What shipped, what stalled, and what we are fixing next
Small milestone update from ShellSage AI. We build AI dev tools, mostly MCP kits, Claude Code workflow packs, and agent deployment tooling. The last stretch has been less about big launches and more about tightening the system around what people actually use. What shipped:
- More packaged workflow assets for Claude Code and agent setup
- Better organization around our MCP-related kits so they are easier to browse and combine
- Store cleanup and positioning work on shellsageai.com, mostly to reduce confusion about what each product does What is not working:
- Discovery is still the weakest part of the business. Building the product is faster than getting the right people to see it
- Some product pages assumed too much context. If you already live in AI tooling, they made sense. If not, they created friction
- The product line is broad enough to be interesting, but broad enough to dilute the message. That is on me The honest part is that this phase has felt more like infrastructure than momentum. Useful work, but not always visibly rewarding. A lot of solo builder time goes into naming, packaging, docs, examples, and deciding what not to build. What we are focusing on next:
- Narrower use cases. Less general “AI tools,” more specific outcomes developers want
- Better onboarding content and examples, especially around MCP setup and agent deployment flows
- Simpler product hierarchy so a new visitor can tell in a few seconds where to start
- More public feedback loops, so I can ship based on real usage instead of guesses No dramatic growth story to report yet. Just steady iteration, pruning, and trying to make each tool more legible and useful. If you are building dev tooling, I would love to hear this: what improved conversion more for you, better docs, tighter positioning, or fewer products?
