guys, we built a +1 you can bring to work 👀
Meet Tag: your personal assistant, in Slack. (not co-worker)
When @karpathy described Claude Tag as “significantly more ‘inline’ with all the other human activity org-wide,” the word “inline” stood out to me.
To me, that’s the interesting shift. You’re not leaving the work to go talk to AI. Your AI joins you where the work is happening.
Few months ago, I found out Slack literally stands for "Searchable Log of All Conversation and Knowledge." Instantly, I realise it is a pretty good place for an assistant to start.
If your team already works there, you’ve already discussed the problem, shared the links, and explained why the last idea didn’t work.
Why copy that context into a private AI chat, work through the answer alone, then paste everything back for your team?
With Tag, you mention your assistant in the thread. Ask it to investigate a question, turn the discussion into a plan, or work on a file. It uses the thread as context and brings the result back into the conversation.
But here’s the thing: working together shouldn’t mean everyone has to share one assistant.
Your Tag is yours. You choose its tools, skills, and connected accounts. Your teammates can each bring their own Tag, while everyone contributes to the discussion and follows the work.
It runs on a computer you control. We don’t host your conversations or working file, so your setup still uses Slack and OpenAI, rather than being fully offline.
Tag is also free and open source. It works with the Codex access you already have through ChatGPT, so there’s no extra Tag subscription.
I think the best place to work together with AI is where you’re already working together.
You bring your assistant. Your teammates bring theirs.
Bring your +1 to work.
→ https://t.co/YgRYBhbifK
@ansh_chokshi I wish we could build one in our country, but unfortunately, the data infrastructure is not there. @kemdigital_gov
Congratulations on empowering your country!
introducing land search and enrich api + mcp
billions of real world data points, structured for agents to make decisions.
now your agents can:
> find matching land across 160M+ parcels.
> filter and rerank using 550 available data fields.
> compare assets using structured data with sources.
fetch, our location data api, got 4M+ calls. and we just made it completely free.
built for agent speed and scale. dirt cheap.
sign up and get $10 for free: https://t.co/acQmRkYcdx
Trillions are pouring into the race to build the first general superintelligence, but leveraging your own specialized know-it-all is now possible as of today.
I built the knowledge systems at @stripe and @uber. Then I helped Anthropic, Metronome, and Graphite build a killer developer experience. Everyone wants Stripe-level quality, but that bar is too low.
Falconer gives you and your customers complete, specialized intelligence: an internal knowledge base and external documentation in one beautiful package. Falconer is the ultimate trust engine to manage your context: self-driving, observable, and agent-friendly.
I co-founded @falconer_ai with @mbenedetto212 and assembled a team of know-it-all builders. We're backed by fellow know-it-alls @thegp, @BoxGroup, @svangel, @karimatiyeh, @benln, @zachlloydtweets, @CeciStalls, @MerrillLutsky, @scottmac, @malthe, and @adamjstevenson, with angels from Anthropic, Stripe, Meta, Cursor, Replit, and more.
Frontier intelligence companies like @FireworksAI_HQ and @⬛⬛⬛⬛⬛⬛; fintech companies like @payabli and @vori; and healthtech companies like @thatch_ai use @falconer_ai because they all share the same vision as us: the knowledge you earn should belong to you.
Now you can know everything, so you can build anything.
@transitive_bs few months ago they were using claude tag to ship claude code desktop, but i guess they move back to dogfooding since the release of claude projects etc. (hopefully