We’re excited to announce the launch of the next version of https://t.co/tlKiYSlfeJ. You can now build and deploy DeepAgents in hours—not weeks—without the heavy lifting of designing architectures, stitching tools with LLMs, or doing complex context engineering, just like the big

12/12 11)Multi-Agent Orchestration: Managing the Digital Workforce In 2026, the challenge shifts from building one AI to managing a "digital workforce." Without coordination, specialized agents (Sales, Legal, Procurement) can work at cross-purposes or get stuck in infinite

11/12 10)Don’t Rip and Replace—Build on Top Replacing an existing SaaS or legacy application takes time, budget, and change management—and it often slows adoption because teams lose familiar workflows. What works Leverage the existing database and APIs as the source of truth.

10/12 9)Open-Source Models: Control Without the Chaos Open-source models work best for internal tools, department assistants, data-sensitive workflows, and high-volume tasks where cost matters. What works Deploy different models by department/use case (not one model for

9/12 8)Token Economics: The Hidden Cost of AI Adoption Most companies don’t think seriously about AI usage economics until the first surprise bill hits. With agentic systems, cost doesn’t just scale with users—it scales with behavior. What drives runaway cost agents looping or

8/12 7)Keep Your Company’s “Secret Sauce” Secret With AI tools (OpenAI and other LLMs), the risk is letting sensitive information leak or be used in ways you didn’t intend—especially if you paste proprietary strategy, pricing logic, customer lists, source code, or internal

7/12 6) AI Can Hallucinate—and the Mistakes Can Get Expensive Hallucinations aren’t just funny slip-ups. In a business setting, they can turn into: wrong legal language (bad clauses, misleading terms) incorrect financial numbers (wrong metrics, wrong calculations) fabricated

6/12 5) Guardrails First: Security for Agentic AI Agentic AI doesn’t just answer questions—it can take actions and share information. Without strong controls, risk grows fast: sooner or later something sensitive will be exposed, either internally or externally. High-risk

5/12 4) Data Readiness: The Real AI Foundation AI is only as effective as the data it can access—safely and reliably. Most rollouts struggle when: information is scattered across too many tools documents and knowledge aren’t structured or searchable permissions are inconsistent

4/12 3)The Pilot Trap: Why AI Never Reaches Production A lot of companies aren’t failing at AI—they’re stuck in pilots and proof-of-concepts that never change how the business runs. The usual culprits are predictable: trying to automate everything at once unclear ownership

3/12 2)The Human Bottleneck in AI Adoption Most leaders know AI is coming—but many don’t have a clear operating plan. Meanwhile, employees often hear “AI” and think, “Is this replacing me?” That uncertainty creates resistance, slows experimentation, and can quietly kill

2/12 1. Shadow AI Is Already Inside Your Company (Without Governance) Every employee is already using personal AI accounts—ChatGPT, Gemini, Claude—for real work: drafting emails, summarizing docs, analyzing spreadsheets, even writing code. And in the process, people routinely

1/12 2026: The Year AI Stops Being Optional After working with multiple companies on implementing Enterprise AI, here are the top friction points we see—and what works. There will be two kinds of companies in 2026. Companies that Adopt AI: They redesign how work gets done,

This is my 10th TiECON, and it feels very different. We are witnessing a fundamental shift in technology—one that will deeply shape the future of humanity and entrepreneurship. We’re in a moment where technology is redefining how we work, live, and build. I’m looking forward to

🔥RemoteAgent transforms @PhilipsHealth's customer journey in 10 mins, cutting drop-offs & adding $3.6M in revenue! Name one company that matches this: https://t.co/zKuiKrdWsj Future’s here — why lag behind?

Don’t settle. @OpenAI's GPT-5 was just the warm-up! McKinsey-style competitor reports that used to take a month? RemoteAgent chews them up before your coffee cools. Here’s RemoteAgent’s competitor benchmarking for Nike, Adidas, and Lululemon: https://t.co/B605RuElyI The best

🩺RemoteAgent's @CVSHealth dashboard dissected May-July 2025 data with surgical precision for MinuteClinic’s preventive care strategy. From eye health spikes, targeted regional campaigns, and inventory smarts, RemoteAgent’s genius is a must-have for your company too!

RemoteAgent's dashboard for @UPS: Turning July 2025 route data into a fuel-saving masterpiece. $95K/year in electric fleet wins, served with unmatched brilliance. 🪄Nothing short of data wizardry!