JetBrains vs Tricentis

How AGI Became a Marketing Department Case

The article discusses how AI, particularly coding agents, is transforming the role of software developers. It highlights that 90% of professional developers use such tools weekly, with 68% daily, and about a third are 'agentic coders' who generate 84% of their code via AI. This shift is changing the developer's role from generalist to specialist, and now to a 'Forward Deployed Engineer' who works closely with clients. The article emphasizes that the real value of developers is shifting from pure coding capacity to understanding business context, identifying problems, and making sound technical decisions. It draws on examples from Google Research and the hiring practices of OpenAI and Anthropic, and suggests that businesses should focus on teams that can quickly build domain context rather than just counting developers.

• 90% of professional developers use coding agents weekly, 68% daily (JetBrains survey).
• One third of developers are 'agentic coders' generating 84% of their code via AI.
• Google Research is investigating whether software agents understand standards and collaborate with developers.

AI Agents Redefine Software Developer Role Toward Context

This opinion piece examines how AI coding agents are reshaping software development, shifting developers' value from implementation to understanding business context and making architectural decisions. JetBrains' survey shows 90% of professional developers use such tools weekly (68% daily), with about a third now 'agentic coders' who let AI generate an average of 84% of their code. This transformation has popularized the 'Forward Deployed Engineer' role at OpenAI and Anthropic, which focuses on client collaboration. The author argues that while AI simplifies coding, experienced developers' true worth lies in contextual understanding, risk identification, and solution validation. The piece advises clients to prioritize contextual insight over mere technical capacity.

• 90% of professional developers use coding agents at least weekly, 68% daily (JetBrains Developer Ecosystem Survey).
• About one-third of developers are 'Agentic Coders', with AI generating 84% of their code on average.
• OpenAI and Anthropic are expanding 'Forward Deployed Engineer' roles, with Anthropic hiring in Munich.

On-Device LLM Chatbot with Kotlin and TensorFlow Lite

This technical tutorial describes how to build an on-device large language model (LLM) chatbot for Android using Kotlin and TensorFlow Lite. It outlines a simple architecture (Chat UI -> ViewModel -> LLM repository -> Tokenizer -> TensorFlow Lite interpreter -> Local model), project setup, model loading, tokenization, background inference with Kotlin coroutines, incremental token handling, conversation-history management, quantization options (FP16, INT8, weight-only) and mobile performance metrics to benchmark (load time, first-token latency, tokens/sec, RAM, battery, thermal). The guide also covers error handling and security considerations (prompts stay on device but APK/model extraction risk), and links to example SDK repos and a Discord community.

• Tutorial outlines an on-device chatbot architecture using a Kotlin Android UI, tokenizer, TensorFlow Lite interpreter, and a local model.
• It shows how to load a .tflite model from app/src/main/assets and initialize a TensorFlow Lite Interpreter in a background runner.
• The guide recommends running inference off the UI thread using Kotlin coroutines (e.g., viewModelScope + Dispatchers.Default) to avoid UI freezes.

Tricentis Opens Riyadh Office to Support Growing Demand Across Saudi Arabia

New office marks the company's second location in the Middle East and supports enterprise and...

Tricentis Launches AI Innovations for Agentic Development

Tricentis announced a set of AI-powered technologies developed via Tricentis Labs to advance agentic quality engineering and accelerate enterprise software development. Revealed at the Tricentis Transform conference, the innovations include Tricentis Aida (an autonomous application-exploration AI agent), Tricentis AgentScore (a probabilistic framework to evaluate AI agents), and Tricentis Release Risk Intelligence (AI-driven release risk and remediation guidance). The release notes the company’s recent acquisition of Tabnine and positions Tricentis Labs as an incubator to co-develop early AI capabilities with customers and partners. The update aims to help engineering and release teams identify quality risks earlier, validate AI-powered systems, and make faster, more informed release decisions.

• Tricentis announced new AI-powered innovations at its Tricentis Transform conference.
• Three technologies were introduced from Tricentis Labs: Tricentis Aida, Tricentis AgentScore, and Tricentis Release Risk Intelligence.
• Tricentis Labs is an innovation incubator intended to give customers early access and collaboration opportunities for emerging AI technologies.