent checks for relevant skills before any task. Mandatory workflows, not suggestions.