{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"The Future of Multi Model AI Workflows with Jonathan Archer","description":"How can developers use multiple AI models without constantly switching tools or hitting rate limits? In Episode 199 of Open Tech Talks, Kashif Manzoor speaks with Jonathan Archer, co-founder of OpenLLM, about AI gateways, Bring Your Own Key (BYOK), multi-model AI workflows, AI coding agents, and the future of developer productivity. As developers increasingly use Claude, ChatGPT, Grok, Gemini, and other AI models, managing multiple subscriptions, API keys, usage limits, and development environments is becoming a real challenge. Jonathan explains how an AI gateway can provide a unified endpoint for multiple AI providers, letting developers route requests between models and create fallback workflows when a provider hits a usage limit or goes down. The conversation also explores why multi-model AI development could become increasingly important. Instead of relying on a single AI provider throughout an entire workflow, developers can assign different models to different tasks such as planning, coding, reviewing, and fixing. Jonathan shares how this approach can improve results while reducing costs and avoiding blind spots that can occur when the same model evaluates its own work. Kashif and Jonathan also discuss AI-assisted software development and graph engineering, where multiple AI agents work together in structured loops to solve problems. They explore how these workflows are changing the way developers build software and how AI coding tools can enable very small teams to develop sophisticated products. Beyond technology, Jonathan shares practical lessons from building and launching OpenLLM. The discussion covers customer discovery, product development, workshops, cold outreach, social media marketing, AI-generated content, and the challenges solo founders and small startup teams face. The episode also covers security and privacy, including how AI gateways handle credentials, why local processing can matter, and why developers should pay close attention to AI providers' terms of service when using subscription-based AI access. The episode concludes with advice for beginners who want to learn coding and build their own products using AI coding tools. Jonathan\u2019s message is straightforward: start experimenting, build something small, learn by doing, and become someone who uses AI rather than someone who fears it. Episode # 199 Today\u2019s Guest: Jonathan Archer, Co-Founder, OpenLLM His work focuses on improving the developer experience around AI models, reducing rate-limit interruptions, and enabling developers to combine different models for coding and agentic workflows. Website: OpenLLM What Listeners Will Learn: How Bring Your Own Key AI Works Why Developers Use Multiple AI Subscriptions How AI Gateways Reduce Workflow Interruptions How Fallback Chains Work Across AI Models Why Multi-Model Agent Workflows Can Produce Better Results How Different AI Models Can Complement Each Other How AI Coding Agents Are Changing Software Development How Developers Can Build AI Products With Small Teams How Customer Feedback Drives AI Product Development How to Market an Early-Stage AI Product Why Security and Terms of Service Matter in AI Gateways How Beginners Can Start Building With AI Coding Tools Why AI Skills Are Becoming Essential for Developers How to Start Learning AI-Assisted Coding Today Resources: OpenLLM ","author_name":"OPEN Tech Talks: AI worth Talking| Artificial Intelligence |Tools & Tips","author_url":"http:\/\/www.otechtalks.tv","html":"