Prompt Engineering Isn’t Enough — I Built a Control Layer That Works in Production
TL;DR debugging the same crash, I stopped blaming the model. It was always the same three problems:broken structured outputs, silent validation failures, and pipelines that looked fine until they didn’t. Tightening the prompt never helped. So I built a control layer above the model — eight components: InputGuard, TokenBudget, PromptBuilder, ResponseValidator, CircuitBreaker, RetryEngine, FallbackRouter, AuditLogger. […]
How to Build a Multi-Agent Research Assistant in Python
In this article, you will learn how to build a multi-agent AI research assistant using the OpenAI Agents SDK, the GPT-5.4 mini model, and the Olostep Web API, including how to wire together a manager agent, specialist sub-agents, and live web tools to produce structured, source-grounded research reports. Topics we will cover include: How to […]
Nvidia Vera chip targets $200bn market as Huang opens a second front
The Nvidia Vera chip is rarely the headline when earnings beat estimates, but it should be. When Nvidia reported Q1 revenue of US$81.62 billion on Wednesday, beating analyst estimates of US$78.86 billion, and guided Q2 at US$91 billion–well above Wall Street’s US$86.84 billion forecast–the numbers did what Nvidia numbers always do: dominate the room. But […]
One Model, Three Modalities: ByteDance Releases Lance for Image and Video Understanding, Generation, and Editing
Building a single model that can both understand and generate images and videos is harder than it sounds. The two tasks pull in opposite directions. Understanding benefits from high-level semantic features tightly aligned with language. Generation needs low-level continuous representations that preserve texture, geometry, and temporal dynamics. Most systems handle this tension by separating the […]
What is a Forward Deployed Engineer: The AI Role OpenAI, Anthropic, and Google Are Hiring in 2026
What is a Forward Deployed Engineer? The term ‘Forward Deployed Engineer’ (FDE) sounds military. That is intentional. A Forward Deployed Engineer is a software engineer who works embedded with the customer’s technical and operational environment on-site, hybrid, remote, or inside a customer cloud or VPC, depending on the engagement. The FDE does not sit at […]
Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm
Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev teams running local or on-premise inference, that number creates real constraints. A new open-source library called turbovec addresses this directly. It is a vector index written in Rust […]
Can LLMs Replace Survey Respondents?
you ask an LLM to simulate 6,000 American households answering questions about inflation? Recent papers find that large language models can replicate the average responses of major household surveys to within a percentage point (Zarifhonarvar, 2026). In 2020, the Survey of Consumer Expectations (SCE) reported a one-year-ahead median inflation rate of about 3%. The median […]
How to Build Knowledge Graph Generation Pipelines From Text With kg-gen, NetworkX Analytics, and Interactive Visualizations
print(“\n” + “=”*70 + “\n SECTION 6 — NetworkX analytics\n” + “=”*70) def kg_to_networkx(graph): G = nx.MultiDiGraph() for e in graph.entities: G.add_node(e) for s, p, o in graph.relations: G.add_edge(s, o, label=p) return G G = kg_to_networkx(g_big) print(f”Nodes: {G.number_of_nodes()} Edges: {G.number_of_edges()}”) H = nx.Graph(G) deg_cent = nx.degree_centrality(H) btw_cent = nx.betweenness_centrality(H) pr_cent = nx.pagerank(nx.DiGraph(G)) if G.number_of_edges() else […]
Optimizing AI Agent Planning with Operations Research and Data Science
to large enterprises, more and more organizations are embracing AI agents and adopting multi-agent architectures to deliver reliable, scalable, and manageable solutions. AI agent and LLM costs can quickly spiral without careful management. In this post, we will uncover several agent planning and cost optimization business problems and frame them as operations research solutions through […]
Agentic Programming: A Roadmap – MachineLearningMastery.com
In this article, you will learn what agentic programming is, how production-grade AI agents are built from the ground up, and what it takes to go from zero experience to shipping a real agent in production. Topics we will cover include: The foundational concepts behind agentic systems, including the agent loop, memory architecture, and tool […]