@jack Absolutely, also not a lot of people focus on building on top of open weights models giving them that openai , anthropic app layer. So i decided to build @kairnsh to fix that
Theย CAF Appeal Board decided that in application of Article 84 of the Regulations of the CAF Africa Cup of Nations (AFCON), the Senegal National Team is declared to have forfeited the Final Match of the TotalEnergies CAF Africa Cup of Nations (AFCON) Morocco 2025 (โthe Matchโ), with the result of the Match being recorded as 3โ0 in favour of the Fรฉdรฉration Royale Marocaine de Football (FRMF).
https://t.co/QKDI0FCKug
10 years of corporate work taught me something most tech people get wrong about enterprises:
The main blocker of innovation isn't budget. It's not awareness. It's not resistance.
It's change management.
"If it works, leave it" โ that's not laziness. Big enterprises have mastered their systems. It might look broken from the inside, but from the outside? It works.
Except now the stakes have changed.
A company that deeply integrates AI vs. one that doesn't โ in a few years, the performance gap won't be incremental. It'll be day and night.
I spent the last 3 years going full throttle on AI. Built systems, automations, trained models. Startups, agencies โ I loved it.
But every time it came to enterprises, the same cycle played out:
"Wow, this is fascinating."
Then the integration nightmare.
Then the solution becomes an orphan in an ecosystem that rejects it.
Then the project dies quietly.
Every. Single. Time.
For a while I blamed the enterprises. Too slow. Too rigid.
Then I realized: the problem was never them. It was us.
The AI industry keeps asking enterprises to change everything for a technology that changes every 6 months.
So I stopped building and started listening.
How do enterprises actually want to work with AI โ not how the industry tells them they should?
The answer was always the same:
"Take what we have and make it smarter. Don't make us rebuild."
That was the breakthrough.
AI shouldn't replace what exists. It should make what exists intelligent.
Same APIs. Same backend. Same logic. But now users say what they need โ and the product acts.
That's Kairn. The agentic layer for existing products.
โ Soul โ how the agent behaves
โ Memory โ persistent context per user
โ Skills โ your APIs, now AI-invokable
โ Observability โ every action auditable
Zero change management. Zero migration.
short visual walkthrough below โ
๐ https://t.co/qbr0SY5O9F
Hot take: the next wave of AI products won't be built from scratch.
They'll be existing products that become agentic.
Your users won't click through 14 screens to upgrade a plan. They'll say "upgrade me and add 3 seats" โ and the product will do it.
But to get there, you need infrastructure:
โ A soul that defines agent behavior
โ Persistent memory across sessions
โ Skills that map to your real APIs
โ Full observability on every action
That's Kairn โ the agentic layer for existing products.
We put together a visual walkthrough of what this looks like in production โ
@topnotchvibe_@BusInsiderSSA Iโm building @kairnsh to help software companies turn existing products into agentic products without rebuilding their backend.
@benln Iโm working on @kairnsh, an API-first backend for stateful AI agents. Weโre early but live in private beta. Happy to send a very short overview if interesting.
If openclaw cannot instantly build a product on top of you infra productโฆ stop and rethink your vision. As far as im concerned I gave openclaw a @kairnsh api key and freedom to build an agentic product. It build an agent first documents compiler(input=md/output= branded docx,pdf, pptx โฆ)