# AI Agent Development Frameworks ADK-TS Helps Developers Build Advanced AI Agents With Minimal Code By Ell Smith | Published 2026-07-31 | Tech Source: Trend Hunter, https://www.trendhunter.com/trends/adkts References: [adk.iqai](https://adk.iqai.com/?ref)  Creating sophisticated AI agents often requires managing complex integrations, memory systems, and conversation workflows. ADK-TS is a comprehensive framework designed to help developers build smart, [tool-using AI agents](https://www.trendhunter.com/trends/potpie-ai) with just a single line of code. The platform supports multiple large language models, advanced tool integrations, memory capabilities, and [flexible conversation flows](https://www.trendhunter.com/trends/ultra-ai-1), making it easier to create powerful AI applications. Designed for developers building next-generation AI experiences, ADK-TS provides the infrastructure needed to create reliable and adaptable agents without unnecessary complexity. By simplifying agent development, the framework helps teams move from ideas to functional AI systems faster. ADK-TS gives developers a flexible foundation for building intelligent agents that can reason, use tools, and interact more naturally with users. Image Credit: ADK-TS ## Trend Insights (Trend Hunter) - Score: 3.7/10 - Popularity: 11% | Activity: 15% | Freshness: 85% - Audience gender: 50% men, 50% women - Primary generations: Millennial - Top markets: North America ## Categories [Trend Hunter](https://www.trendhunter.com/trends) > [Tech](https://www.trendhunter.com/tech) ## Key Themes ### What's Driving This Trend - **Low-code Agent Development:** Minimal-code frameworks are reducing technical barriers for teams building sophisticated AI agents, creating room for faster experimentation and more specialized software products. - **Tool-using AI Agents:** AI systems that can access external tools, memory, and workflows are expanding automation beyond chat interfaces into complex task execution across business functions. - **Flexible AI Orchestration:** Multi-model support and adaptable conversation flows are enabling developers to design agents that better match varied user needs, enterprise systems, and operational contexts. ### Who This Affects Most - **Software Development:** Frameworks that simplify agent infrastructure are reshaping how developer teams prototype, deploy, and scale intelligent applications with fewer engineering resources. - **Enterprise Automation:** Agent-based systems with memory and tool integration are creating new possibilities for automating multi-step workflows across operations, service, and knowledge management. - **Artificial Intelligence:** The rise of accessible agent-building platforms is accelerating competition around modular AI ecosystems, developer tooling, and specialized intelligent applications. ## Related on Trend Hunter - [AI Chatbot Platforms](https://www.trendhunter.com/trends/talk-to-agent.md) - [AI Agent Builder Platforms](https://www.trendhunter.com/trends/one-ai-market.md) - [AI Governance Toolkits](https://www.trendhunter.com/trends/runtime-toolkit.md) - [Domain-Specific Agentic Platforms](https://www.trendhunter.com/trends/c3-code.md) - [AI Developer Tools](https://www.trendhunter.com/trends/tiptap-ai-agent.md) - [Developer Productivity Platforms](https://www.trendhunter.com/trends/turingmind-ai.md) - [AI App Development](https://www.trendhunter.com/trends/tbcai.md) - [AI Coding Development Platforms](https://www.trendhunter.com/trends/kiro-1.md) - [AI Application Development Platforms](https://www.trendhunter.com/trends/21st.md)