Best Enterprise Level Agentic AI Platforms for 2026
In 2026, enterprise agentic AI has moved from pilot budgets to production commitments. Salesforce is closing Agentforce deals at 29,000 since launch with $800M ARR. Microsoft Copilot Studio has 160,000 organizations running 400,000+ custom agents. ServiceNow has restructured its entire commercial model around autonomous AI tiers. The question is no longer whether to deploy — […]
How to Build an Advanced Agentic AI System with Planning, Tool Calling, Memory, and Self-Critique Using OpenAI API
TOOLS = { “calc”: lambda expression: _safe_calc(expression), “kb_search”: lambda query, k=3: _kb_search(query, int(k)), “extract_json”: lambda text: _extract_json(text), “write_file”: lambda path, content: _write_file(path, content), } TOOL_SCHEMAS = [ {“type”: “function”,”function”:{“name”:”calc”,”description”:”Safely compute a numeric expression.”,”parameters”:{“type”:”object”,”properties”:{“expression”:{“type”:”string”}},”required”:[“expression”]}}}, {“type”: “function”,”function”:{“name”:”kb_search”,”description”:”Search internal mini knowledge base.”,”parameters”:{“type”:”object”,”properties”:{“query”:{“type”:”string”},”k”:{“type”:”integer”,”default”:3}},”required”:[“query”]}}}, {“type”: “function”,”function”:{“name”:”extract_json”,”description”:”Extract and parse first JSON object from text.”,”parameters”:{“type”:”object”,”properties”:{“text”:{“type”:”string”}},”required”:[“text”]}}}, {“type”: “function”,”function”:{“name”:”write_file”,”description”:”Write content to a file path.”,”parameters”:{“type”:”object”,”properties”:{“path”:{“type”:”string”},”content”:{“type”:”string”}},”required”:[“path”,”content”]}}}, […]
AI is a matter of power, infrastructure and security: TechEx North America
Although visitors to an event like TechEx North America will always want to see the cutting edge front and centre stage, the nuance and detail brought to the show by the speakers and exhibitors mean that it’s sometimes the smaller considerations that need to play big – at least, in the minds of enterprise decision-makers. […]
Meet MemPrivacy: An Edge-Cloud Framework that Uses Local Reversible Pseudonymization to Protect User Data Without Breaking Memory Utility
As LLM-powered agents move from research to production, one design tension is becoming harder to ignore: the more useful cloud-hosted memory becomes, the more private user data it exposes. Researchers from MemTensor (Shanghai), HONOR Device and Tongji University have introduced MemPrivacy, a framework that attempts to resolve this tension without sacrificing the utility that makes […]
Stochastic Gradient Descent (SGD’s) Frequency Bias and How Adam Fixes It
BG = “#fafaf8” DARK = “#1a1a1a” # Color ramp: blue for common tokens, red for rare TOKEN_COLORS = [“#1a5276”, “#2471a3”, “#5dade2”, “#e67e22”, “#c0392b”, “#7d2a2a”] steps = np.arange(N_STEPS) fig = plt.figure(figsize=(16, 11), facecolor=BG) fig.suptitle( “SGD vs. Adam on Rare Tokens — Frequency Bias and Variance Normalization”, fontsize=14, fontweight=”bold”, color=DARK, y=0.99 ) gs = gridspec.GridSpec(2, 3, figure=fig, […]
Six Choices Every AI Engineer Has to Make (and Nobody Teaches)
teach you how to make a model accurate. They rarely teach you the decisions that come right after. How do you know when to fully automate something versus keeping a human in the loop? When does prompting stop being enough and fine-tuning become worth the cost? What does it actually mean to pick real-time inference […]
One Flexible Tool Beats a Hundred Dedicated Ones
when you wanted an LLM agent to talk to a system at the start of 2026 was to install an MCP server for it. GitHub. Jira. Slack. Linear. Postgres. Neo4j. Each one ships a server that exposes a tidy menu of tools, create_issue, list_pull_requests, merge_pull_request, get_repository, search_code, and so on, and you point your agent at it. It’s a great […]
Building Vector Similarity Search in PostgreSQL with pgvector
In this article, you will learn how to implement vector similarity search in PostgreSQL using the pgvector extension, allowing you to find semantically similar results based on meaning rather than keyword matching. Topics we will cover include: What vector embeddings are and how they enable semantic similarity search. How to install and configure pgvector, store […]
Why Your AI Demo Will Die in Production
any time in enterprise AI over the last two years, you know the pattern. A small team builds a proof-of-concept using a state-of-the-art Large Language Model (LLM). The demo is spectacular. The executive sponsor is thrilled. The budget is approved. And then, six months later, the project is… abandoned? The statistics are grim. According to […]
How to Maximize OpenAI’s Codex
articles about Anthropic’s Claude Code, and how I use it for programming, and different techniques that I apply to make it more effective. However, the last two weeks I’ve been experimenting more and more with OpenAI’s Codex and seeing vastly improved results compared to Codex a few months ago. In my opinion, Codex is equally […]