IBM Developer

Chief Architect, Gabe Goodhart built a local AI coding assistant with Granite 4, Ollama, VS Code, and Continue. He walks through the full workflow — including the architecture and how to run it locally: ibm.biz/BdpqfH

Interested in quantum computing? With over 13 million downloads, Qiskit is the world's most popular open-source quantum computing stack for building and researching quantum algorithms. Dive deeper into Qiskit and our quantum ecosystem here: ibm.co/6010EHDuY

🚀 Langflow V 1.8 is live Langflow 1.8 represents a structural leap in how AI solutions are built, integrated, and scaled. This release makes Langflow more mature, more powerful, and ready for intelligent agents in production, going beyond prototypes and experiments. With 1.8, Langflow is simpler to configure, easier to integrate, faster to use, and prepared for the next generation of AI agents, from visual workflows to production code. What’s new in this release: 🔹 Model Provider Setup Model configuration now follows a single, reusable standard, reducing manual setup, configuration drift, and errors when scaling projects. 🔹 API Redesign (Phase 1) Flows can now be consumed via standardized APIs, making Langflow a more predictable and robust part of applications, systems, and backends. 🔹 Chat Refactor (Playground Improvements) Improved session and message management delivers more stable interactions and a smoother experience when working with long or complex conversations. 🔹 Inspection Panel Direct access to component configuration, parameters, and optional inputs directly from the workspace panel, reducing context switching and accelerating debugging and iteration. 🔹 Knowledge Bases Built-in knowledge bases act as local vector databases inside Langflow, making it easier to store and retrieve documents and datasets while enabling retrieval-augmented workflows. 🔹 Traces Trace support provides deeper visibility into workflow execution, helping developers follow execution paths, measure latency, track token usage, and debug complex flows more easily. 🔹 Agentics Adds structured data workflow components, including N→N transformations (aMap), N→1 aggregations (aReduce), 0→N generation (aGenerate), and DataFrame merging without LLM calls, unlocking practical use cases like data enrichment and aggregation. 👉 Explore Langflow 1.8 and start building production-ready AI agents: langflow.org/blog/langflow-…

@NaugaiGautam Congratulations! Great work. 👏

Happy to announce that I’ve achieved my Prompt Engineering Certificate! @IBMDeveloper

Ready to try it? Sign up for access to IBM Bob → ibm.com/products/bob

There’s a lot of noise around AI IDEs. @if54uran walks through how IBM Bob works with real-world Java codebases, analyzing dependencies and supporting modernization at scale. ⬇️

Enterprise Java isn’t about typing faster. It’s about understanding the system first. @myfear shares a technical perspective on how IBM Bob supports planning and controlled change in real Java codebases:ibm.co/601887E3q

@trustinvibe Cute and collaborative indeed!

IBM just introduced Project Bob he's pretty cute character ibm.com/products/bob

One last look before logging off for the holidays 👀 // nothing on fire // see you 2026-0105T00:00:00Z

🎁 Folks, Langflow 1.7 is here! We’ve got an early holiday drop packed with upgrades for building serious AI agents & MCP servers. Better transports, stronger agents, real auth, cloud storage, and new components. Let’s gooooo! 👇

@LFAIDataFdn 💪

As we wrap up 2025, we’re proud of the momentum behind Docling, an LF AI & Data project making documents ready for GenAI. From PDFs to images to structured outputs, Docling is built for real-world AI pipelines. Get involved: hubs.la/Q03YF1kh0 #OpenSource #GenAI #DocumentAI

@kingofkush710 @IBM @IBMResearch @IBMData 😌🤌

Try Quarkus basics, a beginner’s guide to modern Java, by @myfear: ibm.biz/quarkusbasics

No more waiting on builds. With live coding and zero redeploys, Quarkus lets you iterate faster and stay in flow.

3 ways Quarkus levels up Java, with @myfear 🧵👇

ClickOps doesn’t scale. How Python SDKs let teams build data pipelines as code—versioned, automated, and ready for AI agents. 0:00 Why click-ops break 0:27 Pipelines as code 1:36 Programmatic workflows 3:55 AI agents in production 6:05 Observability youtu.be/R43Q0nIXa1Q

@CrivetiMihai Thanks for sharing!

@IBMDeveloper Check out this blog demoing ContextForge Desktop: heidloff.net/article/contex…

You need a way to secure MCP servers. Forge on with MCP ContextForge, an open-source, secure, governed MCP gateway. 1.0 Beta now on Github ⬇️ ibm.co/6010BQwiO