What are people using for this nowadays? There seems to be a spectrum from fluid, iterative workflows like OpenSpec to more up-front alignment and control like Matt Pocock skills. Curious what people have settled on.
OpenSpec – A lightweight and configurable AI spec framework
51–60 of 74 posts
Re: OpenSpec – A lightweight and configurable AI spec framework
#52my org at work adopted openspec, and i strongly dislike it. every change, medium or larger, turns into a large set of multiple markdown documents, each that need review. and they are never handwritten - always slop, filled with the all the tells of ai writing, which i personally find grating. i find a small, human written spec to be much more effective than these large spec documents. the idea is that you iterate wit…
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.
Re: OpenSpec – A lightweight and configurable AI spec framework
#53Looks like this will be a hard sell for many orgs who are already struggling with explosion of artifacts on JIRA, sharepoint, github, etc. Also, most of them have somewhat settled on some ways (in past 6-8 months) to produce AI first specs and work with them. 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. W…
I use it at a much smaller scale. I think that's also the right place, because its a CLI tool + skills that generate md files. Not something you'd give to a business person. I start from a single ticket (sometimes just a handful of changes, but I want the spec as docs) to changes that you'd normally split over several tickets. Basically the flow proposal -> design -> specs -> tasks gives you and AI a method to build…
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.
Re: OpenSpec – A lightweight and configurable AI spec framework
#54Looks like this will be a hard sell for many orgs who are already struggling with explosion of artifacts on JIRA, sharepoint, github, etc. Also, most of them have somewhat settled on some ways (in past 6-8 months) to produce AI first specs and work with them. 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. W…
OpenSpec maintainer here. A lot of our adoption has mainly been bottoms-up, it's usually driven by engineers. That being said it definitely helps if everyone on the team uses it together. Especially when shifting left and doing a lot more "spec review".
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.
Re: OpenSpec – A lightweight and configurable AI spec framework
#55I 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
Re: OpenSpec – A lightweight and configurable AI spec framework
#56This looks like exactly what I've been thinking I needed. I've tried Superpowers, GSD and oh-my-claude/openagent and mostly they burn more tokens. Lately I've been using stock OMP and its close to the right balance but not quite enough of the brainstorming and spec maintenance built in. I've tried to layer some simple stuff on myself but with mixed results.
Re: OpenSpec – A lightweight and configurable AI spec framework
#57Re: OpenSpec – A lightweight and configurable AI spec framework
#58Haven’t we moved on from these things? Most recent LLMs have been trained on enough long context tasks to have become pretty good at planning. Perhaps with contributions from the harness. In either case, I wouldn’t bother if I were using Codex or Claude Code.
Re: OpenSpec – A lightweight and configurable AI spec framework
#59It'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.
Re: OpenSpec – A lightweight and configurable AI spec framework
#60This is my first time seeing openspec, and it seems to share a similar philosophy to what I've been working on this year. 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).
I did a similar thing. Yours seems cleaner than mine. I have a 'compiler' and a sexp based DSL. I don't know how anybody vibecodes medium or large programs, say above 50,000 lines of code. I don't read all the spec until I sense something is out of alignment. 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…
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.