Abacus. AI and the case for unified AI workflows The post How to Navigate the Shift from Prompt-Based Tools to Workflow-Driven AI appeared first on Towards Data Science .
Understanding ow LLMs interact with the world around them, from returning data to taking action The post Tool Calling, Explained: How AI Agents Decide What to Do Next appeared first on Towards Data Science .
Building manager–specialist workflows with the OpenAI Agents SDK The post Using Agents as Tools appeared first on Towards Data Science .
Computer-use AI agents struggle with multi-step workflows like email and customer support. Echoverse trains agents in realistic environments rather than simply providing more training tasks, helping them improve as the tasks, tests, and environments evolve.
A practical data engineering onboarding workflow for environment setup, automated testing, and AI-assisted development. The post Your First Task as a Data Engineer in a New Company?
The article titled "Is Agentic AI Just Automation?" argues that many so‑called agents are merely flowcharts in disguise. It explains why this misconception exists and suggests what kinds of systems should be built instead to achieve true agentic AI.
Map AI value, design workflows, redefine talent, upgrade the executive team, and measure the business impact. The post Redesign Work Before You Add More AI Agents appeared first on Towards Data Science .
How one open-source ecosystem made state-of-the-art AI accessible The post The Python Ecosystem That Changed AI Development appeared first on Towards Data Science .
The article "How to Work with AI Coding Agents" offers a practical guide aimed at improving code quality rather than merely increasing quantity. It focuses on strategies and best practices for effectively collaborating with AI coding tools to produce better code. The post was originally published on Towards Data Science.
Become a more productive software engineer with LLMs The post How to Perform Effective Project Management with AI appeared first on Towards Data Science .
The article discusses how AI-native companies such as Basis, Clay, and Exa Labs employ AI agents to enhance various business processes, including onboarding, account management, and developer integrations. It highlights the practical applications of these AI-driven workflows for enterprise leaders, illustrating how they can be adopted in similar contexts.
AI has accelerated data scientists’ productivity, but its influence extends beyond speed. The technology is reshaping who owns data, how judgment is exercised, and the overall career trajectory of data scientists. These changes signal a broader transformation in the field’s structure and responsibilities.
from custom integrations to a universal standard for tool access The post MCP Explained: How Modern AI Agents Connect to the Real World appeared first on Towards Data Science .
