๐ข๐ฝ๐ฒ๐ป๐๐ ๐ท๐๐๐ ๐น๐ฎ๐๐ป๐ฐ๐ต๐ฒ๐ฑ ๐๐ด๐ฒ๐ป๐๐๐ถ๐, ๐ฎ ๐ณ๐๐น๐น ๐๐๐ฎ๐ฐ๐ธ ๐ณ๐ผ๐ฟ ๐ฏ๐๐ถ๐น๐ฑ๐ถ๐ป๐ด, ๐ฑ๐ฒ๐ฝ๐น๐ผ๐๐ถ๐ป๐ด, ๐ฎ๐ป๐ฑ ๐ฒ๐๐ฎ๐น๐๐ฎ๐๐ถ๐ป๐ด ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐ด๐ฟ๐ฎ๐ฑ๐ฒ ๐ฎ๐ด๐ฒ๐ป๐๐.
Until now, enterprise teams had to juggle orchestration scripts, eval pipelines, and custom UIs.
AgentKit unifies it all:
ย โขย Agent Builder: visual workflow canvas with versioning and guardrails
ย โขย ChatKit: embeddable chat UI toolkit
ย โขย Evals 2.0: datasets, trace grading, and auto-prompt optimization
Ramp reports a 70% faster iteration cycle; LY Corp built a multi-agent workflow in under 2 hours.
This marks a clear line: LLMs arenโt โappsโ anymore, theyโre operational systems.
Start with one high-value workflow, wire it through Builder + Guardrails, and measure with Evals.
Save this post to reference when your team scales its first agent and follow for more insights!
#AgenticAI #MLOps #EnterpriseAI #Governance #KnowledgeGraphs
Leading the Human-Centered Project Leadershipโข Movement | Building the global standard for people-first project delivery | Founder at The PM Playbook
16 hours ago
Huge leap forward for enterprise AI. Unifying build, deploy, and eval in one stack is exactly what teams need to move from experiments to real operational systems.
Senior Software Architect @ SBS | AI Architect | Cloud Architect
1 day ago
the unified toolkit finally addresses what devops faced years ago. fragmented deployment tools killing velocity. curious about versioning rollback strategies when an agent's behavior degrades in prod unexpectedly?
Global Electronic Trading Engineer | OMS/RMS/EMS โข Market Microstructure | Buy & Sell-Side | Leads High-Performance Teams
1 day ago
This is phenomenal Julian Hernandez
Now, this is game changing.
Wondering what will happen to startups like n8n, Zapier, and Make
They're pretty much done.