Uploaded June 2026 | Updated September 2026, 37 minutes ago
Agentic coding tools have made writing code faster but they haven't touched the 80% that actually slows teams down: bug fixing, testing, PR review, and context documentation.
Twilio Champion David Poindexter breaks down why AI coding assistants are creating a growing backlog of large, context-free pull requests, and why, without proper guardrails, they'll default to writing Python even on your Ruby project.
Q: Why does AI default to Python?
Because most AI coding models were trained heavily on Python — written by data scientists who knew Python. Without language-specific guardrails, it drifts.
Q: What's the fix?
Train your AI assistant with explicit skill sets and guardrails tied to your actual stack and project conventions.
If you're using agentic coding tools like Claude Code, Codex, Cursor, or GitHub Copilot on your team, this one's worth 60 seconds of your time.
🔔 Subscribe for more developer insights from Twilio Champions and the TwilioDevs community. twil.io/sub-twiliodevs
💻 Sign up for a Twilio account here: twil.io/trytwilio-yt
#AgenticCoding #AITools #DeveloperTips #CodeReview #TwilioDevs #SoftwareEngineering #AICodeAssistant
Agentic coding tools have made writing code faster but they haven't touched the 80% that actually slows teams down: bug fixing, testing, PR review, and context documentation.
Twilio Champion David Poindexter breaks down why AI coding assistants are creating a growing backlog of large, context-free pull requests, and why, without proper guardrails, they'll default to writing Python even on your Ruby project.
Q: Why does AI default to Python?
Because most AI coding models were trained heavily on Python — written by data scientists who knew Python. Without language-specific guardrails, it drifts.
Q: What's the fix?
Train your AI assistant with explicit skill sets and guardrails tied to your actual stack and project conventions.
If you're using agentic coding tools like Claude Code, Codex, Cursor, or GitHub Copilot on your team, this one's worth 60 seconds of your time.
🔔 Subscribe for more developer insights from Twilio Champions and the TwilioDevs community. twil.io/sub-twiliodevs
💻 Sign up for a Twilio account here: twil.io/trytwilio-yt
#AgenticCoding #AITools #DeveloperTips #CodeReview #TwilioDevs #SoftwareEngineering #AICodeAssistant




![Turn Conversations into Action: A Deep Dive into Conversation Intelligence
Is your AI just listening, or is it acting? Discover how to turn live customer conversations into real-time business outcomes with Twilio Conversation Intelligence.
In this deep dive, we explore the reasoning layer of the Twilio Conversations stack. Once your infrastructure is connected and your context is persistent, the next step is applying intelligence. We’ll show you how to leverage programmable, GenAI-powered Language Operators to provide real-time guidance to human agents, trigger backend workflows, and ensure your AI agents perform safely and effectively in production.
Using the Voltana dealership scenario, we demonstrate how real-time signals like Next Best Response and Next Best Action drive measurable ROI by increasing conversion rates, lowering handle times, and improving overall customer satisfaction.
In this video, we cover:
- The Three Pillars: Live agent assist, real-time automation, and AI agent observability.
- The Architecture: How to use Intelligence Configurations to bundle rules, operators, and actions.
- GenAI at Work: Real-world examples of Next Best Response, Sentiment Analysis, and Lead Scoring.
- The Voltana Demo: Seeing real-time signals transform a customer journey.
- Operational ROI: Feeding conversation insights into your analytics stack (Tableau, etc.).
Key Moments:
[00:00] The Reasoning Layer: Why AI Needs to Do More Than Respond
[01:07] Architecture: Intelligence Configurations, Rules, and Operators
[01:33] The Three Pillars: Agent Assist, Automation, and Observability
[03:35] The Voltana Demo: Using GenAI Operators in Real-Time
[05:14] Driving Conversion: How Next Best Action Resolves Issues
[06:00] Analytics & ROI: Turning Conversations into Structured Data
[06:50] Series Preview: What’s Next (Agent Connect)
Explore the series:
Watch the previous video on Conversation Memory: https://youtu.be/DPeFiBht0jc
Learn more about building with Twilio Conversations: https://www.twilio.com/en-us/products/conversational-ai/conversation-memory
💻 Sign up for a Twilio account here: https://twil.io/trytwilio-yt
👉 Subscribe for more Twilio updates: https://twil.io/sub-twiliodevs
#Twilio #ConversationIntelligence #GenAI #CustomerExperience #CXStrategy #DeveloperTools #NextBestAction #ConversationalAI #TwilioConversations Turn Conversations into Action: A Deep Dive into Conversation Intelligence](https://i.ytimg.com/vi/qzhWLKIOTAg/mqdefault.jpg)





![The Future of Customer Experience: A Deep Dive into Twilio Conversations
Conversations with Artificial Intelligence are going to continue to be more common. Stop frustrating customers. AI alone wont fix your customer experience. Its only as good as the infrastructure it plugs into. Discover how to connect your customer journey with Twilio Conversations.
In this video, we explore why adding AI to a fragmented customer experience often creates more friction than it solves. Most companies channels operate in silos—voice, messaging, and data are disconnected. To truly leverage the power of AI, you need a unified layer that keeps every interaction continuous across human and AI agents.
This is the first video in our series on building a continuous customer experience. We’ll follow the journey of a customer named Jordan, showing how a connected backend powers a seamless front-end experience.
In this video, we cover:
- Why AI isnt the magic bullet for customer experience.
- The dangers of fragmented infrastructure.
- An introduction to the four pillars of Twilio Conversations: Orchestrator, Memory, Intelligence, and Agent Connect.
For more information, check out https://www.twilio.com/en-us/products/conversational-ai
💻 Sign up for a Twilio account here: https://twil.io/trytwilio-yt
👉 Subscribe for more Twilio updates: https://twil.io/sub-twiliodevs
Key Moments:
[00:00] Why AI Needs Connected Infrastructure
[00:33] The Problem with Fragmented Systems
[02:40] Introducing the Customer Journey (The Voltana Example)
[03:04] Defining the Unified System
[03:23] Overview of Conversation Orchestration Components
[03:42] Series Preview: What’s Next
#Twilio #CustomerExperience #AI #CXStrategy #DeveloperTools #Omnichannel The Future of Customer Experience: A Deep Dive into Twilio Conversations](https://i.ytimg.com/vi/sMJl0fhVLkE/mqdefault.jpg)