Posted by etoxin 10 hours ago
In my experience, spec drift is the main reason why none of these tools work. Maybe they work for one shot greenfield feature generation but in a large, multi developer long lived code bases, specs rot and end up being more pain than they are worth.
I use this skill and it makes the specing process progressive. Human driven for the "what", 50/50 for higher level technical planning, only where it has questions in the low level details: https://github.com/scosman/vibe-crafting
This is absolutely not true
feels less like planning and more like throwing spaghetti at the wall the moment ambiguity emerges, I really hope the next batch dials it back
OpenCode and various open models do not exhibit this tendency nearly as much in my experience. My recent experiences with GPT-5.6 were also very positive in this regard. Alas for regulatory reasons this stack is a non-starter at $DAYJOB so I'm stuck working around Anthropic's capacity optimizing shenanigans.
I also ended up doing my own thing mainly to address several omissions in the existing frameworks (for SDD I prefer to use Superpowers and/or Matt Pocock's skills):
1. Artifact staleness and tracking - if you have a structure around starting with something like an ADR, common patterns for the whole repo etc., it's super hard to keep track of and actually keep it up to date. You make a strong early decision in an ADR and realize that you have to change it later on, or diverge. These changes get rarely properly recorded.
2. Review loop - Same model review isn't enough, I want bunch of models bouncing off each other, whilst still using my subscription and not API.
3. Feature creep and deferral tracking - it happens a lot that you encounter either during review or one of the validation phases that you also need to implement x, which is not covered by the original spec. There are several options to handle that, with the key that all those decisions need to be tracked and at some point decided by a human.
4. Custom workflow with governance - I have my own preferred SDLC if you can call it that, which includes rounds of agentic review of spec, before manual approval gate, review loop with certain specification depending on the codebase, feature size, deferral rules.
5. Ceremony based on context - Because it would happen that some of the ceremony would get in the way at some points (like producing a 100+ loc spec for 10loc change) I ended up basically developing a flow to decide whether a feature actually needs the full ceremony (full lane) or we can simply use the native plan feature (fast lane), so that I don't have to go through the whole ordeal of steps, when I need a tiny change.
I forked this code and added bits that matched my flow and it works out pretty well https://github.com/nutthouse/tutti
If you like this / SDD, I'd appreciate your feedback:
https://github.com/spekk-ai/spekk-cli
Similar iterative specs philosophy. Ours is a bit different because we focus on declarative specs and installable agent skills. We chose Go for simplicity and minimal requirements (single binary).
Ive wondered if I have too much complexity, and from time to time I do a "prompt astrology reset" where I get rid of all the extra cruft. I can't go without the spec sheets though.
On removing cruft: one of the key features of spekk is an "observer" agent role that is tasked with finding drift. On a production codebase, I run this daily in a sandbox. It pulls the latest changes and looks for specs that are mismatched from the implementation, preferring to look at specs and code that changed recently and prioritizing "major" drift events. The observer agent then opens a PR wkth its observations (markdown with YAML like the specs). It also posts a summary to Slack, but that's optional. The sandbox agent code is part of the spekk-cli codebase.
It's also worth noting that SDD is such a wide variety of approaches that the term on its own says very little. For example, SpecKit and SpecDD are both very capable SDD frameworks, yet they have only minimal overlap: SpecDD describes system components (with emphasis on boundaries), while SpecKit is a fairly advanced process for changing specs.
Also, this looks like something which leadership level folks need to adopt first and then somehow it needs to trickle down to PI planning and sprint planning. Would like to hear someone's experience on how this has got adopted in their org.
Basically the flow proposal -> design -> specs -> tasks gives you and AI a method to build context on what you want to achieve. In a way you're just creating a plan/big prompt that is structured in such a way that they start stacking on each other.
The power is that you do a lot of upfront thinking. In my team we then share it with a colleague who will review it through a PR. After that implementation is usually hands off. At the end there is a skill to verify the change against specs. I do still review the code myself too.
I guess if you work in a task oriented environment this will not work as well, as you'd lack/don't care about the business context. I'd like to think that most software development does not happen like this, but is done by engineers who actually understand why something is needed and take that into account when designing and building the solution.
This is the best part of this spec, but we have found from our experience that though upfront thinking changes has a lot of merits and adds clarity and alignment upfront, but it changes bit by bit in every meeting and before you know your specs are not aligned with general consensus in the team. If your team is large enough, then it gets very difficult to own the task of constructing alignment between your principal-artifacts and your evolved under-current of understanding.
If you check my submissions (https://news.ycombinator.com/submitted?id=gps372), I have written whole set of articles on the myths of how easy it is keep the understanding consistent.
I would still say that if you are working on a platform and if your engg team size if anything more than 25-30, then this spec must be adopted from top-down and not bottoms up. Bottom level engineers usually don't have the level of consistent exposures (as and when they socialize and evangelize their platform) which top level engineers have.
Please note that I can already see that github repo has 68k+ stars. So popularity is not in question, just the viability and consistency of adoption across different scenarios.
Last week, I gave a 471 line spec to implement a major feature and it didn’t flinch. I wrote about it here.
https://jaisenmathai.com/articles/sojourn-for-ios-was-45-one...
i find a small, human written spec to be much more effective than these large spec documents.
the idea is that you iterate with your agent to write the spec, you implement, then eventually that spec gets merged into a "spec corpus" that describes all the behavior of the repository. but i don't think that prose can ever enumerate all the behaviors required of code, nor should it. the spec almost immediately becomes out of date.
Either ways, we're open to feedback and I'm happy to have a conversation. Feel free to email me at tabish@openspec.dev to set something up.