You don't write prompts. You author intent. Save, search and share your AI chat history with SpecStory.
Joined January 2025
- Tweets 55
- Following 17
- Followers 263
- Likes 73
Pinned Tweet
100,000+ devs. 4 million AI chats saved with SpecStory. Ready to join them?
h/t to @HamelHusain, @aronchick, @TaylorJHolland, @JnBrymn for ongoing support
SpecStory retweeted
people heavily using ai coding tools to build and implement serious stuff should seriously use @specstoryai to save those conversations.
those conversations capture so much around decision-making process, implementation details, and reasoning.
SpecStory retweeted
SpecFlow changed how I build with AI agents. Huge thanks to the @specstoryai team, @isaac_flath, and @intellectronica for introducing me to this game-changing workflow. 🚀
specflow.com/getting-started…
We had a chat with @mitchell, the creator of Ghostty, about what it’s really like maintaining an open source project in the age of AI
He’s reviewed hundreds of AI-generated pull requests, and his takeaway is simple but powerful
“Open source doesn’t have an AI problem. It has a transparency problem.”
In our conversation, Mitchell shared:
- How Ghostty now requires contributors to disclose when they’ve used AI
- The rise of “AI code slop” and what separates good-faith contributors from noise
- He’s also thinking beyond Git, about what version control might look like when code is co-written by humans and AI
It’s part of a quiet shift in open source: AI isn’t replacing contributors, it’s testing how transparent we’re willing to be about our process.
Full story below👇
SpecStory retweeted
Thanks to our friends at @specstoryai for collaborating with us! 🤝
As AI coding tools are becoming a natural part of every developer’s workflow, open source collaboration is evolving too
We teamed up with the amazing folks at @digitalocean to publish a new guide:
"How to Be an Open Source Hero: Contributing AI-Generated Code with Care"
In it, we explore:
- How to use AI coding tools responsibly in open source projects
- Best practices for contributors and maintainers
- When and how to disclose AI-assisted code
- Real-world examples of ethical, transparent collaboration
Aim is to make open source development more inclusive, transparent, and future-ready together. ✨
Read the full article here: digitalocean.com/community/t…
As AI coding tools are becoming a natural part of every developer’s workflow, open source collaboration is evolving too
We teamed up with the amazing folks at @digitalocean to publish a new guide:
"How to Be an Open Source Hero: Contributing AI-Generated Code with Care"
In it, we explore:
- How to use AI coding tools responsibly in open source projects
- Best practices for contributors and maintainers
- When and how to disclose AI-assisted code
- Real-world examples of ethical, transparent collaboration
Aim is to make open source development more inclusive, transparent, and future-ready together. ✨
SpecStory retweeted
I've seen some interesting ideas in this vein. It's not chatting, but one of them is @specstoryai (specstory.com/). They're working on extracting information from the context you generate while using a coding agent. I believe the purpose is to work on the next "artifact" beyond code.
For this sort of stuff, I get a lot of value out of drawing pictures in particular. This was a paper / tool from a while ago that I think is a very interesting approach:
x.com/ryanyen22/status/19002…
I haven't been able to follow up on it, but a (drawing, writing) -> generating -> (drawing, writing) workflow seems ideal.
SpecStory retweeted
i've been doing similar stuff combining several things along with @specstoryai to "auto-document" the initial grind and then produce steps
x.com/matijagrcic/status/192…
what i find the most valuable is the documentation produced, even if you don't need everything, you'll find nuggets you can apply to your problems.
The best part I leveraged @specstoryai and instructed the agent to write instructions . md which I now just drop in any @lovable_dev project and agent does all so it takes like 2mins.
SpecStory retweeted
未来的代码评审（Code Review）可能不再是看代码本身，而是看你和 AI 的聊天记录。AI 就像一个编译器，把你的自然语言（Spec）编译成代码。我们 review 的是意图，而不是机器码。
这个趋势下，一个叫 @specstoryai 的产品思路很有趣。
🚀 SpecStory now supports Codex CLI
One of the most requested features by our users is finally here:
You can now auto-save every OpenAI Codex terminal session to structured Markdown in .specstory/history.
What’s new:
- Official support for Codex CLI in SpecStory CLI v0.11.0+
- `specstory run codex` launches Codex with automatic session capture
- Sessions can be saved in clean, git-friendly Markdown (prompts, tool calls, code, timestamps)
- Optional cloud sync if you want global search & sharing across projects
How it add values:
- 🔁 Reproducibility: Re-run agent work with full context (not just diffs)
- 📝 Reviews: Share the why behind code for faster reviews and onboarding
- 🛡️Resilience: Treat agent output as a durable record you can search, reuse, and learn from
Your Codex sessions now won't vanish, instead will stay as lasting context.
Hacktoberfest by @digitalocean has kicked off 🎉
Thousands of developers will be diving into open source, contributing code, and learning in public.
But this year, there’s something new in the mix: AI-assisted coding is everywhere
It makes contributing to repos easier than ever, but also easier to overwhelm maintainers with low-context contributions.
For contributors, AI can help you explore unfamiliar codebases, draft faster, and learn by example.
For maintainers, it can also mean extra review work if the context and reasoning behind the code are missing.
That’s why responsible AI use in open source matters:
- Disclose if you used AI, and how.
- Share your process (yes, even the messy parts)
- Leverage AI to understand the code that you are about to submit
- Check the quality yourself before submitting
Transparency builds trust. And trust is what keeps open source sustainable.
We put together a guide on how to contribute AI-generated code with care for both contributors and maintainers. Read below 👇
AI has made it possible to build faster than ever. We type a prompt, generate the code, iterate until it works, and move on.
But speed has a cost: the reasoning behind the code disappears. Weeks or months later, the context is gone, nobody remembers:
- Why a decision was made
- Why was it built this way
- What alternatives were tried
- How false starts shaped the design
That context is as important as the code itself.
SpecStory captures those details automatically. It preserves the conversation history that built the code: the “why” that usually vanishes once the tab is closed. That history isn’t just a transcript, it’s structured memory that users can reuse.
One of our user, @isaac_flath, discovered this firsthand. His SpecStory logs didn’t just capture the final output, they preserved the messy process: the failed examples, the back-and-forth reasoning, the design debates. That history became the outline for his blog post. He didn’t have to reconstruct his thinking from scratch, it was already there in the conversation.
Read the full story below 👇
Never lose your AI coding chats💥
SpecStory automatically captures every AI-assisted chat and prompt as local Markdown - instantly searchable, version-controlled, and shareable with your team.
- Revisit decisions weeks later and understand the reasoning behind a code/feature change
- Debug faster by tracing how a solution evolved across prompts
- Review PRs with context and see the exact conversation that led to the code.
🎥 Here’s a quick demo: see how SpecStory captures your Cursor sessions right into .specstory/history/ so the reasoning lives alongside your commits.
👉 Works today in VS Code with Copilot, Cursor, and Claude Code.
SpecStory retweeted
Vibe Coding is shifting fast.
From ❓“Why won’t AI understand me?” → ➡️“Treat it like a junior dev.” → 🚀“We’re architecting AI systems.”
I tested @specstoryai 10k-Reddit posts insights from dev forums by VibeCoding a presentation app.
👉 Slides: simple-slide-presenter-qaf8u…
Software development is undergoing a meaningful shift.
Traditionally, the act of building software was often judged by its output: PR commits, features shipped, tickets closed, etc. But anyone who’s built systems knows the real work has always been reasoning through tradeoffs, constraints, and design choices.
That picture is now changing. AI coding tools are making it easier than ever to generate code. The real challenge isn’t code generation. It’s clarity: deciding what to build, why it matters, and how it should behave. In other words, defining the requirements rather than writing the syntax. And that shift changes how we think about building software.
And that’s not just a product manager’s job anymore. Every role now influences the product in meaningful ways. Engineers make product decisions when they choose performance over simplicity. Designers shape the product when they adjust flows that reduce friction. SREs and infra teams define the product when they set standards for reliability and scalability. Even support and customer success teams contribute when they bring forward constraints from real users.
The future of software development will not be defined by code alone. It will be defined by the conversations, the decisions, and how clearly we capture and communicate the requirements.
