More Bobcoins to build, debug, and iterate with IBM Bob, at no extra cost. Free trial: 1.25× more Bobcoins Pro: 1.25× more Pro Plus: 1.125× more Ultra: 2× more Explore the update: ibm.co/6016Epa9E

Once deployed, Bob IDE and Bob Shell connect to your organization’s hosted backend. Teams can use these clients with the backend running on infrastructure their organization manages.

Getting things running takes two stages with bobctl: First, create the cluster-wide resources. Then, install Bob into a namespace using namespace-level permissions.

IBM Bob Self-Hosted is now supporting @nvidia Nemotron and Poolside Laguna. After a year of rigorous model evaluation and optimization alongside NVIDIA, the IBM Bob team selected these models to power on-premises and air-gapped enterprise deployments. Read more about the selection process → ibm.co/6017Epm5d

No text. No chat. Just probabilities. @if54uran demos Jev, a new kind of AI model designed to make quick and efficient decisions.

Today, IBM is announcing self-hosted deployment for IBM Bob. Explore how this update brings agentic software development to where your most sensitive code already lives: ibm.co/6014Epk0I

Announcing the Artificial Analysis Cyber Index and the Artificial Analysis Cyber Index Alliance, a new standard for evaluating AI models on enterprise cyber defense The Artificial Analysis Cyber Index Alliance brings together industry partners to create a new standard for evaluating how AI models perform on enterprise cyber defense tasks. The Alliance launches alongside the Artificial Analysis Cyber Index, which combines three partner-contributed and open benchmarks to evaluate how well agents find and fix vulnerabilities. As models demonstrate increasingly advanced cyber offense capabilities, it becomes more relevant for AI labs and companies alike to understand how models perform on cyber defense tasks and which perform best. We’re announcing the Cyber Index Alliance today with @CollinearAI, @IBM, @nvidia, and @vercel as launch partners. Benchmarks in the Artificial Analysis Cyber Index: ➤ CWE-Bench-AA, from @CollinearAI, covers auditing and patching: 120 held-out tasks spanning all ten OWASP Top 10 (2025) categories, across C/C++, Go, Java, JavaScript/TypeScript, Python and Rust. ➤ DeepsecBench-AA, from @vercel, isolates discovery: Given a codebase and a budget, the agent needs to find every vulnerability present, and is scored against a golden set of findings from human security reviewers. Real findings are rewarded and benign code flagged as vulnerable is penalized. ➤ CyberGym-E2E-AA, from @BerkeleyRDI, runs end to end: Find the memory-safety bug, write a proof-of-concept that triggers the crash, then patch it so the crash no longer reproduces. Key results: ➤ Grok 4.7 (xhigh) and MiMo-V2.6-Pro lead the Cyber Index scoring 56, followed by GPT-6 Luna (max, 53), GLM-5.3-Flash (50) and Muse Spark 1.3 (xhigh, 44). ➤ Safety refusals hold back several frontier models: GPT-6 Sol (max), GPT-6 Astra (max), Claude Opus 5.5 (max with fallback), Claude Fable 5.1 (max with fallback) and Gemini 3.8 Flash (high) decline tasks representing 32-38% of the Cyber Index on safety grounds. Despite frontier agentic coding capabilities, they trail the leaders by 19 to 31 points. Most of the gap comes from CyberGym-E2E-AA, where GPT-6 Sol and GPT-6 Astra refuse every task, Claude Opus 5.5 refuses 98% and Claude Fable 5.1 refuses 99%.

Bob TV: Episode 2: with yours truly and @if54uran ! Tokenmaxxing: How Much Context Does AI Coding Really Need? Tue, Oct 6, 2026 11:00 AM EDT (5:00 PM Europe/Berlin) ibm.webcasts.com/starthere.j… #Register #Free @IBMDeveloper #IBM

Starting next week, builders of every background will be putting IBM Bob to work as they design and deploy real solutions. Are you ready to build with them? Check out the challenge themes and get started: ibm.co/6015ETxgx

Choosing the right local LLM tool can be tough. @cedricclyburn shares his take with a tier list to make the decision a little easier. How would you rank them? Let us know below.

Turn one BRD into a multi-agent solution with five AI agents, Python tools, and a knowledge base. Follow Ahmed Azraq and Allen Chan as they use the Launch Bob feature in watsonx Orchestrate to build, test, evaluate, and deploy the solution: ibm.co/6015ETZQf

👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 👏 developers 👏 Happy world developer day :)

Same coding agent. Completely different outcomes. Context can be the difference between a rough response and production-ready software. @TechCowgirlBri explains why: ibm.co/6013ETVBh

Can’t miss me being welcomed by Ryan to the @StackOverflow #podcast to talk about why your coding agent should be writing #Java. We talk about why the long history of Java both makes for a stable language and a source of training data for AI. On top of that, we discuss how agentic Java excels by working with powerful partners: a massive ecosystem of Java libraries and agentic harnesses. stackoverflow.blog/2026/09/0… @IBM @IBMDeveloper