🔍 What makes EventHouse the AI data backbone enterprises actually need? We're breaking down: ✅ EventHouse's core capabilities ✅ Its positioning in the AI era ✅ How it helps businesses unlock data value at unprecedented speed — and drive growth in a fast-moving market 👉 Learn more: #EventBridge# #EventHouse# #Cloudnative# #AI# #AIAgent#

# Decision Points in AI Agent Development # Orchestration vs Choreography 🎼 🎯 The Hook When coordinating multiple agents or services, you face a fundamental choice: place a conductor at the center, or let each component dance autonomously? Orchestration means a central authority controls everything. Choreography means each component reacts to events on its own. The locus of control is fundamentally different, and it shapes fault handling, auditing, debugging, and scaling in entirely different ways. 📋 Overview In orchestration, a central orchestrator defines the entire workflow, invokes components sequentially or in parallel, aggregates results, and decides the next step. Temporal, Airflow, and LangGraph's Supervisor pattern are typical implementation platforms. In choreography, each component subscribes to events on an event bus (Kafka, EventBridge, etc.), autonomously processes events it cares about, and publishes new events. No central entity knows the overall control flow. 🔍 Decision Points The primary axis is **accountability**. 🏛️ **Favor orchestration when**: - You need to explain the overall flow and decision rationale at each step after the fact - Strict sequencing constraints exist (review → approval → execution) - LLM outputs need validation or transformation before passing to the next step - Central budget management (tokens, time, cost) is required - Component count is roughly 10 or fewer 🌊 **Favor choreography when**: - High throughput and high scale are required and a central point becomes a bottleneck - Many teams independently develop and deploy components - "Reacting to events" is the primary processing pattern (notifications, logging, async aggregation) - Strict execution order tracking is unnecessary 💡 Key Details 🟢 **Orchestration excels in clarity of control and auditability.** The entire workflow is defined in one place, so "how far have we progressed" and "why was this step executed" are always clear. Recovery from failures pinpoints exactly which step failed and resumes from there. Agent-specific advantage: LLM outputs can be validated before proceeding to the next step, blocking hallucination propagation at each stage. 🟡 **Choreography excels in loose coupling and scalability.** Components share only event schemas and know nothing about each other's existence. Adding a new component is just adding an event subscription -- no changes to existing components. Each component scales independently, with the event bus acting as a buffer to absorb temporary load spikes. ⚖️ Trade-offs | Dimension | Orchestration | Choreography | |---|---|---| | Overall state visibility | Always clear 🟢 | Requires event log correlation 🔴 | | Auditability | High (causal chains are traceable) | Low (distributed tracking needed) | | Scalability | Central becomes bottleneck | Independent component scaling | | Coupling | High (changes concentrate on center) | Low (schema sharing only) | | Hallucination control | Validate at each step | Each component needs own guardrails | | Team independence | Orchestrator changes cause conflicts | Independent development and deployment | 🛠️ Use Cases 🔵 **Orchestration fits**: Business systems, regulated processes, review-approval workflows, processing requiring LLM output validation. Environments demanding accountability. 🔴 **Choreography fits**: High-throughput event-driven processing, notification/log aggregation/analytics pipelines. Large-scale systems where many teams independently develop components. 📌 **Default strategy**: For business systems, orchestration (centralized) is the default. In systems involving AI agents, a central entity that controls and validates LLM's probabilistic outputs is critical for both safety and auditability. A practical compromise is "centralized core, event-driven periphery" -- the orchestrator manages the main business flow while peripheral async processing (logging, notifications, analytics) is loosely coupled via events. #AIAgents# #SoftwareArchitecture#

ATF has upgraded its alert system for federal firearms and explosives licensees to the BEACON/Everbridge platform to strengthen and streamline emergency and other critical communications with licensees. The FFLAlert notification announced Sept. 8, 2026, was an official and authorized ATF communication. Learn more about the new system at

Becoming CEO doesn’t mean you suddenly have all the answers. When Julia Hartz stepped into the CEO role at Eventbrite, she didn’t feel ready. In fact, the first word she uses to describe the transition is “terrifying.” On this episode of Build Mode, Julia talks about learning to lead in real time, the uncertainty that comes with taking the top job, and why even experienced CEOs are sometimes making it up as they go. Watch the full episode:

This Friday will be discussing How Blockchain will Change Everyday life with some amazing Women in Blockchain. Just search for FutureBanking on Eventbrite. The use cases now range across industries including…

Bending Spoons is worth $24 billion. It trades at 8x ARR and buys B2B companies at 2.3x to 2.7x ARR. 5 learnings from its first 102 days as a public company: #1#. Revenue grew 126%. Organic growth was 3%. Nearly all of the $393M of added revenue in Q2 came from six acquisitions. The CEO says he doesn't optimize for organic growth. He optimizes for EPS, which grew 167%. #2#. R&D is 8% of revenue. Sales and marketing is 10%. HubSpot and Datadog each spend about 70% of revenue on those two lines. Bending Spoons spends 18.6%. About 60 people run Vimeo. The core team is under 700 people, at $4M+ of revenue each. #3#. Miro sold at 2.3x ARR, five weeks after Airtable at 2.7x. $1.08B of ARR for $2.64B, signed 37 days apart. Miro was valued at $17.5B in 2022. Bending Spoons underwrites to a 25% unlevered return. At its 54% margin, that supports about 2.2x ARR. #4#. 1,830 people came with AOL, Eventbrite and Vimeo. Only a few hundred were kept. Airtable arrived with 935 employees, more than Bending Spoons’ entire core team. Reorganization costs were $51M in Q2 alone. #5#. AI writes 90%+ of the code. Customers pay about 10% more for the AI features. The CEO says a customer who paid 100 will now pay about 110. The AI gain shows up as capacity: the same 60 people on a business four times the size. If you're at $300M to $800M in ARR growing under 25%, this is the buyer most likely to at least call. But ... the only do a handful of deals a year. Its own stock trades at roughly 7x to 8x revenue. Your revenue is worth about 3x more inside Bending Spoons than it is in your hands.