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ISE Developer Blog
Solving global tech challenges, sharing insights, and empowering developers
Latest posts
Teaching a Vision Model to See Like a Human Annotator—and Catching It When It Lies
A multimodal LLM enrichment pipeline that extracts structured metadata from visual assets, constrains output to predefined values to minimize hallucinations, and uses a ground truth evaluation template to measure quality—all as a plug-and-play module.
From Noisy Queries to Precise Frames: Query Decomposition for Media Asset Search
How query decomposition separates metadata filters from visual intent to significantly improve media asset retrieval quality.
Enabling MLflow OpenAI Autolog on PySpark Workers
When distributing LLM calls across PySpark workers via mapInPandas, MLflow autolog silently fails. Here is how to fix it.
Passing Context Between Agents in Multi-Agent A2A Systems
How we solved the challenge of passing conversational context between independently deployed agents using the A2A protocol's embedded context pattern, keeping domain agents stateless and secure.
Separating Deterministic Extraction from AI Inference in Industrial Summarization
When 100% of our prototype outputs were valid JSON but 0% met the data contract, we discovered the LLM was doing work that software should own. A field classification exercise and 4-pass pipeline brought schema compliance from 0% to 100%.
Orchestration Patterns for Multi-Agent Systems: Performance and Trade-offs
Real-world lessons from evolving a production chatbot into a coordinator-based multi-agent architecture, including performance trade-offs for enterprise-scale agent reuse.
How we Decide Between Keyword and Hybrid Search: 5 Enterprise Evaluation Criteria
A data-driven framework we use in enterprise deployments to decide between vector-only keyword and hybrid search, based on five measurable evaluation criteria.
Verification-driven tooling prompts for fast-moving codebases
A practical pattern for using GenAI research agents to produce reliable internal tooling by verifying assumptions with detection classes and a final checklist.
Coordinating AI-Assisted Development with AGENTS.md and Skills
How to move AI-assisted development from ad-hoc experimentation to a coordinated team-wide capability using AGENTS.md and reusable skills with GitHub Copilot CLI