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Alpesh Kumar

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Six-stage LangGraph multi-agent tutorial roadmap: foundations, supervisor, shared state, routing, persistence, and evaluation.

LangGraph Multi-Agent Systems: Practical Tutorial Series

Alpesh Kumar12 September 2026,,,(0)
A practical, step-by-step tutorial series for building reliable multi-agent systems with LangGraph...
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Building Intelligent Conversational Agents with LangGraph: A Tutorial Guide

Alpesh Kumar5 April 2025,,(0)
Creating sophisticated conversational agents requires more than just a powerful language model. You need a framework that can manage complex...
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Layered AI agent architecture with a visible trajectory moving through reasoning, tools, sandbox, monitoring, and human approval controls

GPT-6 Astra Didn’t Break AI. It Revealed What Was Already Broken.

Alpesh Kumar11 September 2026,,,,,,,,(0)
GPT-6 Astra exposes the limits of response safety, chain-of-thought monitoring, token economics, and sandboxes in autonomous AI systems...
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Architectural blueprint for building ChatGPT apps

Games with Astra: How AI Is Changing Game Development

Alpesh Kumar5 September 2026,,,,,(0)
I have been following the rapid progress of AI-assisted software development, and games with Astra caught my attention because they show a different...
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iPhone 18 Pro Max - A Closer Look at the Camera, Power and Possibilities

iPhone 18 Pro Max. See the Shot. Learn the Settings. Make It Yours.

Alpesh Kumar9 September 2026,,,,(0)
Light, depth and detail: a visual camera settings guide for photographers, camera enthusiasts and iPhone lovers...
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Diagram comparing traditional API integrations with an MCP server connecting AI clients to multiple tools

MCP vs API: What’s the Difference, and How Do They Work Together?

Alpesh Kumar8 September 2026,,,,(0)
APIs expose software capabilities. MCP gives AI applications a standard way to discover and use tools. Here’s how they fit together, with a practical...
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A magnifying glass examines a circled em dash beside the headline A dash of suspicion, illustrating doubts about AI authorship.

Should We Really Be Afraid of an Em Dash?

Alpesh Kumar7 September 2026,,,,,(0)
The em dash has become an unlikely symbol of AI writing. Here is what the evidence actually shows, and how to focus your editing on what helps readers...
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OpenAI Claims We’re in the “AGI Era.” The Catch? It Costs $20,000 Per Test

OpenAI Claims We’re in the “AGI Era.” The Catch? It Costs $20,000 Per Test.

Alpesh Kumar4 September 2026,,,,,,,(0)
OpenAI co-founder Greg Brockman just dropped the line tech executives have been teasing for years: “We are in the AGI era.” The vehicle for this...
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The UUID Primary Key Problem That Shows Up at 200 Million Rows — a framed technical comparison shows a random UUID B-tree scattering inserts and a point lookup fanning into many cold row pages, contrasted with a time-ordered UUID path that keeps inserts and fetched pages locally clustered. Visual direction: idea: a UUID primary-key lookup can find the key quickly yet still cause extreme page reads when random insertion order scatters the B-tree and cold row pages; subject: UUID primary keys at 200 million rows; mechanism: compare random UUID insert distribution across many B-tree leaf pages with time-ordered UUID inserts concentrated at the active edge, then show a point lookup descending the index and fanning out into scattered cold data pages marked by a dense 94,000-read texture; composition: framed comparison — a generous title band across the top, with a large left diagnostic zone for random UUID scatter and a right diagnostic zone for ordered UUID locality, joined only at the bottom by one shared lookup-to-row path; palette: deep forest/moss — pale eucalyptus background, forest-green and near-black ink, muted sandstone page blocks, restrained burnt-orange I/O accents, and a small burgundy warning accent; exclusions: dark navy, neon-blue glow, floating UI cards, network nodes, generic AI circuitry, people, robots, hands, dashboards, logos, fake code, secondary readable text, decorative charts, physical-machine metaphors

The UUID Primary Key Problem That Shows Up at 200 Million Rows

Alpesh Kumar4 August 2026(0)
A primary-key lookup can still become expensive when random UUIDs, cache pressure, and table layout collide. Here is how to diagnose the evidence...
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Design Uber’s AI Demand Prediction and Driver Repositioning System

Design an Uber Demand Prediction and Driver Repositioning System

Alpesh Kumar16 August 2026,,,,,,,,,(0)
Interview question:Uber predicts that ride demand in a particular area will increase significantly in the next 20 minutes. How would you design an AI...
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AI Watermarks Are Not a Silver Bullet: What Provenance Signals Can and Cannot Prove — a warm ivory technical diagram shows a media file with an embedded watermark band and a linked provenance record feeding an evidence tray, then stopping before separate source, context, and corroboration checks, representing that C2PA metadata and watermarks inform origin but cannot independently prove accuracy, ownership, or context. Visual direction: idea: provenance signals are useful evidence but stop short of editorial truth; subject: C2PA Content Credentials and embedded AI watermarking; mechanism: a media file carries an embedded watermark while a separate provenance record supplies origin/history information, both entering an evidence tray before a hard boundary requiring source, context, and corroborating-evidence checks; composition: landscape editorial explainer card with the exact headline in the upper third and a lower horizontal proof-boundary schematic; palette: warm ivory, ink charcoal, muted brick red, moss green, soft ochre, pale stone gray; exclusions: dark navy, neon-blue glow, floating UI cards, network nodes, generic AI circuitry, people, robots, hands, dashboards, physical-machine metaphors, decorative charts, logos, secondary readable text.

AI Watermarks Are Not a Silver Bullet: What Provenance Signals Can and Cannot Prove

Alpesh Kumar13 August 2026,(0)
C2PA metadata and embedded signals can offer helpful evidence about an image's origin. They cannot, on their own, prove that an image is accurate...
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AI Agent Frameworks Compared: Vercel AI SDK, LangGraph, CrewAI, AutoGen and LangChain — a framed comparison diagram visually separates streaming provider-flexible TypeScript output, branching and resumable orchestration, role-based collaboration, conversational agents, and modular integration building blocks, showing why framework selection follows architecture rather than a universal winner.

AI Agent Frameworks Compared: Vercel AI SDK, LangGraph, CrewAI, AutoGen and LangChain

Alpesh Kumar14 August 2026,,,(0)
A practical, source-led comparison of five AI frameworks. Choose from your application architecture, streaming needs, and agent workflow rather than a...
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Alpesh Kumar
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